quasi-2d liquid state at metal-organic interface and ......green and blue lines correspond to...
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Quasi-2D Liquid State at Metal-Organic Interface and Adsorption State Manipulation
by
Masih Mehdizadeh
A thesis submitted in conformity with the requirements for the degree of Master of Applied Science
Department of Materials Science & Engineering University of Toronto
© Copyright by Masih Mehdizadeh 2017
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Quasi-2D Liquid State at Metal-Organic Interface and
Adsorption State Manipulation
Masih Mehdizadeh
Master of Applied Science
Department of Materials & Engineering
University of Toronto
2017
Abstract
The metal/organic interface between noble metal close-packed (111) surfaces and organic
semiconducting molecules is studied using Scanning tunneling microscopy and
Photoelectron Spectroscopy, supplemented by first principles density functional theory
calculations and Markov Chain Monte Carlo simulations. Copper Phthalocyanine molecules
were shown to have dual adsorption states: a liquid state where intermolecular interactions
were shown to be repulsive in nature and largely due to entropic effects, and a disordered
immobilized state triggered by annealing or applying a tip-sample bias larger than a certain
temperature or voltage respectively where intermolecular forces were demonstrated to be
attractive.
A methodology for altering molecular orientation on the aforementioned surfaces is also
proposed through introduction of a Fullerene C60 buffer layer. Density functional theory
calculations demonstrate orientation-switching of Copper Phthalocyanine molecules based
on the amount of charges transferred to/from the substrate to the C60-CuPc layers;
suggesting existence of critical substrate work functions that cause reorientation.
iii
Acknowledgments
This work in many ways is a result of the support provided by my supervisors, colleagues,
family, and friends, each in their own way. I’d like to extend my thanks and gratitude to
Professor Jun Nogami for giving me the freedom to explore problems that were of interest
to me during the course of my degree and always making himself available despite his busy
workload. I’d also like to thank Professor Zheng-Hong Lu, whose device fabrication lab was
where I started my work. He took the time to help and provide a sense of direction and also
supported my transition to Professor Nogami’s research group when I realized my interests
lie in the fundamental physics of the metal-organic interface.
Further thanks to Dan Grozea who was always there to lend a helping hand. And last but not
least, I’d like to thank my family and friends for their loving support.
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Table of Contents
Acknowledgments........................................................................................................... iii
Table of Contents ............................................................................................................ iv
List of Tables .................................................................................................................. vi
List of Figures ................................................................................................................ vii
Chapter 1 ...........................................................................................................................1
Introduction ..................................................................................................................1
1.1 Motivation .............................................................................................................1
1.2 Background ...........................................................................................................3
1.3 Outline...................................................................................................................4
Chapter 2 ...........................................................................................................................6
Methods & Materials....................................................................................................6
2.1 Materials ...............................................................................................................6
2.1.1 Copper Phthalocyanine .............................................................................6
2.1.2 Fullerene C60 .............................................................................................8
2.2 Experimental Methods ..........................................................................................9
2.2.1 Scanning Tunneling Microscopy ..............................................................9
2.2.2 Photoemission Spectroscopy ..................................................................11
2.3 Simulations & Calculations ................................................................................12
Chapter 3 .........................................................................................................................14
Entropic Order in Phthalocyanine Films on Nobel Metals ........................................14
3.1 Introduction .........................................................................................................14
3.2 Liquid Phase of Submonolayer CuPc Films .......................................................16
3.2.1 Imaging of Short Range Order Signature ...............................................16
v
3.2.2 Origin of Interference-like Patterns Observed ........................................19
3.3 Entropic Order & the 2D Liquid-Solid Phase Transition ...................................24
3.3.1 2D Monte-Carlo Simulations ..................................................................24
3.3.2 A Brief Look at the Liquid-Solid Phase Transition ................................28
3.4 Dual Adsorption States & Immobilization of Molecules ...................................30
3.5 Summary .............................................................................................................36
Chapter 4 .........................................................................................................................37
Molecular Orientation Control ...................................................................................37
4.1 Introduction .........................................................................................................37
4.2 Pc Monolayer Films on (111) Metal Surfaces ....................................................38
4.2.1 Lattice Measurement & Adsorption Geometry Using STM ...................38
4.2.2 CuPc Monolayer on Ag(111) ..................................................................41
4.2.3 F16CuPc Monolayer on Ag(111)............................................................45
4.3 Reorienting CuPc Molecules ..............................................................................47
4.3.1 Introduction of a Buffer Layer ................................................................47
4.3.2 Introduction of a Buffer Layer ................................................................50
4.3.3 Charge Transfer & Buffer-Enhanced Substrate Interactions ..................53
4.3.4 Proposed Method for Molecular Reorientation of Pc Molecules ...........57
4.3.5 Summary .................................................................................................58
Chapter 5 .........................................................................................................................59
Summary & Future Work...........................................................................................59
5.1 Summary .............................................................................................................59
5.2 Future Work ........................................................................................................61
References or Bibliography ............................................................................................63
Copyright Acknowledgements........................................................................................67
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List of Tables
Table 3.1: Summary of results for binding energies calculated based on DFT, The binding
energies of various configurations have been calculated and presented above.
The ‘No Substrate’ column refers to gas phase configurations. The ‘s’ and ‘f’
suffixes refer to standing and flat-lying orientations respectively …….….... 55
vii
List of Figures
Figure 2.1 | Phthalocyanine family and their relation to parent compounds. a-b,
Molecular structure of molecules. (a) Porphine on the left, the parent compound of
Phorphyrazine, found on the right. (b) Child compound of Porphyrazine: Phthalocyanine on
the left. Its metal complex derivative CuPc in the center and its derivative F16CuPc on the
far right. ……………………………………………………………………………..……... 7
Figure 2.2 | Fullerene C60, Also known as buckminsterfullerene has a van der Waals
diameter of 10.0A and has the soccer ball shape depicted above.
…………………………………………………………………………………………….... 8
Figure 2.3 | STM Lab Equipment. Room temperature Omicron STM with modified
chambers that house a LEED system as well as sputtering and deposition sources.
………………..............................................................................................................…….10
Figure 2.4 | PES Lab Equipment. Kurt J. Lesker MAC cluster tool with an attached PHI
5500 system (the chamber to the far right).
…………………………………………………………………………………………..… 12
Figure 3.1 | STM images of Cu(111) and Ag(111) surfaces under various CuPc coverage.
a-c, Spatial images of Cu(111) on the top panels and Ag(111) on the bottom. (a) 0.4ML
coverage,(b) 0.8ML coverage, and(c) 1.0ML coverage.
……………………………………...………………………………………………...…… 17
Figure 3.2 | STM images of standing-wave-like patterns on submonolayer covered
Cu(111) surface. a, Spatial image of Cu(111) covered with 0.9ML of CuPc on the left and
an example of fluctuations in the local density of states on the Cu(111) surface due to electron
scattering on the right (borrowed from the Yukio Hasegawa group at University of Tokyo).
b, The Cu(111) surface covered in 0.75ML of CuPc on both left and right panels. Image in
the left panel has been scanned at a bias of 0.5V and -1.5V on the right. The spacing between
the second and third peaks shown in the insets (red line) in each panel, zooming in on the
area close to the step edge on the bottom left of each image. The spacing is 1.95nm in both
scans, as well as on images collected with biases in between -1.5V and 0.5V.
…………………………………………………...………………………………………... 18
Figure 3.3 | Distribution of 1D hard rods on a line of finite length a-d, Analytically
calculated probability distribution in position along the a line of length 50nm for rod densities
corresponding to (a) 0.1ML, (b) 0.4ML, (c) 0.7ML, and (d) 0.95ML coverage.
…………………………….................................................................................................. 20
Figure 3.4 | 1D model compared to STM images along symmetry directions on both Cu
and Ag samples, The surfaces of (a) Ag(111) and (b) Cu(111) at a coverage of 0.85ML. The
green and blue lines correspond to line-cuts taken along the shortest path between two
impurity points on Ag and Cu respectively. The selected impurity pair on each surface was
chosen to insure similar geometry on both surfaces. (c) The STM height profiles in blue and
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green (Cu and Ag respectively) are plotted against theoretically calculated values in red.
STM height profiles have been normalized and shifted along the y-axis for clarity.
…………………………...………………………………………………………………... 22
Figure 3.5 | Illustration of a few cases in the hard rods model demonstrating root cause
of non-uniform distribution functions, (a) shows two cases where the first rod X1 has
landed at the boundary and another where it has landed in the middle of the line. The areas
in green highlight available space for a second rod to land. The available space for a third
rod to land is demonstrated for two different cases in (b). As it can be seen both diagrams at
the top in (a) and (b) have higher probabilities of surviving addition of another rod, hence
demonstrating the reason for high probability aggregation of rods at the boundaries and the
oscillatory behavior respectively. ……………………………………………………….... 24
Figure 3.6 | Monte Carlo simulation results of 2D liquid of hard disks. a-c, calculated
positional distribution function: normalized configuration-averaged disk positions, obtained
from a two-dimensional histogram of positions of disks. Simulation box size of 30nm was
used and results were calculated for (a) fully periodic boundary conditions, (b) periodic
boundaries with an impurity point of radius 0.8nm in the center of the box, and (c) closed
boundary conditions with an impurity of the same radius at the center of the box.
………………………………………….............................................................................. 26
Figure 3.7 | Experimental and simulation result comparison. a-b, Comparison of STM
image of CuPc-covered substrate with corresponding Monte Carlo Simulations. STM images
in the top left panels, Monte Carlo simulated positional probability distributions in the top
right, and comparison of line-cuts taken along both in the bottom panels. (a) Ag(111) surface
at a coverage of 0.85ML. Periodic boundary conditions used in the simulations. (b) 0.85ML
coverage on Cu(111), with closed boundary conditions used to mimic the effects of a step-
edge. ……………………………………………………………………………………… 28
Figure 3.8 | Liquid-Solid phase transition in the CuPc sub-monolayer films. a-d, Spatial
images of Cu(111) at various coverage close to critical phase transition density. (a) 0.85ML
coverage, (b) 0.92ML coverage; molecules can almost be made, as in the liquid phase has
transitioned to its solid counterpart, (c) 0.95ML coverage; Rhombic order starting to emerge,
and (d) 0.98ML coverage, long range order emerging.
…………………………………………………………………………………………….. 29
Figure 3.9 | STM images of sub-monolayer CuPc films annealed. a-c, Spatial images of
Ag(111) at 0.4ML coverage annealed for 30 minutes up to a temperature of (a) 500K, (b)
630K, and (c) 770K.
…………………………………………………………………………...………………... 31
Figure 3.10 | STM images of patterning of CuPc molecules on Cu(111) and bias
threshold plot for pinning. a-b, Spatial image of tunneling electron induced chemisorbed
CuPc. (a) “CUPC” written with a single pass of the STM tip at V=+4.5V, I=1.5nA, and scan
speed of 16nm/s. Inset is a zoom-in on the “C”, scanned at V—1.5V, I = 300pA.(b) Indicated
square of size 25nm on a 0.5ML covered Cu(111) surface has been scanned at V=2.8V,
I=1.2nA for 60min. Then imaged with parameters: V=1.8V, I=300pA. (c), Bias dependence
of induced CuPc chemisorption. Turn-on happens at V>2.0V. This figure has been adapted
ix
from earlier work done in the group by T. Stock et al. [48].
…………………………………………………………………………………………...... 33
Figure 3.11 | STM images of pinning of CuPc molecules on Ag(111) and bias threshold
plot for pinning. a-b, Spatial STM images collected at a bias of V=+1.7V, current setpoint
of 600pA. (a) Image of the area and surroundings of where the pinning was done before
pinning. Red square highlights the area exposed to high bias. (b) Image of the same area as
in a) after high speed high bias scans at V=+4.0V, I=1.5nA, and scan speed of 20nm/s.
……………………………………………...……………………………………………... 34
Figure 4.1 | STM images showing sub-monolayer C60 coverage of the Ag(111) surface.
Image was captured with the following set parameters: 0.5ML C60 on Ag(111), V=0.1 V,
I=200 pA. The C60 ordered domain appearing in the bottom left corner of the image has
adopted the (2√3×2√3)𝑅30° structure referenced to the Ag(111) lattice, as can be seen
from the inset image at the top right.
……………………………………………………………………………...……………... 40
Figure 4.2 | STM image of the Ag(111) surface covered in 0.5ML C60 and 0.5ML CuPc.
Image was captured with the following set parameters: V=-0.5 V, I=300 pA. The image
shows selective adsorption of CuPc molecules onto the bare Ag(111) surface, once deposited
onto the 0.5ML C60 covered Ag(111) surface.
……..………………………………………………........................................................… 42
Figure 4.3 | 2D crystal phases of CuPc molecules selectively adsorbed onto the
Ag(111)+0.5ML-C60 surface. Both images in a) and b) were captured with the following
set parameters: V=-0.5 V, I=300 pA. a) Given the C60 ordered domain has adopted the
(2√3×2√3)𝑅30° structure (referenced to the Ag(111) lattice), it can then be deduced that
the CuPc rows which make an angle of 120 degrees with the (2√3×2√3)𝑅30° structure’s
high symmetry direction (equivalent to Ag(111)’s [-110] direction) are in fact lying along
the [-2-21] direction of the underlying lattice. b) This image displays a rotationally symmetric
phase of the CuPc molecules, rotated by 60 degrees. The inset shows the lattice vectors of
the CuPc crystal.
…………………………………………………………...………………………………... 44
Figure 4.4 | 2D crystal lattice of F16CuPc molecules selectively adsorbed onto the
Ag(111)+0.5ML-C60 surface. Both images in a) and b) were captured with the following
set parameters: V=-0.8 V, I=800 pA. a) Given the C60 ordered domain has adopted the
(2√3×2√3)𝑅30° structure (referenced to the Ag(111) lattice), it can then be deduced that
the rows are aligned with the [-1-10] direction of the Ag(111) lattice. b) The unit cell
primitive lattice vectors were measure to be a=1.55+-0.05nm, b=1.52+-0.05nm with the
angle between them being 72+-3 degrees. Each set of rotated rows indicated existence of a
variety of unit cells.
…………….………………………………………...…………………………………….. 46
x
Figure 4.5 | Results of UPS experiments on the C60-CuPc interface summarized in an
energy level diagram. The shift in the local vacuum level at the interface indicates formation
of an interfacial dipole as well as possibly a surface dipole moment at the CuPc-vacuum
interface. The shift in the position of the HOMO of CuPc to 0.68eV from 0.93eV when at
bulk also signals band bending and transfer of charge across the interface.
………………………………………………………………………………...……….….. 50
Figure 4.6 | STM image and epitaxial models of 1ML of CuPc deposited on the Ag(111)
surface covered with 1ML of C60. This figure is borrowed from earlier work done by
Taylor J. Stock. a) an oplique unit cell of the superstructure moire patterns is laid out. b)
Cartoon of CuPc packing in the standing orientation along the <-110> direction. This
periodicity is in fact synchronous with the moire pattern in the direction of vector a. c)
Epitaxial models for the brickstone and herringbone phases. Adapted with permission from
ref. [64]. ……………………………………………………………………………...…... 51
Figure 4.7 | STM images of 0.5ML of CuPc deposited on Ag(111) covered with 1ML of
C60, a) STM image of CuPc molecules shows an entirely different structure than the flat-
lying orientation. It closely resembles the Moire patterns observed on the Cu(111)-C60
system. b) The height profile at the step edge shows a height of 0.5nm, making it difficult to
confirm a standing orientation or else due to the convoluted nature of STM and dependence
of tunneling on both of topography and local density of states.
………………………………………………..………………………………………….... 52
Figure 4.8 | Difference in DFT-calculated binding energies of standing and flat-laying
CuPc orientation on C60, a) Difference in binding energy of the two orientations plotted as
a function of net charges added/removed from each unit cell. b) Models of the supercells
used for calculating the binding energies for the standing and flat-lying orientations.
……………………………………………...…………………………………..…………. 56
Figure 4.9 | Proposed steps for achieving charge transfer threshold for reorienting
CuPc stacking, The choice of buffer layer, its thickness, as well as the substrate can
effectively result in an equilibrium charge distribution state that can lead to reorienting the
CuPc molecules. The diagram illustrates the steps needed to do so as well as the role of each
step described below it. ............…………………………………………………………... 57
1
Chapter 1
Introduction
1.1 Motivation
Globally, there are two major sectors which have the potential to contribute immensely to
sustainability and advancement of the world civilization, energy and computation respectively.
On the energy front, growing demands in energy consumption and large emissions of
greenhouse gases due to overuse of cheap energy sources such as fossil fuels have made global
warming quite a great concern over the past decades. This has created a need for green sources
of energy which can sustainably be employed; the largest source of which is solar energy.
However, solar technologies are not widespread in their global application (though gaining
great traction in recent years) due to high manufacturing costs when compared to pre-existing
fossil fuels. Negative environmental impacts of fabrication and materials in some cases for
higher efficiency solar cells has been a bottleneck as well.
On the other hand, the computation (for the lack of a better word) sector here generally defined
as a sector where any form of machinery or device which can compute or perform a function
(such as transistors, diodes, light emitting diodes, various circuitry and electronic chips,
processing units, and in turn computers) is involved; has been growing in an exponential
manner, heavily impacting and advancing many other fields along with itself. Observing and
learning from abundantly available forms of machinery in nature, we see many hints at
existence of greater complexity of materials and interactions, contrary to that seen in man-
made tools for computation which seem to be quite rudimentary when compared and contrasted
to naturally occurring computational power houses. With advancements in physics,
nanotechnology, chemistry, and engineering we have come to better understand the world at
the molecular and atomic scales which has brought upon a new era of technologies, though
barely touching the surface when put into perspective, however with great potential.
2
Given the above point of view on computation, the solution to the energy crisis and more
efficient and cost-effective capture of solar energy along with many other advancements lies
within progression of computation, as defined generally as above. Thus far, most
computational tools developed and researched have been based off of highly ordered single
crystalline materials, with the most widely used materials being Silicon. Such materials are
more easily modelled and understood due to their rather simple structures, thus have been an
ideal candidate for research and development. In recent years however, organic materials have
come under the spotlight for the purpose of computation. Organic electronics has emerged as
an exciting field of interdisciplinary research and development over the past few decades.
Extending across various fields of academic research such as physics, materials science,
chemistry, and engineering, it has demonstrated rapid growth and has led to development of
new and more efficient technologies. While organic semiconductors aren’t necessarily destined
to replace silicon-based technologies today, they bring about a world of possibilities given their
rather complex and abundant structure as well as the possibility of creating fully flexible
optoelectronic devices such as solar cells, displays, diodes, and solid-state lighting devices.
With already successfully implemented commercial applications of organic semiconducting
materials in organic optoelectronic devices such as displays and solar cells, further growth and
expenditure is expected to fuel the field in the years to come.
Not only are such organic molecules of interest for the purpose of thin film devices as discussed
above, they are also the heart of a relatively newly budding field: molecular electronics. As
silicon-based technologies have advanced over the years and devices have reached smaller and
smaller scales, we have embarked upon regimes where quantum mechanical phenomenon such
as tunneling have become unavoidable. An important instance of this issue is present in
manufacturing of Central Processing Unit (CPU) chips which house many small transistors,
densely packed at the nanometer scale. We have now reached a packing density of transistors
which limits intact operation of each device; currents of charge carriers tend to ‘leak’ from one
device to the next due to tunneling, thus leaving researchers with no options than to account
3
for the quantum effects at such scales. Whilst molecular electronics research is in its early
infancy days, it is made rather obvious by nature and its various forms of machinery that
fabrication of computational devices with the caliber of those found in biological systems,
requires understanding of interactions, control, and fabrication methodologies at the molecular
scale.
1.2 Background
Organic optoelectronic devices are normally composed of layered structures with thicknesses
in the nanometer scale and can be fabricated using cost-efficient methods such as vacuum
coating, roll-to-roll printing, and in some cases solution processing. Organic LEDs, thin film
transistors, diodes, and photovoltaics are all optoelectronic devices in which the main active
materials are entirely composed of organic semiconducting materials. As opposed to their
inorganic counterparts, there is no need for perfectly ordered crystal structures, since each
individual molecule discretely exhibits semiconducting properties. This provides an advantage
over traditional inorganic semiconductors such as GaAs and Si which require perfectly ordered
single crystals to form the band structure expected for a semiconductor and to be used for the
purpose of operation in a device. Organic materials are also available in an immense variety of
structures and properties which has made them an ideal candidate for applications in
optoelectronics. Optical and electronic properties of many polymers and molecules can be
adjusted through modification of chemical structure and molecular design. The charge
transport mobilities in such Van der Waals bonded solids is limited by overlap of the molecular
Van der Waals radii and is generally limited to µ < 10 cm2/Vs [1-3]. Thus, molecular stacking,
orientation, and order in molecular films is highly important a factor for achieving high
conductivity. As a result, many early studies and applications of such molecular materials have
been focused on ordered molecular crystals and polycrystalline films which provide the best
electronic transport properties.
4
The importance of molecular stacking and orientation is also vivid when looking at the discrete
nature of organic semiconducting molecules which results in the lack of intrinsic charge
carriers within the organic layers. This means the molecular layers behave as insulators unless
charges (electrons and holes) are injected into them from the electrodes (cathode and anode
respectively). As such, the performance and efficiency of organic optoelectronic devices
depend highly on the efficiency of charge injection as well as the aforementioned role played
by transport. The efficiency in charge injection also heavily relies on molecular orientation at
the electrode-organic interfaces, which determine the potential barrier charge carriers are faced
with when being injected into the organic layer.
Thus, forming recipes for high efficiency organic optoelectronic devices relies on
understanding the intermolecular interactions as well as electrode-organic interactions that
determine the sort of emerging molecular order in the organic layers. Knowledge of the
physical mechanisms involved as well as predictable modelling can allow for design and
fabrication of layered devices which can attain highest measures of performance and
efficiency. The same understanding and ability to model and predict molecular assembly would
also count as a triumph in the field of molecular electronics and can lead to design and
fabrication of novel devices.
1.3 Outline
The remainder of this thesis tends to the problem at hand: study of intermolecular and
substrate-molecule interactions at metal-organic interfaces. A combination of experimental
and theoretical means are deployed to further our understanding of interactions at a few
archetypal metal-organic interfaces and to reveal the mechanisms involved in controlling
molecular stacking and orientation. The following chapter, Chapter 2 details the experimental
methods, materials, and models used in this work. Chapter 3 goes on to present the physics of
the interface between coinage metal (111) surfaces and the archetypal organic semiconducting
5
molecule, Copper Phthalocyanine (CuPc). Chapter 4 presents a potential methodology for
reorienting CuPc molecules and proposes a physical mechanism responsible for change in
molecular stacking as a result. Finally, Chapter 5 summarizes the major findings in this work
and discusses potential future work.
6
Chapter 2
Methods & Materials
2.1 Materials
The organic materials studied in this work consist of the archetypal small molecule organic
semiconductor: C60 Fullerene (i.e. Buckminsterfullerene) as well as two members of the
Phthalocyanine family of molecules, specifically Copper Phthalocyanine (CuPc) and Copper
Hexadecafluoro-Phthalocyanine (F16CuPc).
2.1.1 Copper Phthalocyanine
Phthalocyanines are not readily found in nature. However they are efficiently synthesized at large
scales [4]. The parent compound of Phthalocyanines is meso-tetraazaporphin, commonly referred
to as porphyrazine (see figure 2.1). Porphyrazine itself is based on porphin, with substitution of
the four meso-methin bridges in porphin by nitrogen atoms. Porphin is also the parent compound
of porphyrin and its various complexes which normally play an active role in many biological
systems ranging from chlorophyll in photosynthesis to heme as the oxygen-binding agent in red
blood cells. Similar to porphyrins, phthalocyanines also form complexes with many elements.
Presently, metal complexes of Phthalocyanine molecules are widely produced and used in industry
as pigments. In recent years however, unsubstituted Phthalocyanine (H2Pc), its metal complexes
(MPc), peripherally substituted phthalocyanines such as hexadecafluoro-phthalocyanine
(F16H2Pc) and its metal complexes (F16MPc) have attracted considerable attention in the context
of devices and surface physics. The delocalized π-conjugated nature of electron bonds extended in
phthalocyanines makes them an attractive candidate for optoelectronic applications. The π – π*
electronic transition from the Highest Occupied Molecular Oribital (HOMO) of the π-bonds to the
Lowest Unoccupied Molecular Orbital (LUMO) leads to an optical band gap that promotes strong
optical adsorption in the visible spectrum for most MPc molecules such as CuPc [5-6]. Chemical
7
functionalization and change of the central atom lead to changes in relative and absolute
positioning of the HOMO and LUMO energies [7]. Furthermore, due to the π-π overlap in
molecular solids, a transport band gap of around 2.2eV is also observed [8-9]. The combination of
electrical and optical properties of phthalocyanines, especially metal phthalocyanines such as
CuPc make favorable candidates for applications in optoelectronics.
Figure 2.1 | Phthalocyanine family and their relation to parent compounds. a-b, Molecular
structure of molecules. (a) Porphine on the left, the parent compound of Phorphyrazine, found on
the right. (b) Child compound of Porphyrazine: Phthalocyanine on the left. Its metal complex
derivative CuPc in the center and its derivative F16CuPc on the far right.
8
2.1.2 Fullerene C60
Buckminsterfullerene (C60) molecules are a member of the fullerene family which includes C60,
C70, and C84 to name a few. Fullerene molecules are made of carbon atoms arranged in a closed
shell-like structure which mimic the shape of a soccer ball (i.e. a truncated icosahedron), composed
of twenty hexagonal and twelve pentagonal faces. Carbon atoms reside at the vertices of these
faces, forming bonds to their nearest neighbors along the edges of the polygonal faces (see figure
2.2). Fullerenes been found to occur in nature, detected in soot as well as in outer space [10-12].
The C60 Fullerene molecules were first discovered in 1985 by Harold Kroto et al [13] after
theoretical predictions that preceded in the 1960s and early 1970s [14]. Since then, C60 molecules
have attracted much attention and have been intensely studied due to their unique geometry and
electronic properties. The HOMO-LUMO gap is measured to be approximately 2.3 eV [15], thus
similar to phthalocyanines, C60 molecules display insulating characteristics. In the solid form,
C60 molecules form weakly bound molecular crystals, thus very much so preserving their
molecular properties with discrete energy levels and minimal broadening. Injection of charge
through a conducting interface or doping with metals can make C60 behave as semiconducting
molecules with an electronic band gap of 1.5-2.3 eV in thin films [16].
Figure 2.2 | Fullerene C60, Also known as buckminsterfullerene has a van der
Waals diameter of 10.0A and has the soccer ball shape depicted above.
9
The combination of the unique geometry of the molecules, weak intermolecular van der Waals
interactions, and strong electronic interactions with metallic substrates has made the metal-C60
interface family allows for tuning of intermolecular distances and orientations through choice of
the substrate materials. C60 molecular crystals for a face-centered cubic (fcc) lattice, with a lattice
parameter of 14.17A for the bulk structures [17]. On various metal surfaces such as Cu(111) and
Ag(111), C60 forms close-packed structures with various lattice parameters depending on the
substrate. On Cu(111) for instance, a commensurate lattice is formed in the C60 layer which is due
to the closely matched lattice parameters of the Cu(111) surface and the C60 over-layer. The
favorable electronic properties of C60 molecules and the aforementioned characteristic interfacial
interactions of metal-C60 interfaces have led to applications in a variety of optoelectronic devices
such as OLEDs, OTFTs, OPVs, and other devices [18-22]. Additionally, the adsorption of C60
molecules on metallic surfaces has been of particular interest due to its potential for applications
in molecular electronics [23].
2.2 Experimental Methods
2.2.1 Scanning Tunneling Microscopy
The STM experiments were carried out using an Omicron UHV RT-STM (setup shown in figure
2.3); samples were prepared, measured, and analyzed in a single UHV chamber (housing the STM
itself as well) with a base pressure of 5.0e-11 Torr. All imaging was performed at room
temperature. Pt-Ir tips were mechanically cut and placed onto the STM head for measurements.
Tip manipulation and optimization was often done through a combination of in situ Ar+ sputtering,
field emission onto the clean substrates, as well as mechanical grazing of the tip on clean metallic
clips using the course piezo motors. The collected images have been corrected for linear lateral
drift [24] where noted, as well as calibrated to reproduce the well-known Cu(111)-C60-p(4x4) and
Ag(111)-C60-(2√3×2√3)𝑅30 structures where applicable.
10
Single crystal Copper and Silver substrates cut along the (111) plane were purchased from
Princeton Scientific Corp., with an orientation accuracy of less than 0.1 degrees. Both Ag(111)
and Cu(111) atomically clean surfaces were prepared in situ by several cycles of Ar+ sputtering
and subsequent annealing at ~900K. Annealing of the samples and substrates was done via a
ceramic radiative heating element attached to the back of the sample plate on the manipulator
arm’s sample holder head and temperatures were monitored using a Raytek optical pyrometer
mounted outside the chamber, pointed at the sample through a window.
Figure 2.3 | STM Lab Equipment. Room temperature Omicron STM with
modified chambers that house a LEED system as well as sputtering and
deposition sources.
Molecular sources were outgassed in situ prior to deposition; heated slowly to temperatures just
below those required to achieve detectable deposition whilst keeping chamber pressures below
1.0e-9 Torr. The samples were then outgassed at the mentioned temperature for several hours.
C60, CuPc, and F16CuPc molecules were all deposited at room temperature in situ at a typical rate
11
of 0.5ML/min from fused quartz K-Cells at normal incidence to the samples. Deposition rates were
monitored using an in-situ quartz crystal microbalance (ML: Monolayer, referring to a full
coverage of surface by the molecules; having considered molecular orientation and packing
density). In the case of coverage dependent experiments, deposition was done in steps up to a full
monolayer on the same sample, at each step yielding a surface with a known sub-monolayer
coverage of CuPc molecules.
2.2.2 Photoemission Spectroscopy
Photoemission Spectroscopy (PES) experiments on thin films were done in collaboration, by
Yiying Li of the Lu group. HOPG substrates were prepared ex situ using the scotch tape method
and organic overlayers were deposited in situ in a Kurt J. Lesker multi access chamber (MAC)
cluster tool with an added chamber for a PHI 5500 multi-technique surface analyzer; shown in
figure 2.4. The PHI 5500 come equipped with a hemispherical electron analyzer and two photon
sources: a high energy Al Kα source (hv = 1486.6 eV) for X-ray Photoemission Spectroscopy
(XPS) and a He I (hv = 21.22 eV) discharge lamp for Ultraviolet Photoemission Spectroscopy
(UPS). The PES chamber has a base pressure of ~5.0e-10 Torr with the other deposition chambers
as well as the central distribution chamber maintaining base pressures of ~1.0e-9 Torr.
12
Figure 2.4 | PES Lab Equipment. Kurt J. Lesker MAC cluster tool with an
attached PHI 5500 system (the chamber to the far right).
2.3 Simulations & Calculations
To complement experimental observations and help explain the physics of interactions, first
principles Density Functional Theory (DFT) calculations as well Monte Carlo simulations were
employed in this study. DFT calculations were done in collaboration, by Phil De Luna of the
Sargent group at the University of Toronto using the Vienna Ab Initio Simulation Package
(VASP). The Projector Augmented Wave (PAW) method was used to perform calculations with
greater efficiency. Van der Waals interactions were also accounted for and all calculations were
carried out on SciNet’s General Purpose Clusters (GPCs). The Monte Carlo simulations were done
for the 2D hard disks problem using custom written Python scripts. To avoid the inefficiencies of
direct sampling, Markov Chain Monte Carlo methods were employed in conjunction with the
13
Metropolis-Hastings algorithm to sample the phase space. Though massively parallel Monte Carlo
methods were not employed, various calculations on various systems with different sizes and
densities were simultaneously run in parallel on SciNet’s GPCs in order to accelerate the
computation times.
14
Chapter 3
Entropic Order in Phthalocyanine Films on Nobel Metals
3.1 Introduction
Understanding the mechanisms responsible for growth and self-assembly of molecular materials
such as the archetypal organic semiconductor Copper Phthalocyanine (CuPc) on various surfaces
is an essential step towards design and creation of complex nanostructures from such molecular
building blocks and is also important for optimization of performance in organic electronic devices
such as organic light-emitting diodes and solar cells. Such structures of interest are typically grown
on metallic surfaces and can have a variety of factors affect their growth and self-assembly, of
which, some of the most prominent are the intermolecular interactions amongst the molecules and
interaction of the molecules with the metallic substrate. Electronic and geometric properties of the
interface which are related to device performance and efficiency, such as molecular orientation,
charge transfer, band alignment, and dipole formation are all heavily influenced by the nature of
the interactions in the very first adsorbate layer, as the first layer acts as a template upon which
further layers are adsorbed. Characterization of the nature of molecule-substrate and molecule-
molecule interactions at the submonolayer regime is thus an integral step towards gaining such
control.
In the last decades, a range of studies has attempted to quantify the strength of such interactions
and relate them to growth, ordering, and self-assembly of the molecules [25-30,36-40]. Studies
range from experimental to theoretical fronts; deploying various surface techniques to characterize
interactions and explaining observations through the use of first principals Density Functional
Theory (DFT) calculations and scouring of the system energy landscape for minima that would
lead to stable lattice configurations and molecular orientations [30-40,43,57]. However, given the
dependence of such calculations on the choice of Exchange-Correlation functionals, system size,
15
and initial conditions (such as initial spatial positioning of the molecules) calculations have not
been able to lead the way and to make meaningful predictions. Experiments have generally led the
way in the field and calculations have followed as a complementary analytical tool to explain
experimental observations and to suggest mechanisms responsible for such observations [36-
40,43].
Various detailed experimental investigations have been reported on the various CuPc-Metal
interfaces [36-40]. In fact, adsorption behavior of CuPc molecules were compared directly using
X-ray and Ultraviolet Photoemission Spectroscopy (XPS/UPS), SPA-LEED, and XSW
experiments by Stadtmuller et al., Kroger et al., and Stadler et al. on the (111) surfaces of Ag, Au,
and Cu [36-37,41-43]. Transfer of charge between the substrate and the Lowest Unoccupied
Molecular Orbital (LUMO) of the CuPc molecules has been reported (at low temperatures for
annealed CuPc films) on Ag and Cu, with Cu interacting more strongly with the overlayer, leading
to a larger amount of charge transfer than its Ag counterpart. The origin of the claimed attractive
and repulsive intermolecular forces in the case of Cu and Ag respectively have been attributed to
the exchange of charges between the molecules and the surface [42,43]. The studies have been
done on the Au(111) surface as well and the molecular interaction with the substrate in each case
has been ranked, with Au(111) being the most weakly interacting substrate and with Cu(111) on
the opposite end of the spectrum [42].
Furthermore, while most organic adsorbate systems tend to form close-packed islands in the sub-
monolayer regime and leave areas in between the islands uncovered, it has been demonstrated that
CuPc molecules form disordered mobile phases on the Ag(111) and Au(111) surfaces [36,42,43],
and a disordered non-mobile phase is claimed for the submonolayer CuPc-Cu(111) system [42-
43]. Here in this chapter however, we demonstrate that the molecules show very similar behaviors
on Ag and Cu substrates, and that their behavior can be justified by simply accounting for entropic
effects and ignoring any possible substrate effects; just as in the case of an actual 2D liquid system.
We have employed Markov Chain Monte Carlo methods to model growth of CuPc molecules
16
leading up to phase transition to a solid 2D crystal. The results of these simulations are then used
to explain the behavior of CuPc molecules as observed in STM images collected at various
coverage levels of CuPc on Copper and Silver (111) surfaces. Furthermore, we demonstrate the
existence of dual adsorption states and dependence of intermolecular interaction strength on the
adsorption state and elucidate contradictory literature reports in the case of Cu(111).
3.2 Liquid Phase of Submonolayer CuPc Films
3.2.1 Imaging of Short Range Order Signature
As mentioned previously, LEED and SPA-LEED experiments show CuPc molecules are found in
a mobile state on both Au(111) and Ag(111) surfaces []. As for Cu, there are conflicting reports,
some suggesting a disordered non-mobile phase [42] and others suggesting existence of a mobile
phase at submonolayer coverages [44]. To provide further insight into the state of the molecules,
submonolayer CuPc films were studied in detail by STM at various densities on Ag(111) and
Cu(111) surfaces. CuPc molecules were deposited at room temperature (RT) in situ at a rate of
0.5ML/min from fused quartz K-Cells. Deposition rates were monitored using an in situ quartz
crystal microbalance (ML: Monolayer, referring to a full coverage of surface by flat-lying CuPc
molecules). Deposition was done in steps up to a full monolayer, at each step yielding a surface
with a known sub-monolayer coverage of CuPc molecules. The surface was then imaged at each
stage. Figure 3.1 shows the Silver and Copper (111) surfaces at various coverage levels. As it can
be observed from the figure, a series of standing-wave-like patterns start to emerge as the
atomically clean surfaces are covered by the CuPc molecules. Highlighted in figure 3.1, even at
0.4ML coverage, ripples start to emerge around impurity sites and step-edges.
17
Figure 3.1 | STM images of Cu(111) and Ag(111) surfaces under various CuPc coverage. a-
c, Spatial images of Cu(111) on the top panels and Ag(111) on the bottom. (a) 0.4ML coverage,(b)
0.8ML coverage, and(c) 1.0ML coverage.
At the lower two coverages shown, the emerging patterns are reminiscent of fluctuations in the
Local Density of States (LDOS) due to scattering of electronic wave functions from impurity sites
and atomic step edges (see Figure 3.2a). It should however, be noted that the experiments are
carried out at RT where the conduction band is widened due to Fermi broadening. Electrons with
various energies contribute to the scattering process; this leads to a superposition of scattered
waves with different wave-vectors, which then limits our ability to observe a single wavelength in
the LDOS. Hence, we can rule out the possibility that the observed patterns are due to scattering
of the electronic surface states of the metal. To definitively illustrate independence of emerging
standing-wave-like signatures from electronic effects that may give rise to such interference-like
patterns at RT (such as complex alterations or emergence of surface states that result in very steep
low density conduction bands – possibly as a result of the metal-organic interactions) we collected
images at various biases to probe the structure of the surface states at various energies. Figure
3.2b shows images of the same Cu(111) surface with a coverage of 0.75ML collected at different
18
biases and it can clearly be seen that the ripple wavelengths are fully independent of the energy at
which the bands are being probed and in turn of any quantum effects.
Figure 3.2 | STM images of standing-wave-like patterns on submonolayer covered Cu(111)
surface. a, Spatial image of Cu(111) covered with 0.9ML of CuPc on the left and an example of
fluctuations in the local density of states on the Cu(111) surface due to electron scattering on the
right (borrowed from the Yukio Hasegawa group at University of Tokyo). b, The Cu(111) surface
covered in 0.75ML of CuPc on both left and right panels. Image in the left panel has been scanned
at a bias of 0.5V and -1.5V on the right. The spacing between the second and third peaks shown
in the insets (red line) in each panel, zooming in on the area close to the step edge on the bottom
left of each image. The spacing is 1.95nm in both scans, as well as on images collected with biases
in between -1.5V and 0.5V.
19
3.2.2 Origin of Interference-like Patterns Observed
A predicted signature of 2D liquid states is the emergence of short range order, with the correlation
length predicted to grow larger as the density increases. Though of course, it is difficult to imagine
the standing-wave-like signatures to be due to short range order in a liquid state; mainly due to a
lack of homogeneity across the imaged areas. This is however, due to existence of high diffusion
barrier obstacles on the surface of our substrate, such as step edges and impurities which act as
fixed boundaries to the CuPc liquid. To demonstrate this, we can refer to the simplest 1D liquid
model, a system of hard rods. An analytical solution exists in this particular case, allowing us to
understand the origin of the observed wave like signatures on a fundamental level. The partition
function for a system of 1D hard disks on a line of finite length with fixed boundaries is given as
follows:
𝑍 = (𝐿 − 2𝑁𝜎)𝑁 𝑖𝑓 𝐿 > 2𝑁𝜎
where L is the length of the box, N is the total number of disks, σ is the radius of the disks. Since
the analytical form of the partition function for the system is determined, we can easily turn our
attention to calculating various observable quantities with ease. One such observable quantity
which is of relevance to our experimental data, is the position observable (coordinate of the center
of a molecule). We can calculate the probability distribution of the position of molecules; that is,
knowing the number of allowed configurations in the phase space of the system, we can calculate
the likeliness of a given rod adopting a certain coordinate along the length of a given line with
length L. This probability distribution is derived in earlier work by A. Robledo et al [45] and is as
follows:
𝑝(𝑥) = ∑1
𝑍𝑁,𝐿(
𝑁 − 1
𝑘) 𝑍𝑘,𝑥−𝜎𝑍𝑁−1−𝑘,𝐿−𝑥−𝜎
𝑁−1
𝑘=0
20
with all the variables defined as before. Now that a closed form solution for the probability
distribution of the 1D hard disks on a line of finite length with fixed boundaries is in sight, it is
worthwhile to look at solutions which mimic our experimental observations. By fixing the
variables N, L, and σ to physically meaningful values representative of those in 1D line-cuts of
our experimental images of the 2D liquid state of CuPc molecules (i.e. comparable densities in
1D), we can reproduce similar sinusoidal behavior as a function of position along a given direction.
Figure 3.3 shows the probability distribution of 1D hard disks for a variety of concentrations. As
it is clear, there is a concentration dependence for the distribution of the disks, one which closely
mimics the observed experimental data.
Figure 3.3 | Distribution of 1D hard rods on a line of finite length a-d, Analytically calculated
probability distribution in position along the a line of length 50nm for rod densities corresponding
to (a) 0.1ML, (b) 0.4ML, (c) 0.7ML, and (d) 0.95ML coverage.
21
Of course, the above plots are of the position distribution function, however, given the probability
distribution of position of disks p(x), a height profile can be calculated as follows:
ℎ(𝑥0) = ∫ 𝑝(𝑥 − 𝑥0) 𝑑𝑥𝑥0+𝑑/2
𝑥0−𝑑/2
where d is the width of each 1D hard disk. STM images of the liquid state of the molecules
correspond to the 2D version of the above equation, where p(x) would instead refer to the 2D
positional probability distribution. The STM tip essentially samples various states of the liquid
over time (as the molecules are constantly moving and forming new states) and records an average
height at each point once its sampling is done. Using this formulation, 1D cross-sections of STM
data at various coverages can be fitted to the height profile as shown in figure 3.4. A caveat
however exists, STM height measurements are ultimately convoluted with fluctuations in the local
density of states which result in a non-topographic component that makes height measurements
unreliable. For the purpose of comparison, STM image line profiles are processed by removal of
linear trends followed by normalization of height values by way of dividing by the sum of all
height values, as has been done in figure 3.4.
22
Figure 3.4 | 1D model compared to STM images along symmetry directions on
both Cu and Ag samples, The surfaces of (a) Ag(111) and (b) Cu(111) at a coverage
of 0.85ML. The green and blue lines correspond to line-cuts taken along the shortest
path between two impurity points on Ag and Cu respectively. The selected impurity
pair on each surface was chosen to insure similar geometry on both surfaces. (c) The
STM height profiles in blue and green (Cu and Ag respectively) are plotted against
theoretically calculated values in red. STM height profiles have been normalized and
shifted along the y-axis for clarity.
Additionally, there are a few things to note with regards to the results of the 1D hard rods model.
Firstly, we can clearly observe the emergence of non-uniform oscillatory behavior in the model’s
positional distribution function despite abiding by the principal of equiprobability and the absence
of any external potentials (other than that which defines the line). As such, even though each
a) b)
c)
23
position on the line has an equal probability of being selected for a given rod, the overall positional
probability distribution is not uniform throughout the line. This phenomenon occurs due to
entropic interactions that exist in the system. To understand the origin of this behavior better, we
must analyze the statistics of our system by looking at the process of making various allowed states
(an allowed phase space configuration with all N rods taking on coordinates on the line without
overlapping with each other or the boundaries) and how some states may be statistically favored
over others. To assemble an allowed state, we can randomly lay down rods onto the line and accept
or reject each one based on the overlap and boundary criteria; with an additional criterion to start
building the configuration over again from the beginning every time a rod is rejected (this is to
ensure statistical integrity of our sampling of the phase space; as we would be introducing a bias
if a rejection criterion is satisfied yet we ignore it and just keep on choosing another rod until it is
accepted). Given the rods have a radius σ associated with them, we can reference each rod by the
coordinates of its center point, where there would be a set of N accepted rods in a stable
configuration denoted as follows:
{𝑋0, 𝑋1, … , 𝑋𝑖 , … , 𝑋𝑁}
where Xi is the center position of a given rod. For instance, figure 3.5 shows two different choices
of X1, one where rod one has landed at the boundary and one where it has landed somewhere in
the between the boundaries. The acceptance probability of laying down a rod is directly
proportional to the available values left for Xi to take, thus the probability of choosing a X2 value
that will be accepted in the case shown at the top of figure 3.5a) is proportional to L-4σ as opposed
to L-6σ for the case appearing at the bottom of the same figure. The two compared cases were
chosen on purpose, as they demonstrate the entropic effect which leads to large peaks in the
positional probability distribution at the boundaries. This however does not explain the oscillatory
behavior observed as the distance from the boundary grows. To explain the oscillatory behavior,
figure 3.5b) displays a pair of choices for {X1, X2} that show the dependence of acceptance
24
probability of X3 on the choice of {X1, X2}. It can readily be seen that there is a dependence. In
fact, each rod acts as a pole to other rods and results in what is observed as oscillatory behavior.
Hence, we see that there is a dependence of acceptance probability of laying down a rod Xj+1 on
the choice of the already accepted values of {X1, X2,…,Xj}; which in turn results in certain
positions to have a higher chance of appearing in various states in the phase space.
Figure 3.5 | Illustration of a few cases in the hard rods model demonstrating root cause of
non-uniform distribution functions, (a) shows two cases where the first rod X1 has landed at the
boundary and another where it has landed in the middle of the line. The areas in green highlight
available space for a second rod to land. The available space for a third rod to land is demonstrated
for two different cases in (b). As it can be seen both diagrams at the top in (a) and (b) have higher
probabilities of surviving addition of another rod, hence demonstrating the reason for high
probability aggregation of rods at the boundaries and the oscillatory behavior respectively.
3.3 Entropic Order & the 2D Liquid-Solid Phase Transition
3.3.1 2D Monte-Carlo Simulations
Thus far we have shown that oscillatory signatures can arise even in the simplest of liquid systems
as seen in the 1D hard rods liquid model above. However, CuPc molecules are found in a two
dimensional liquid state and thus a 2D model should be used to study the nature of the molecular
25
liquid observed in STM images earlier. Unfortunately, even the simplest 2D Liquid models do not
have analytical solutions. In fact the existence and nature of the liquid-solid phase transition in 2D
liquid systems has been the subject of debate among physicists for the past few decades. Only
quite recently has it been demonstrated through Monte Carlo simulations that there exists a
continuous phase transition for the simplest 2D liquid system imaginable; a system of two
dimensional hard disks []. There have also been few observations of quasi-2D liquids in
experiments, however the existence of coupling to the third dimension due to interactions with the
substrate has always obstructed experimentalists from drawing firm conclusions about actual 2D
liquid systems.
Returning to the observed short range order signatures; given the lack of an analytical closed form
solution to the 2D-liquid problem, even in the hard disks case (molecules approximated by circular
disks), we have used Monte Carlo simulations of hard disks where the interaction amongst any
two disks i and j is defined as follows:
𝑢(𝑟𝑖𝑗) = {∞ 𝑖𝑓 𝑟𝑖𝑗 < 2𝑅
0 𝑖𝑓 𝑟𝑖𝑗 > 2𝑅}
where R is the radius of each disk and rij is the distance between the centers of the two disks i and
j. Of course, our system of interest is composed of molecules which have 4-fold symmetry and are
not circular, thus a reasonable approximation for the radius R has to be made. Since we are utilizing
fully stochastic dynamics in our simulations, it is fair to assume there is an equal probability of a
molecule colliding with another (or with the boundaries) at all possible rotation angles with respect
to the rotational axis of symmetry of the molecule. Consequently we have taken our ansatz for the
value of the radius of the hard disks to be the length of the vector running to the side of a square
which has the dimensions of a CuPc molecule, measured from the center of the square and
averaged over all angles. Given previously measured size of the molecules, 1.2nm, we have
calculated this average radius to be 0.67nm, comparable to half the lattice spacing value in the 2D
lattice phase of the molecules [44,52].
26
Figure 3.6 | Monte Carlo simulation results of 2D liquid of hard disks. a-c, calculated
positional distribution function: normalized configuration-averaged disk positions, obtained from
a two-dimensional histogram of positions of disks. Simulation box size of 30nm was used and
results were calculated for (a) fully periodic boundary conditions, (b) periodic boundaries with an
impurity point of radius 0.8nm in the center of the box, and (c) closed boundary conditions with
an impurity of the same radius at the center of the box.
Figure 3.6 shows the results of the simulations under closed and periodic boundary conditions at
various densities. The simulated positional probability distributions of the molecules show that the
emergent short range order in earlier STM results (Figure 3.1) can be reproduced by simply
treating the molecules as colloidal objects, without the influence of any external potentials, as was
27
illustrated in both one dimensional systems and 2D systems. This resulting order and non-uniform
density distribution in our simulations is rooted in similar entropic interactions that were present
amongst the 1D hard rods as well as the boundaries when applicable. Such entropic interactions
originate from existence of the no-overlap condition (and boundary conditions when applicable)
for reaching a legal configuration in the phase space of the system of N molecules, and as predicted
by Asakura-Oosawa in 1954, lead to depletion forces which are repulsive in nature. Figure 3.7
superimposes predicted order along a particular direction - i.e. a linear profile in the 2D map - onto
its experimentally observed counterpart. Simulations were done for a simulation box size of 30nm,
with according number of particles to produce the wanted densities. It is interesting to note that
the assumed value of the effective molecular radius resulted in a close match to the data on the
Ag(111) surface. However the same was not true on the surface of Cu(111). Instead, a radius of
0.98nm showed quite a strong agreement with experimental findings (see figure 3.7b). This
suggests existence of different effective Van der Waals radii on each substrate, possibility due to
slightly longer range interactions between neighboring molecules that could be arising due to
stronger substrate effects on copper. A likely mechanism responsible for such repulsive
interactions could be repulsion between like dipole on molecules, induced by a high density of free
electron like surface states on the substrate’s surface.
Thus, contrary to the claims of earlier work of Stadler et al., entropic effects are indeed large
enough to insure the system behaves as it does. In fact preliminary results to be published, show
this effect takes place for a variety of Phthalocyanine variants on the (111) Copper and Silver
surfaces, hence suggesting the possibility of existence of such depletion forces in various
unexplored organic systems.
28
Figure 3.7 | Experimental and simulation result comparison. a-b, Comparison of STM image
of CuPc-covered substrate with corresponding Monte Carlo Simulations. STM images in the top
left panels, Monte Carlo simulated positional probability distributions in the top right, and
comparison of line-cuts taken along both in the bottom panels. (a) Ag(111) surface at a coverage
of 0.85ML. Periodic boundary conditions used in the simulations. (b) 0.85ML coverage on
Cu(111), with closed boundary conditions used to mimic the effects of a step-edge.
3.3.2 A Brief Look at the Liquid-Solid Phase Transition
A closer look at the short range order signatures in the submonolayer regime in our thin-films
reveal that the liquid-solid phase transition takes place at a coverage of 0.90ML+-0.03, as can be
observed in figure 3.8. This critical value of coverage can in fact be converted into a packing
density value that allows us to compare it to the phase transition density value in the case of 2D
hard disks. Given that CuPc molecules arrange themselves into a distorted square lattice at a full
monolayer, we can approximately scale our ML coverage measurements by a factor of 0.78 - the
packing density associated with hard disks in a square lattice configuration. Incidentally, 0.9ML
corresponds to a packing density of 0.7 within the bounds of error, which corresponds as expected,
29
to the packing density at which the 2D hard disk liquid-solid phase transition takes place. This
liquid-solid phase transition, though not referred to as one by the studies referred to earlier, is in
fact present in many experimental studies for various Phthalocyanine molecules on different
substrates and is found to happen at similar coverage levels ranging from 0.89ML to 0.93ML, all
in agreement with our results within the expected error [36,37,41,42,43]. Such observations as
well as the present work make us confident that at the very least, quite a few Phthalocyanine
variants as well as possibly other organic molecules may display repulsive forces where entropic
interactions play a role.
Figure 3.8 | Liquid-Solid phase transition in the CuPc sub-monolayer films. a-d, Spatial
images of Cu(111) at various coverage close to critical phase transition density. (a) 0.85ML
coverage, (b) 0.92ML coverage; molecules can almost be made, as in the liquid phase has
transitioned to its solid counterpart, (c) 0.95ML coverage; Rhombic order starting to emerge, and
(d) 0.98ML coverage, long range order emerging.
It is rather important to make note of the importance of the definition of a monolayer and the
impact of its accuracy of measurement in pin pointing the phase transition as well as relating to
the Monte Carlo simulation results. A monolayer is defined as the point where the full surface is
covered with one single layer of molecules, yielding the maximum average two-dimensional
density [g/cm2] allowed by the system. As such, a monolayer of CuPc molecules on Cu(111) and
on Ag(111) lead to different densities and in turn of course different packing fractions. When
dealing with molecules in the mobile state, the Sauerbrey equation which is used for correlating
30
the oscillation frequency of the piezoelectric crystals in the QCM system [46] becomes inaccurate
as it is formed on the assumption of rigid attached masses. A correction term which shows a
decrease in the resonant frequency with viscosity is to be accounted for in liquids [47]:
∆𝑓 = 𝑓°3/2
(𝜂𝑙𝜌𝑙/𝜋𝜌𝑞𝜇𝑞)1/2
where is and are the density and viscosity of the liquid respectively, with and being the quartz
density and shear modulus respectively. Given the difficulty in knowing the density of the liquid
state of the CuPc molecules, it is then very difficult to achieve a high precision measure of the
percent monolayer coverage using the QCM system. Thus, given such difficulty in measurement,
it is best to set the 1ML deposited surface as a reference, as done here in this work. Furthermore,
the full monolayer surface provides insight on the molecular density and allows for calculation of
a sensible effective molecular radius based off of the observation of packing density at full
coverage. As observed earlier from the discussions around simulation results, the effective radii
on the two studied surfaces were quite different, in line with the observed differences in the
packing density at a full monolayer coverage on each surface.
3.4 Dual Adsorption States & Immobilization of Molecules
Up to this section so far we have presented for the first time, direct spatial imaging of short range
order and have demonstrated existence of a liquid state in sub-monolayer Cu-Phthalocyanine
(CuPc) molecular films on two close-packed metallic surfaces using STM. The short range order
signatures in the liquid state were studied as a function of molecular density and direct images of
the system undergoing the liquid-solid phase transition at higher densities were obtained; with the
solid phase eventually transitioning to an ordered lattice at a full monolayer. This existence of the
liquid state up to about 0.9ML coverage as well as the liquid-solid phase transition is apparent on
both Cu(111) and Ag(111) substrates (at RT), contrary to previous LEED and SPA-LEED
31
experimental findings of Stadler et al., Kroger et al., and Stadtmuller et al. which suggest existence
of a disordered non-mobile phase on Cu and a disordered gaseous phase on Ag at coverages below
0.76ML and 0.9ML respectively [42-43]. Our experiments clearly show that CuPc molecules are
in a liquid state on both substrates at RT. Nevertheless, differences in preparation of the films can
play a large role in Phthalocyanine films, as will be demonstrated in this section. The films
examined by Stadtmuller were annealed at 433K for 20 minutes following RT deposition, whereas
the samples in our studies were not annealed. This difference in preparation is key to producing
different structures in this particular metal-organic system.
Figure 3.9 | STM images of sub-monolayer CuPc films annealed. a-c, Spatial images of
Ag(111) at 0.4ML coverage annealed for 30 minutes up to a temperature of (a) 500K, (b) 630K,
and (c) 770K.
Given the apparent inconsistency between our direct observation of existence of a liquid state of
CuPc molecules on Cu(111) and earlier findings which claim a non-mobile disordered phase; we
conducted a study on the effects of annealing on the CuPc-Ag(111) system at submonolayer
coverages. Silver substrates covered by 0.5ML CuPc were prepared (RT deposition) and each was
annealed at a set temperature, ranging from 500K to 770K. The substrates were annealed for 30
minutes each. Figure 3.9 shows STM scans of three samples, each annealed at a different
32
temperature. When annealed to 770K, CuPc molecules are no longer found in a mobile state and
form a new structure; the molecules have formed disordered chain structures, and fraction of the
surface covered by the disordered chains imply that the density of CuPc in the disordered areas is
close to 1 ML. This tendency of CuPc molecules to form immobilized disordered chains on the
(111) surface of Silver when annealed could be the cause of the discrepancy between our
observations and the aforementioned literature. This will be further confirmed when we have
annealing results for CuPc on Cu(111).
When not annealed, we have demonstrated that the molecules show identical behavior on both
substrates at room temperature and that their behavior can be justified by simply accounting for
entropic effects and ignoring any possible substrate effects. In effect, the picture claiming
interaction due to substrate mediated charge transfer and induced dipole formation [43] no longer
works when both substrates start with similar un-annealed conditions. Similar repulsive forces are
present in both Cu(111)-CuPc and Ag(111)-CuPc systems despite claimed attractive interactions
due to transfer of charges between the substrate and the molecules in the case of Cu(111). Thus, a
small oversight in assuming that annealing will simply allow for effective diffusion of molecules
across step edges in the previous experiments as well as low temperature effects, could have led
to formation of chains in the molecular films without the intention of doing so, and hence leading
to an altered morphology. What is then made clear when results of previous photoemission
spectroscopy studies are combined with our annealing experiment observations, is that the switch
from repulsive to attractive intermolecular interactions is not driven by choice of the substrate.
33
Figure 3.10 | STM images of patterning of CuPc molecules on Cu(111) and bias threshold
plot for pinning. a-b, Spatial image of tunneling electron induced chemisorbed CuPc. (a) “CUPC”
written with a single pass of the STM tip at V=+4.5V, I=1.5nA, and scan speed of 16nm/s. Inset
is a zoom-in on the “C”, scanned at V—1.5V, I = 300pA.(b) Indicated square of size 25nm on a
0.5ML covered Cu(111) surface has been scanned at V=2.8V, I=1.2nA for 60min. Then imaged
with parameters: V=1.8V, I=300pA. (c), Bias dependence of induced CuPc chemisorption. Turn-
on happens at V>2.0V. This figure has been adapted from earlier work done in the group by T.
Stock et al. [48].
Aside from annealing, we have observed another mechanism in the Cu(111)-CuPc and Ag(111)-
CuPc systems that can trigger localization of the molecules. As also outlined in an earlier paper on
tip-induced chemisorption of CuPc molecules on Cu(111) by Taylor J. Stock et al., the pinning of
the molecules could also be done in a controlled fashion through application of tip-induced bias
exceeding a threshold value of +2.15+-0.15 V on Cu(111) as shown in Figure 3.10 (borrowed from
[48]), thus providing a mechanism for controllable patterning of the molecules on the substrate's
surface through immobilization of the free roaming molecules at chosen locations. The same
behavior is indeed present on the Ag(111) surface as presented in figure 3.11. The threshold bias
at which the field-induced pinning occurs is 3.6+=0.15 V on Ag(111), considerable larger than the
bias required to accomplish pinning of molecules on the copper substrate. Similar behavior has
also been observed by Y. C. Jeong et al. [49] in the Au(111)-NiPc system. The pinning of the
molecules has been attributed to breaking of hydrogen bonds on the molecules (due to the tip-
34
induced electric fields) which allow for bond vacancies which then bond with the substrate. If such
is true however, the same threshold bias value of 3.1 V [49] should have been observed on both
Ag(111) and Cu(111) for CuPc molecules as well. This observation along with annealing based
molecular localization suggest dual adsorption states on the (111) surfaces of silver and copper for
CuPc molecules, and perhaps other members of the Phthalocyanine family.
Figure 3.11 | STM images of pinning of CuPc molecules on Ag(111) and bias
threshold plot for pinning. a-b, Spatial STM images collected at a bias of
V=+1.7V, current setpoint of 600pA. (a) Image of the area and surroundings of
where the pinning was done before pinning. Red square highlights the area exposed
to high bias. (b) Image of the same area as in a) after high speed high bias scans at
V=+4.0V, I=1.5nA, and scan speed of 20nm/s.
35
The ability to immobilize molecules through application of an electric field on both substrates
(provided enough energy) is of interest in two ways. Firstly, we can see right away that CuPc
molecules can controllably be patterned onto the surface by taking advantage of existence of the
two accessible adsorption states available to them on each of the substrates, one where they are
found in a liquid state and interacting weakly with the substrate (studied earlier in this chapter),
and another where they are localized and interacting more strongly with the surface of the
substrates. Secondly, the mechanism for molecular pinning seems to be the same as that of
annealing based localization of the molecules. As well, the change from repulsive to attractive
intermolecular interactions is also marshaled by the change from the liquid adsorption state to the
immobilized one. When the molecules are pinned they tend to form aggregates and pin other
molecules in the vicinity of where the bias was applied (see figure 3.10 a) and b) ); and as well,
the disordered chain structure of the annealed films suggest localization of each molecule during
annealing is accompanied by growth of a chain of molecules around it as other mobile molecules
collide with the localized ones, at the end forming the observed large molecular chains.
Furthermore, the pinning threshold bias values for the substrates correlate nicely with the ranking
of molecules-substrate interaction strengths in studies done by Stadtmuller et al. at low
temperatures where the molecules are found in an immobilized state. As the interaction strength
on copper is stronger [42], a lower threshold bias needs to be applied to pin the molecules, and on
Silver a higher threshold, as the opposite is true with regards to molecule-substrate interaction
strength. In tune with such correlations, are the annealing temperatures needed to localize the
molecules. A higher amount of energy and hence a higher annealing temperature is needed to
localize the molecules on Ag(111) as opposed to Cu(111).
36
3.5 Summary
In summary, in this chapter we have explored the fundamentals of the nature of interactions at the
CuPc-Ag(111) and CuPc-Cu(111) interfaces. It’s been made clear that there are two possible
adsorption states (in the submonolayer regime) available to the molecules, previously unnoticed
in literature; one where the molecules are in a 2D liquid state and another where they are
immobilized and pinned to the surface in a disordered fashion. Furthermore, it was shown that the
molecule-substrate interactions in each adsorption state is completely different, ranging from very
weakly interacting substrate potentials in the liquid state, to strongly interactive in the immobilized
state. Interestingly enough, the immobilization of the molecules can be triggered by application of
a bias larger than threshold values presented earlier; making the studied systems potentially
interesting for patterning and molecular electronics applications. It was also deduced from the
collection of results in this work and pre-existing ones in the literature that the intermolecular
interactions change from repulsive to attractive when the state of adsorption is changed from the
liquid state to the disordered immobile state. In the liquid state specifically, Monte Carlo
simulations showed entropic interactions to be quite important in such systems; with
intermolecular interactions being weak enough to be represented by hard-core interactions (to first
order at least). This leads the way into the next chapter where full monolayers of CuPc molecules
and their geometries are presented with detail, in the process hinting at weak intermolecular
interactions and substrate effects.
37
Chapter 4
Molecular Orientation Control
4.1 Introduction
Control over orientation and assembly of molecules on various surfaces is of particular interest for
the purpose of building molecular and organic thin-film optoelectronic devices. In the context of
thin-film devices, the geometrical stacking structure of molecules have a great impact on the
electronic properties of the interface, such as the energetic barrier height for charge carriers. Aside
from the interface itself, the emergence of various types of geometrical order – i.e. crystallization
of the molecules – or disorder can impact the mobility of charge carriers within the molecular film.
Thus, disorder or emergence of various kinds of order in molecular films could be critical to
determining device performance.
Given the link between electronic properties of the interface and the degree and type of order in
spatial distribution of organic molecules, it is vital to recognize the parameters which allow for
tuning of such properties. Though it may seem quite trivial that there exist two main physical
interactions which are major parameters for determining the molecular orientation adopted by the
molecules in a given system: intermolecular interactions and molecule-substrate interactions, it is
quite difficult to control each individual set of interactions separately as they are often times
convoluted and can have effects on each other, hence we need to look further to find parameters
which we can control and understand more easily.
Molecule-substrate interactions sometimes lead to induced dipole moments on the molecules
which can in turn alter the nature of intermolecular interactions. On a relatively larger scale, the
difference in the work functions of the substrate and the molecular crystal can also lead to
interfacial dipole moment formation which can alter the charge injection properties at the interface.
38
Thus it is reasonable to assume that the choice of substrate can in fact be used as a parameter for
determining electronic and geometric properties of a given organic overlayer.
In this chapter, the CuPc molecules discussed in the previous chapter are studied at full monolayer
coverage on metallic substrates and mechanisms responsible for control of molecular orientation
are examined. The Phthalocyanine family of molecules have simplistic geometric shapes – more
or less planar and square shaped – and come in many chemical varieties that allow for tuning of
the bandgap, magnetic properties, and molecular size and shape to certain degree. CuPc has been
thoroughly studied in the literature and is a great candidate for study of orientation as it is a planar
molecule. The orientation of CuPc on Cu(111) and Ag(111) surfaces is confirmed and lattice
parameters are extracted. The molecular orientation is altered through introduction of a single
monolayer buffer layer.
4.2 Pc Monolayer Films on (111) Metal Surfaces
4.2.1 Lattice Measurement & Adsorption Geometry Using STM
While submonolayer CuPc films are mobile on the surface of both Cu(111) and Ag(111) at room
temperature, at CuPc coverage of 1ML, the molecules are no longer mobile on the surface, but
rather coalesce into a 2D crystal lattice where the molecules opt for the flat-laying orientation. The
use of STM for measurement of the orientation of the CuPc 2D lattice with respect to the
underlying Cu(111) and Ag(111) crystal lattices poses a significant challenge, as the CuPc crystal
phase only emerges at full coverage of the surface. Since the substrate's lattice and the CuPc lattice
cannot be imaged within the same STM scan, the angular and atomic registration of the CuPc
lattice and molecules with respect to the underlying substrate cannot accurately be determined by
STM.
39
To that end, we have overcome this difficulty by simultaneously measuring the Ag(111)-CuPc and
the Ag(111)-C60 systems and taking advantage of the already known structure of Fullerene C60
molecules on Ag(111) surfaces to act as a reference, as has already been done in work by Taylor
J. Stock for the case of Cu(111) [50]. In the Cu(111)-C60 system, the structure is well-known and
studied to a great degree; at coverages of 1ML and less the annealed (at 573K) C60 films form
ordered hexagonal p(4x4) commensurate overlayers owing to the relatively small lattice mismatch
between the C60 nearest neighbor distance (bulk C60 has a nearest neighbor distance of 10.0Å)
and four times the Cu-Cu nearest neighbor distance on the Cu(111) surface of 10.2Å. This
translates to a quite small lattice mismatch of about 2%, which can explain the dominant and
simple p(4x4) structure on Cu(111).
Of course this technique of measurement using Scanning Tunneling Microscopy is made possible
due to the site selective adsorption of CuPc molecules as well as crystallization of C60 molecules
in the submonolayer regime on Cu(111) and as it will be demonstrated soon in what’s to follow,
on the Ag(111) surface. STM images of the Cu(111) surface covered in 0.5ML of C60 p(4x4) and
0.5ML of CuPc which has subsequently been deposited at room temperature show the CuPc
molecules have diffused over and away from the C60 covered regions and have segregated to the
bare Cu(111) regions. In this process the CuPc molecules have formed 2D crystal structures of
varying phases on the Cu(111) surface. In accordance with the work of Taylor J. Stock et al., the
CuPc lattice is measured to be a=1.36+-0.05nm, b=1.4+-0.05nm, and theta=88+-2deg. Using the
C60 lattice as a reference, it is observed that three rotationally equivalent domains form whose
rotational orientation with respect to the <-110> symmetry axes of the Cu(111) surface are all the
same; all forming an angle of -9+-2deg with lattice vector b. Another set of domains emerge from
reflection of the above domains in the <-110> axes.
These two assumptions of immobile submonolayer C60 and site-selective CuPc adsorption prove
to be true for the Ag(111)-C60 and Ag(111)-CuPc systems respectively as well. Akin to its
Cu(111) counterpart, not only is the Ag(111)-C60 system well-studied, it is also easily and
40
reproducibly measurable using STM. In fact the structure is known with high precision and
accuracy, at C60 coverages of 1ML or less on Ag(111), the annealed films - at 685K - are known
to form nearly perfectly ordered hexagonal (2√3×2√3)𝑅30° commensurate structures [51].
Despite a lattice mismatch of about 14.5% between the C60 layer and the substrate, the C60 adlayer
forms an ordered structure. The nearest neighbor distance on the Ag(111) surface is about 2.85Å
which leads to a relatively small lattice mismatch of about 1.4% when adopting the scaled and 30°
rotated superstructure. Thus, given the C60-C60 nearest neighbor distance of 10.0Å in bulk C60
crystal structures, it is sensible that the (2√3×2√3)𝑅30° would be a dominant phase on the
Ag(111) surface; with a nearly commensurate layout.
Figure 4.1 | STM images showing sub-monolayer C60 coverage of the Ag(111) surface
Image was captured with the following set parameters: 0.5ML C60 on Ag(111), V=0.1 V, I=200 pA. The C60 ordered domain appearing in the bottom left corner of the image has
adopted the (2√3×2√3)𝑅30° structure referenced to the Ag(111) lattice, as can be seen from
the inset image at the top right.
41
Figure 4.1 displays both the ordered C60 structure on Ag(111) as well as the underlying Ag(111)
lattice’s atomic corrugations. In Figure 4.1 the original image has been linearly skewed to bring
the Ag(111) lattice into confirmation with the already well-known structure (a=2.85Å,
theta=60deg). In this one step we have corrected for xy-piezo measurement miscalibration as well
as linear thermal drift. It can be seen in the corrected image of Figure 4.1, that there exist two
different phases of the adsorbed C60 layer, one of which is indeed the (2√3×2√3)𝑅30°
commensurate structure that has been observed in prior LEED experiments. Given that the C60
film was not annealed, it is expected that other phases of C60 would co-exist alongside the
aforementioned commensurate structure [51]. Having established the structure of the C60 layer as
reference with respect to the Ag(111) substrate, it is then possible to measure the lattice parameters
of the CuPc lattice and the rotational registration of the CuPc molecules with respect to the
underlying symmetries of the Ag(111) lattice.
4.2.2 CuPc Monolayer on Ag(111)
Deploying similar linear skewing techniques as mentioned before, this time using the C60 ordered
structure as reference, images of the Ag(111) surface covered by 0.5ML of C60 and 0.5ML of
CuPc were collected and corrected for thermal drift and miscalibration. As it can be seen in figure
4.2, the CuPc molecules have indeed diffused to bare Ag(111) areas when deposited on the
Ag(111) surface covered in 0.5ML of ordered immobile C60. Figure 4.3 provides a STM image
of this surface showing 2 of three common phases of the CuPc ordered structures on Ag(111) in
a). Other phases were also detected, however, the lack of large enough C60 ordered lattices in the
images did not allow for accurate correction of images and in turn extraction of the CuPc lattice
parameters.
42
Figure 4.2 | STM image of the Ag(111) surface covered in 0.5ML C60 and 0.5ML CuPc
Image was captured with the following set parameters: V=-0.5 V, I=300 pA. The image shows selective adsorption of CuPc molecules onto the bare Ag(111) surface, once deposited onto the 0.5ML C60 covered Ag(111) surface.
Using a large set of such images, all corrected in a similar fashion, the lattice parameters of the
CuPc ordered domains were extracted, as well as the rotational orientation of each domain with
respect to the symmetry axes of the C60 domains and in turn the underlying Ag(111). The CuPc
2D crystal is measured to be a rectangular lattice with dimensions a=1.42+-0.05nm, b = 1.27+-
0.05nm, and theta=85+-4deg. The measured values of the lattice parameters are in agreement
within the bounds of error with previously published results [52], however the measured theta
43
seems to be smaller than expected which could possibly be due to non-linear drift making the C60
lattice parts of the image scale differently than the CuPc areas. Using the C60 ordered domains as
a reference, it was found that the CuPc lattice occurs in three rotationally invariant forms, in each,
the lattice vector a aligning with the <-2-21> family of Ag(111) lattice directions and b aligning
with directions parallel to the <-110> symmetry axes.
Additionally, using the C60 referencing technique the rotational orientation of the CuPc molecules
have been determined within the unit cells. For the three rotationally equivalent domains aligned
with the <-2-21> and <-110> symmetry directions for the a and b lattice vectors respectively, the
molecules are observed to form an angle of 60+-5deg between the axis passing through the
diagonally opposed molecular lobes and the <-2-21> symmetry axes of the underlying Ag lattice.
This implies a rotation of about 15 degrees within their unit cell from a non-rotated molecular
orientation which would make angle of 45 degrees between the two axes described above. The 60
degree rotation of the molecular lobes with respect to the <-2-21> directions means that one of the
diagonal lobes potentially aligns with the <-110> direction while the other along the <-2-21>
symmetry directions.
44
Figure 4.3 | 2D crystal phases of CuPc molecules selectively adsorbed onto the Ag(111)+0.5ML-C60 surface
Both images in a), b), and c) were captured with the following set parameters: V=-0.5 V, I=300 pA. a) Given the
C60 ordered domain has adopted the (2√3×2√3)𝑅30° structure (referenced to the Ag(111) lattice), it can then be
deduced that the CuPc rows which make an angle of 120 degrees with the (2√3×2√3)𝑅30° structure’s high
symmetry direction (equivalent to Ag(111)’s [-110] direction) are in fact lying along the [-2-21] direction of the underlying lattice. b) This image displays a rotationally symmetric phase of the CuPc molecules, rotated by 60 degrees. The inset shows the lattice vectors of the CuPc crystal.
An interesting observation can also be made when comparing various Metal-Phthalocyanine
family of interfaces. The previously studies systems of Ag(111)-CuPc and Cu(111)-CuPc display
45
an interesting difference in behavior which seems to be prevalent in all of the images collected
from both systems. On the Ag(111) surface there are almost no appearances of different rotational
orientations of the CuPc molecules within their lattice, leading to almost no observations of
alternating rotated rows, as opposed to the Cu(111)-CuPc system where a variety of molecular
rotational orientations are observed in the lattice. This pronounced difference in the way the CuPc
molecules form ordered crystal structures on the two substrates, stresses the importance of
substrate effects in the process of self-assembly of the molecules. In this particular system, as
demonstrated in the previous chapter the molecules are driven to the ordered state through
interactions that are entropic in nature which emerge out of the hard-core nature of the interactions
of the molecules. Granted this, the difference in the emerged order in the full monolayer regime
on two different substrates shows, as postulated earlier, that the substrate’s geometry and potential
landscape (lattice size for instance) can perturb the entropic interactions and introduce non-2D
effects (whether entropic in nature or not), effects which can nonetheless be incorporated into
Monte Carlo simulations to account for such perturbations.
4.2.3 F16CuPc Monolayer on Ag(111)
To further explore this phenomenon, F16CuPc molecules were deposited on the Ag(111) surface
to study effects of molecular size on the molecular crystal and to monitor whether formation of
rotated rows will be triggered through such alteration in the lattice mismatch between the
molecular lattice size and that of the substrate. Since rotated rows were not observed in the
Ag(111)-CuPc system, this comparison would make for a reasonable test of whether geometric
factors play a significant role in lattice formation or not, as the Ag(111)-F16CuPc system displays
similar entropic nature of interactions as those earlier found in the CuPc systems. Figure 4.4
displays the F16CuPc lattice on the Ag(111) surface, and as it is immediately visible, the molecules
have formed a pattern of alternating rotated rows. Various images of this surface reveal similar
structures to be dominant in three different phases; all rotationally equivalent, one is shown in
46
figure 4.4b, where the rows are forming along the [-2-21] direction of Ag(111), in accordance with
findings in the literature [53]. Although the alternately arranged double-molecular rows are the
most dominant, larger alternating patterns are observed at times as well. Not all rotated rows have
the same unit cells, indicating formation of an overall more complex structure in order to
compensate for the lattice mismatch. The lattice unit cells also seem to be larger than that of CuPc
molecules on Ag(111), as expected due to the relatively larger size of the F16CuPc molecules.
Figure 4.4 | 2D crystal lattice of F16CuPc molecules selectively adsorbed onto the Ag(111)+0.5ML-C60 surface
Both images in a) and b) were captured with the following set parameters: V=-0.8 V, I=800 pA. a) Given the C60
ordered domain has adopted the (2√3×2√3)𝑅30° structure (referenced to the Ag(111) lattice), it can then be deduced
that the rows are aligned with the [-1-10] direction of the Ag(111) lattice. b) The unit cell primitive lattice vectors were
measure to be a=1.55+-0.05nm, b=1.52+-0.05nm with the angle between them being 72+-3 degrees. Each set of
rotated rows indicated existence of a variety of unit cells.
47
Overall, looking at both CuPc and F16CuPc molecules on the Ag(111) surface, it seems the
difference in geometrical structures of the underlying lattices and that of the molecules seem to be
the root cause for the preferential alignment of the molecules along the symmetry axes such as the
<-110> and <-2-21> axes on Ag(111). Though of course, geometrical structure change translates
to changes in distribution of charges, meaning the aforementioned trends can neither prove or be
used to claim a lack of existence of strong substrate-molecule interactions but rather can
demonstrate the de-convoluted nature of the forces where the intermolecular interactions are
seemingly short-range enough and un-affected by the substrate interactions, that they can allow
for the molecules to behave as though they are freely moving billiard balls that can find their stable
equilibrium in areas of minimum potential energy in a potential energy landscape set up by the
underlying lattice as the density of the molecules on the surface approaches a regime where kinetic
energy of the molecules has decreased and a solid phase has emerged. In this manner, the size of
the molecules and the underlying lattice’s nearest neighbor distances start to matter and dictate the
crystal structure of the molecules once the liquid-solid phase transition (as discussed in the
previous chapter) has taken place.
Beyond such suggestions and detailed accounts of the emergence of a variety of ordered structures
on the Ag(111) and Cu(111) surfaces, what is clear is that the molecules tend to form rather
complicated overlayers which are not simply uniform commensurate structures. Having stated that,
all of the systems studied tend to have a single commonality, in that in all of them the molecules
adopt a flat-lying orientation with respect to the substrates.
4.3 Reorienting CuPc Molecules
4.3.1 Introduction of a Buffer Layer
Thus far the nature of interactions at the Ag(111)-CuPc and Cu(111)-CuPc interfaces have been
revealed and it’s been shown that the molecules adopt a flat-lying orientation at both interfaces. In
48
conjunction, as it was established earlier in the introduction and background sections, the
orientation of molecules in the context of thin film devices can be of significant importance. In
fact the mobility of charge carriers in a given film can significantly be impacted by the way the
molecules have assembled and orientated themselves in the thin film. Aside from effects on
mobility of electrons and holes, the orientation of the molecules in such molecular films as CuPc
thin films which are the concern of this study, can also largely impact the size of electron and hole
energy barriers at interfaces and ultimately play a large role in determining device performance.
In this section, a methodology is proposed in quest of controllably altering the orientation of the
molecules and their stacking on the studied metallic (111) surfaces. As it was discussed earlier,
the CuPc molecules, when deposited at room temperature adopt a weakly interacting (with the
substrate) state where they are bound to the surface yet mobile in a 2D liquid state and as the
density (i.e. surface coverage) increases they transition to a solid ordered phase. Hence, in order
to dramatically change the state of the system and enable control of orientation of the molecules,
introduction of a single layered molecular buffer is made. A proposed molecular materials for the
buffer layer is the Fullerene C60 molecule. C60 molecules have a high degree of symmetry due to
their geometrical shape, and as well offer high conductivity and mobility of charge careers which
make them a suitable candidate for device applications. Furthermore, C60 molecules are well-
studied and are known to form a close-packed ordered structure in the bulk [51] and to similarly
form commensurate hexagonally close-packed crystals on the (111) surfaces of Silver and Copper
[51,54-56].
These properties of the C60 molecular films help preserve similar symmetries to those of the
underlying lattice and to introduce minimal contribution to the overall properties of the archetypal
organic optoelectronic device which typically has layers with thicknesses of the order of 10s to
100s of nanometers. The real decider for the choice of C60 for the purpose of a buffer layer
however emerged from results of XPS/UPS studies carried out on C60-CuPc interface.
49
Figure 4.5 shows the summary of the experimental results, displayed as an energy level diagram.
It can easily be observed that the relative difference in the bulk work functions of the two crystals
(C60 and CuPc) contributes to a difference between the local vacuum levels of each side of the
interface and in turn the formation of an interfacial dipole moment. Of course, looking at the local
vacuum level offset at the interface, it can also be seen that the value does not directly correspond
to the difference between the bulk work function values of each crystal, a value of -0.08eV. In fact
the offset is measured to be -0.17eV. This is to be expected since the second UPS work function
measurement (with the CuPc deposited on top of the C60 layer) is taking into account surface
dipoles which may form at the CuPc-Vacuum interface as well. In fact, earlier UPS studies done
on CuPc and F16CuPc vacuum-deposited thin-films on C8-SAM/Au(111) substrates demonstrate
formation of surface dipoles for both molecules [58]. Opposite surface dipoles are shown to form
in each case, originating from different intramolecular bonds exposed at the surfaces, C-H bonds
in the case of CuPc and C-F in the case of F16CuPc, thus exposing dipolar bonds (due to
differences in electronegativity of H and F) of opposite polarity. Of course this holds true in the
mentioned systems due to adaptation of the standing orientation of both molecules [58,59]. The
same study carried out a comparison between the mentioned standing orientations and flat-lying
orientations by using substrates known to force CuPc and F16CuPc molecules to orient in the flat-
lying orientation. The results showed a shift of -0.4eV in the ionization potential for CuPc
molecules in the standing orientation and a shift of 0.85eV for standing F16CuPc; with both shifts
measured relative to the ionization potential of their flat-lying counterparts [58].
50
Figure 4.5 | Results of UPS experiments on the C60-CuPc interface summarized in an energy level diagram
The shift in the local vacuum level at the interface indicates formation of an interfacial dipole as well as possibly a surface dipole moment at the CuPc-vacuum interface. The shift in the position of the HOMO of CuPc to 0.68eV from 0.93eV when at bulk also signals band bending and transfer of charge across the interface.
Given results of our UPS measurements on the C60-CuPc interface (existence of a surface dipole,
aside from the interfacial dipole moment) along with the work discussed above (ionization
potential dependence on molecular orientation), it can then be suggested that CuPc molecules
could possibly be adopting a standing orientation when deposited on the C60 lattice, since the
ionization potential of flat-lying CuPc on HOPG was measured to be 5.45eV and CuPc on C60
was measured to be 5.11eV, a change of 0.34eV.
4.3.2 Introduction of a Buffer Layer
Going back to the very task at hand, all the evidence provided above hint at C60 being a great
candidate for reorienting the CuPc molecules. Figure 4.6, borrowed from reference [64], shows an
STM image of the Cu(111)-C60-CuPc system. A monolayer of C60 has been deposited on the
cleaned Cu(111) surface and has been annealed to ensure complete coverage of the surface, CuPc
C60 CuPc
51
molecules are then deposited onto the C60 monolayer. As it is evidenced by Figure 4.6, CuPc
molecules have indeed adopted ordered phases of what seems to be parallel columns of CuPc
molecules oriented in the standing upright position. Similar behavior is observed in Figure 4.7 for
the system of Ag(111)-C60-CuPc, where the CuPc molecules seem to have adopted similar
ordered structures in the standing orientation.
Figure 4.6 | STM image and epitaxial models of 1ML of CuPc deposited on the Ag(111) surface covered with 1ML of C60.
This figure is borrowed from earlier work done by Taylor J. Stock. a) an oplique unit cell of the superstructure moire patterns is laid out. b) Cartoon of CuPc packing in the standing orientation along the <-110> direction. This periodicity is in fact synchronous with the moire pattern in the direction of vector a. c) Epitaxial models for the brickstone and herringbone phases. Adapted with permission from ref. [64].
52
Figure 4.7 | STM images of 0.5ML of CuPc deposited on Ag(111) covered with 1ML of C60
a) STM image of CuPc molecules shows an entirely different structure than the flat-lying orientation. It closely resembles the Moire patterns observed on the Cu(111)-C60 system. b) The height profile at the step edge shows a height of 0.5nm, making it difficult to confirm a standing orientation or else due to the convoluted nature of STM and dependence of tunneling on both of topography and local density of states.
a)
b)
53
Contrary to our experimental findings, numerous Density Functional Theory (DFT) studies
predict higher binding energies for the flat-lying orientation of CuPc molecules on top of the
C60 close-packed structure [60-62] and in gas phase. Given the earlier suggestive local vacuum
offset in the UPS results for the CuPc-C60 interface as well as the STM results demonstrating
that CuPc molecules adopt a standing orientation in the Cu(111)/Ag(111)-C60-CuPc systems,
then there seems to be a discrepancy between the first principals DFT calculations and what is
actually happening in the physical system. In fact, the DFT studies have been performed on
isolated systems of the C60-CuPc with either slabs of each molecular structure interfacing the
other or in gas phase where single molecules are interfaced with each other. Substrate effects
seem to be the missing common factor in such calculations, in fact a look at work function
measurements as a function of C60 overlayer thickness on various pristine metal surfaces
reveals a strong transfer of charge close to the interface from and to the C60 layer depending
on the work function difference between the C60 and the underlying metallic substrate. In work
done by N. Hayashi et al., band bending at C60-Metal interfaces are examined closely and it
is revealed that substrate effects can have severe implications on the C60 overlayer electronic
properties, up to thicknesses of 2.5nm [63].
4.3.3 Charge Transfer & Buffer-Enhanced Substrate Interactions
Focusing once again on our suspect (substrate effects) to shed light on the discrepancy between
the molecular orientation predictions of DFT calculations and the actual observed preferred
orientation of the molecules, we can see that the missing element in the DFT calculations were
likely the substrate effects which evidently, as demonstrated by Metal-C60 work function
measurements discussed above, allow for band bending and interfacial dipole formation
between the metal substrates and the C60 crystalline layer. In fact, given that our measurements
on the Ag(111)/Cu(111)-C60-CuPc systems all involved a single monolayer of ordered C60,
it becomes further evident that our system lies in a regime of thickness where band bending
54
and interfacial dipoles have the largest impact on the C60 layer (and in turn the CuPc layer
which is interfaced with the affected C60 layer).
Inclusion of the substrate in DFT calculations can be quite costly in terms of computation time,
thus another strategy was devised to account for the ignored Metal-C60 interface. As the
aforementioned work function measurements on the Metal-C60 systems show, the effective
consequence of having a substrate interfacing with the C60 is transfer of charge and
equilibration of the Fermi levels of the C60 lattice and the underlying metal crystal. Hence, to
account for this effect, we set out to carry out a theoretical investigation of the atomic structure
and the resulting electronic properties of the C60-CuPc molecular interfaces in various
configurations.
Initially, first principles DFT calculations were used on both single standing and flat-lying
CuPc molecules interfacing with a single layer slab of close-packed C60 molecules. After
optimizing the atomic structures, we find that the CuPc molecules prefer to lie flat on the C60
molecules with the Cu atom above the bridge site; in agreement with pre-existing literature
[61-63]. Standing orientation of CuPc molecules generally had higher binding energy values.
Introduction of different substrates in this picture (Ag(111) and Cu(111) slabs with a 100
atoms, four layers thick) also had a minor effect on the binding energies. Table 3.1 displays a
summary of the results. Though we found no significant difference in binding energies as a
function of removing, adding, or changing the substrates, this study could not be conclusive as
CuPc-CuPc interactions in the standing orientation were not accounted for (as a result of
having a single CuPc molecule in our structure). As shown in table 3.1, the CuPc-CuPc gas
phase interactions are indeed low in energy and make for significant contributions if accounted
55
for in the Ag(111)/Cu(111)-C60-CuPc structure by introducing a periodic lattice of standing
CuPc molecules.
Table 3.1: Summary of results for binding energies calculated based on DFT
The binding energies of various configurations have been calculated and presented above. The ‘No Substrate’ column refers to gas phase configurations. The ‘s’ and ‘f’ suffixes refer to standing and flat-lying orientations respectively.
Due to difficulty finding a super-lattice periodic across all three layers and high computational
costs, the single CuPc molecule in our models could not be replaced by a periodic overlayer of
CuPc for an accurate depiction of the physical systems. Instead, taking advantage of earlier
analysis of the experimental UPS results on the Metal-C60 interfaces (i.e. the knowledge of
the effective influence of the substrates: addition/removal of charge from the C60 layer
depending on substrate work function) we carried out DFT calculations on the C60-CuPc
interface for varying amounts of charges added or removed from the system. The setups
consisted of a single layer slab of close-packed C60 interfaced with a single layer of ordered
CuPc molecules, once in the standing orientation and once in the flat-lying orientations. Results
of the calculations are summarized in figure 4.8. It can be seen that the addition of more than
one electron per unit cell can make the standing orientation have a more favorable binding
energy value relative to its flat-lying counterpart.
a
The Journal of Chemical Physics (2005): 122.9, 094315 b
Nano Research 5.4 (2012): 248-257
56
Figure 4.8 | Difference in DFT-calculated binding energies of standing and flat-laying CuPc orientation on C60
a) Difference in binding energy of the two orientations plotted as a function of net charges added/removed from each unit cell. b) Models of the supercells used for calculating the binding energies for the standing and flat-lying orientations.
Given the intrinsic low accuracy nature of the DFT method for calculation of binding energies
due to dependence on the choices of Exchange-Correlation functionals (especially in metal-
organic systems) and various approximations such as use of pseudo potentials, we cannot
exactly translate the results to an amount of charge needed to add or remove in order to reverse
the sign of ΔEbinding experimentally. However, the results provide a qualitative framework for
explanation of observation of the CuPc molecules in the standing orientation on the Ag(111)-
C60 and Cu(111)-C60 surfaces as we showed earlier and as also demonstrated in the literature
[59,53,50]. It is also worthwhile mentioning that CuPc molecules deposited on a Au(111)
surface covered by a monolayer of C60 were shown to be in the flay-lying orientation. The
Au(111) surface has a high work function of 5.31eV compared to that of bulk C60 which is
4.6eV. In this system, one expects electron accumulation on Au(111), meaning charges will be
removed from the C60-CuPc interface. Though further DFT calculations are needed to obtain
more data points for figure 4.8 to confirm the switching behavior for removal of charges from
the system (as in the case of Au(111)-C60-CuPc), the trend in the already calculated binding
energy difference values supports the hypothesis.
-0.40
-0.30
-0.20
-0.10
0.00
0.10
0.20
0.30
0.40
-1 0 1 2
Δ B
ind
ing
Ene
rgy
(eV
)
Charge ( e/UC) ΔEbinding
= Eside
– Eface
57
4.3.4 Proposed Method for Molecular Reorientation of Pc Molecules
Accordingly, our DFT calculations demonstrate that there exists a critical amount of charge
transfer between the substrate and the C60-CuPc system (combined) which would allow for a
shift in CuPc orientation to the standing orientation. As the amount of band bending and charge
transfer at an interface is proportional to the work function difference between the two
materials at the interface (as shown in reference [63] for metal-C60 interfaces), then the amount
of charges removed or added to the C60-CuPc system can be controlled through choice of a
substrate. Thus one can define a critical value for substrate work function which would force
the molecules to reorient. Figure 4.9 proposes a general strategy which could be deployed for
reorienting molecules. On metallic surfaces where CuPc molecules adopt a flat-lying
orientation, the introduction of a strongly interacting buffer layer such as C60 can alter the
orientation of the CuPc molecules. As explained earlier, the choice of C60 provides a rather
geometrically smooth close-packed surface with six-fold symmetry and allows for strong
electronic interactions with the metallic substrates and CuPc molecular films. The buffer layer
then can act as a medium for altering the equilibrium state of the CuPc molecules through
mediation of charge transfer and alteration of charge distributions across the interface.
Figure 4.9 | Proposed steps for achieving charge transfer threshold for reorienting CuPc stacking
The choice of buffer layer, its thickness, as well as the substrate can effectively result in an equilibrium charge distribution state that can lead to reorienting the CuPc molecules. The diagram illustrates the steps needed to do so as well as the role of each step described below it.
58
4.3.5 Summary
In summary, it is found that the introduction of a monolayer-thick C60 buffer layer is enough
to reorient CuPc molecules at Ag(111)-CuPc and Cu(111)-CuPc interfaces. Given the weakly
interacting adsorption state of CuPc molecules on both of the studied surfaces, a mechanism
of reorienting the CuPc molecules was proposed through altering the interactions but keeping
similar geometric symmetries as the underlying substrate. A C60 buffer layer was introduced
to act as a catalyst to strengthen interactions. Furthermore, DFT calculations emulating loss
and addition of charges to the C60-CuPc interface through interactions with the substrate
predict alteration of orientation of CuPc molecules at critical charge transfer thresholds.
Though further studies need to be carried out to fully confirm the usefulness of the suggested
mechanism, there is strong evidence in literature showing that CuPc molecules adopt a flat-
lying orientation on a monolayer of C60 deposited on Au(111) which has a significant
difference in its work function when compared to Ag(111) and Cu(111). Thus the introduction
of a monolayer of C60 as a buffer does seem to be a promising technique for altering and
parametrizing molecular orientation of CuPc molecules as a function of the substrate work
function, as well as predict orientation when paired with first principles DFT calculations.
59
Chapter 5
Summary & Future Work
5.1 Summary
The work carried out in this thesis has fundamentally addressed the nature of interactions at
archetypal metal-organic interfaces of interest that have promised great prospects for
applications in optoelectronics and molecular electronics. The interface between noble metal
surfaces and CuPc molecules has been the focus of research and the nature of interactions in
such systems has been revealed through a combination of experimental work and theoretical
modelling. Further, mechanisms of control over molecular orientation and stacking in the
systems are studied and a methodology for controlling orientation is proposed.
In chapter 3, the interface between noble metal (111) surfaces and CuPc molecules were
thoroughly discussed and experimental STM results revealed the existence of a 2D liquid state
with short range order at submonolayer regimes, never seen before. The phase transition from
liquid to solid was shown to take place at a coverage of 0.90+-0.02 ML, where the molecules
formed a solid; with long range order emerging at a full monolayer. Monte Carlo simulations
showed that only accounting for local interactions (hard core interactions) is good enough of
an approximation to explain the nature of intermolecular interactions on the aforementioned
surfaces. It was also demonstrated, through comparison of STM images of similar
submonolayer films on both Ag(111) and Cu(111) surfaces with corresponding simulations,
that the substrate does play a small role. The substrate interactions can be accounted for by
defining an effective radius for the molecules on each substrate. As shown before, an effective
radius of 0.67nm was obtained for Ag(111) and 0.9nm for Cu(111). Furthermore, CuPc
molecules were found to have dual adsorption states on both substrates; the already mentioned
liquid state and a disordered immobile state. Our experiments showed the immobile state can
be achieved through annealing the submonolayer films to a critical temperature or by exposing
60
them to high tip-sample biases. The formation of the immobilized state through annealing shed
light on the origin of disagreements between claims of a non-mobile disordered adsorption
state on Cu(111) at room temperature and our observation of a liquid state. Additionally, the
molecular pinning, previously also observed by another group at the NiPc-Au(111) interface
and attributed to breakage of hydrogen bonds and formation of bonds with the substrate; was
shown to happen at two different thresholds on Ag(111) and Cu(111), suggesting a different
mechanism at play. The pinning of molecules through application of a large enough bias also
provides a potential technique for a bottoms up approach to creating molecular devices.
Chapter 4 moved on to discuss the full monolayer films and the emerged crystalline order. It
was shown that lattice matching, relative substrate and molecule geometries, and as well the
symmetries in the system played a role in formation of the observed lattice structures;
suggesting small coupling between molecule-substrate interactions and molecule-molecule
interactions. The short range intermolecular interactions allow the molecules to settle into the
highest entropy configurations, given the underlying lattice symmetries. In an attempt to
reorient CuPc molecules at the said interfaces, the introduction of a single monolayer C60
buffer was made. It was shown through PES experimental results and DFT calculations of
binding energies, that C60’s strong interaction with the substrate and the CuPc layer (i.e. at
both interfaces), allowed for redistribution of charge at the new effective-substrate/CuPc
interface (where the effective-substrate is the metal/C60-ML) which in turn resulted in
reorienting the CuPc molecules to a standing edge-on orientation. Further analysis of our DFT
results and data available on the Au(111)-C60-CuPc interface suggest existence of a critical
charge transfer threshold (and in turn substrate work function) which determines the lowest
energy state in terms of molecular orientation and stacking; therefore putting forth a
mechanism for control of molecular orientation and stacking.
61
5.2 Future Work
Given the limited time spent on the projects covered in this thesis (about 1 year), there remain
many potential questions to be answered. Firstly, with regards to the 2D liquid state of CuPc
molecules and the emergence of entropic order, the following can naturally be extensions to
the work already done during the extent of this degree:
1- More representative Monte Carlo simulations accounting for molecular geometry and
substrate potential landscape can be carried out to increase predictive power of the
models. As the concentration of the molecules increases on the surface, the more the
hard disks model diverges from the actual molecular system studied; thus it is important
to create more complex models to look at the critical densities nearing phase transition
and formation of an ordered crystal lattice. One can wonder if the commonly observed
rotated row structures are a result of entropic effects as well?
2- Implementation of massively parallel Monte Carlo algorithms and taking full
advantage of the GPCs on SciNet would also make a great next step for exploration of
higher density regimes more efficient means of running simulations on systems with
rotational degrees of freedom.
3- The choice of effective molecular radius can be studied in more depth. The full
monolayer covered surface can be used to extract a packing density that can possible
be used to plug into the simulations. Is the ordered structure at 1ML and its packing
density reflective of the exposed nature of molecular interactions at the submonolayer
regime? Or does the system diverge from entropic effects as molecules are more closely
packed and van der Waal interactions become more pronounced?
4- Various families of Phthalocyanines show similar behavior (preliminary work not
presented in this thesis have shown), it would be a next step in understanding
interactions and perhaps seeing the effects of substitution of the peripheries of the
molecules on the nature of intermolecular interactions. Perhaps there are trends that
emerge as a function of choice of metal complex of the Pc molecules used and its
62
peripheral substitution type? If so, this could provide further insight on the emergence
of order at a monolayer.
5- Given the annealing experiment results revealed in this work on the Ag(111)-CuPc
interface, it would be nice to see similar experimental data on the the Cu(111)-CuPc
counterpart. Given the lower pinning bias threshold on Cu(111), one might wonder if
a lower annealing temperature would cause the molecules to be immobilized. Results
in the literature seem to suggest so, however, confirmation is needed.
6- A natural extension of the studies would also be temperature dependent study of the
phase transition from liquid to solid.
The above points are to name a few, there are of course many more pathways to follow in order
to explore the phase space of such molecules. Moving on to the second major portion of this
work on molecular orientation control, here are further developments that need to be worked
on:
1- To really confirm with confidence the applicability of the proposed mechanism for
molecular stacking and orientation in the metal (111)-CuPc systems, it is necessary to
confirm the behavior of CuPc molecules using STM on various substrates of different
work functions (below and above 4.6eV, that of C60). Au(111) would make a decent
choice, given there is already substantial evidence in literature that support flat-laying
CuPc molecules on the Au(111) surface covered in C60.
2- DFT calculations need to be carried out for a larger range of charges removed and
added to the C60-CuPc system. This would enable comparison with substrates such as
Au(111) which have a much higher work function when comparing with C60.
Following the above experiments, other planar molecules can be studied within this
framework in order to make headway towards generalizing this approach to a larger subset of
organic molecules.
63
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Copyright Acknowledgements
Figure 3.10 has been adopted from the following previously published work:
“Tunneling electron induced chemisorption of copper phthalocyanine molecules on the
Cu(111) surface”
T. Stock, and J. Nogami, Applied Physics Letters, 104, 071601 (2014)
DOI: 10.1063/1.4866283
Figure 4.6 has previously been reported and has been adopted from the following PhD thesis:
“Organic Molecular Thin Films: Growth , Structure , and Manipulation Studied by Scanning
Tunneling Microscopy”
T. Stock (2015). Organic Molecular Thin Films: Growth, Structure, and Manipulation
Studied by Scanning Tunneling Microscopy. (Doctoral dissertation).