theoretical and computational materials science
DESCRIPTION
Theoretical and Computational Materials Science. TETY. Photonic, Phononic and Meta- Materials. Materials Theory. C. Soukoulis. I. Remediakis. M. Kafesaki (to be appointed). G. Kopidakis. Materials Theory Group (est. 2007). - PowerPoint PPT PresentationTRANSCRIPT
Theoretical and Computational Materials ScienceTETYTETY
Photonic, Phononic and Meta- Materials
M. Kafesaki (to be
appointed)
Materials Theory
I. Remediakis
G. Kopidakis
C. Soukoulis
C. Motsanos, N. Galanis, C. Mathioudakis, G. Kopidakis, I.Remediakis, E. Tylianakis, G. Barmparis, S. Stamatiadis (not shown: G. Kwtsopoulou, A. Maniadaki, G. Vantarakis,
E. Pantoulas (graduated), K. Moratis (graduated))
Members: two faculty (I.R, G.K), one adjunct (C.M), five students (four PhD, one undergraduate), one staff.
Materials Theory Group (est. 2007)
Core courses (programming, solid-state physics, quantum mechanics).
Advanced courses (group theory, electronic structure).
~ 1 diploma thesis/year.
4 PhD students, 1 graduated.
2 ‘Manasaki’ best graduate student awards.
Training
Empirical Force Fields plus Classical Monte-Carlo and Molecular Dynamics Simulations.
Quantum mechanical simulations (Tight-binding / LCAO).
Ab initio simulations (Density-functional Theory - DFT).
Variety of home-made, commercial and open-source codes running on a Beowulf cluster of ~60 nodes.
From atomistic Simulations - Electronic Structure Theory...
Surface chemistry and catalysis. Carbon-based materials and other superhard ceramics. Quantum dots, nanocrystals, nanowires. Non-linear dynamics, energy localization and transfer. All-optical signal processing and firewalls. Hydrogen storage.
… to computer-aided Design of new Materials
Atomistic simulations
We are usually interested in the ground and metastable states of the system, i.e. the global and local minima of
G=U+PV-TS=f(R1, R2, ...,RN; P, T, ...).
Two tasks: (a) approximate G (b) minimize G.
If U is more important than S (e.g. solids), we need an accurate quantum mechanical method (such as Density Functional Theory, DFT). Most CPU time is spent on calculation of G.
If S is more important than U, (e.g gases and liquids), we need an accurate statistical method (such as empirical potential Monte Carlo or Molecular Dynamics). Most CPU time is spent on minimization of G (time evolution).
Nano is differentGold is noble
...but nano-gold is a superb catalyst.
Left: Jewel from Malia, Crete, Greece (ca. 1800 BC);
Right: CO oxidation on Au nanoparticle
(Remediakis, Lopez, Nørskov, Angew. Chem. (2005)).
See also: “Making Gold Less Noble”, Mavrikakis et al., Catal. Lett. (2000).
Nanoparticle shapes
G = Gb u l k + Σ γh k l Ah k l (Gibbs, 1878)
Equilibrium shape: minerals (billions of years to equilibrate) or nanoparticles (small size).
www.mindat.org Turner et al., Adv. Func. Mater. 2009
Surface energies of Ru from DFT
Virtual catalyst for NH3 synthesis
Operation of this catalyst is a pure nano-effect.
K. Honkala, A. Hellman, I. N. Remediakis, A. Logadottir,A. Carlsson, S. Dahl, C.H. Christensen and J. K. Nørskov,
Science, 307 558 (2005);Surf. Sci., 600, 4264 (2006); Surf. Sci., 603, 1731 (2009).
Si quantum dots in a-SiO2E=0.000 E=0.010E=0.010
E=0.010 E=0.005E=0.061 E=0.050
Red : {100} Blue : {110} Green : {121}G. Hadjisavvas, I. N. Remediakis, P. C. Kelires, Phys. Rev. B 74, 165419 (2006);
On-going collaboration with R. Kalia and P. Vashishta, USC.
Shape of diamond nanocrystals in amorphous Carbon
G. Kopidakis, I. N. Remediakis, M. G. Fyta and P. C. Kelires, Diam. Rel. Mater. 16, 1875 (2007).
G. D. Barmparis & I. N. Remediakis, in preparation.
Au nanoparticles in CO gas
Theoretical and Computational Materials ScienceTETYTETY
http://theory.materials.uoc.gr
Theory and modeling in materials physics• Understand and control properties of materials with fundamental and
practical interest from the bottom up by developing and using atomic-scale computational and theoretical tools
• Simple models for fundamental understanding– General physical phenomena of wide applicability– Novel concepts of general validity– Qualitative results
• Realistic models for accurate predictions– Atomistic computer simulations well suited for applications at nanoscale– Direct comparison with experiments
• Current activities– Nonlinear wave localization and propagation– Structural, mechanical, electronic, optical properties of amorphous and
nanostructured materials– Practical applications in ICT, “green” technologies
Localization in nonlinear disordered systems• Widely used toy models in condensed matter (polarons, excitons)
nonlinear optics, photonics, BECsResults often confirmed by realistic calculations
• Discrete linear models– Periodic (homogeneous lattices)
propagation– Disordered (inhomogeneous)
Anderson localization• Discrete nonlinear models
– Periodic, localization without disorder– Disordered ? GK, Aubry PRL 2000
• Interplay of disorder and nonlinearity– Mathematical and numerical results– Experimental confirmation
Lahini et al PRL 2008
Localization in isolated nonlinear disordered systems• Anderson localization not destroyed by nonlinearity
GK, Komineas, Flach, Aubry PRL 2008, Johansson, GK, Aubry EPL 2010
Propagation in driven nonlinear disordered systems Johansson, GK, Lepri, Aubry EPL 2009
Transmission thresholds for amplitude of driving field
Self-induced transparency
Targeted transfer of nonlinear excitations
• Understand and control propagation phenomena in complex systems
• Ultrafast electron transfer in photosynthetic reaction centers
not thermally activated, nonlinear dynamical theory
Biomimetics
Aubry, GK JBP 2005
Amorphous and nanostructured carbon
• Relate macroscopic properties and experiment to atomic bonding through simulation
• Tight-binding molecular dynamicsMore efficient than first principles, more accurate than empirical potentialcalculations
• Atomic structure, mechanical, electronic, optical properties
Mathioudakis, GK, Kelires, Wang, Ho PRB 2004
Amorphous and nanostructured carbon
Accurate calculation of imaginary partof dielectric function Mathioudakis, GK, Patsalas, Kelires DRM 2007
Nanodiamond in a-C• link atomic level structure with optoelectronic response Vantarakis, Mathioudakis, GK, Wang, Ho, Kelires PRB 2009
Density sp3 fraction3.24 g/cm3 88%
2.91 g/cm3 71%
2.58 g/cm3 51%
Diamond, a-D
Mechanical properties of nanocrystalline materials• Hall-Petch effect for metals
Hardness and yield strength increase with decreasing grain size• ‘Reverse’ Hall-Petch Softening when grain size is in nanometer range• Optimum grain size for strongest material Crossover from dislocation-dominated plasticity to grain-boundary sliding
• dependence of elastic properties on grain size?Softening not limited to plastic deformations.
• What about non-metals?Softening for non-metals, such as diamond.
wikipedia
Mechanical properties of nanocrystalline materials• Universal laws for softening of nanocrystalline materials
– Emerge from our studies of elastic response of very different materials, such as copper and diamond.
– Appear to be general, independent of chemical composition of material.
– Derived from general considerations of increasing fraction of grain boundary atoms.
Galanis, Remediakis, GKPSS 2010
Mechanical properties of nanocrystalline materials
• Similar softening for ultra-nanocrystalline diamond
Remediakis, GK, Kelires AM 2008
All-optical processing
Pattern matching
circuit
Optical routing switch
Optical bit filter
Incoming data
Control signal
Router
InterceptOptical buffer
memory
Optical routing switch
Suspect packet
FirmwareInterface
OpticalDomain
ElectronicDomain
SAPInterface
General Purpose Processor
Pattern matching
circuit
Optical routing switch
Optical bit filter
Incoming data
Control signal
Router
InterceptOptical buffer
memory
Optical routing switch
Suspect packet
FirmwareInterface
OpticalDomain
ElectronicDomain
SAPInterface
General Purpose Processor
Core routers
Metro ring
IP / Ethernetcore
Optical firewall
Optical transmission rates at hundreds Gb/s
Electronic processors at a few Gb/s
Bridge the gap bysuccessfully implementing network security operations ‘on the fly’
No optical to electronic (and back) conversion
R. Webb et al IEEE JSTQE 2011
http://www.ist-wisdom.org/
External Collaborators
S. Aubry Saclay, France
M. Johansson Linkoping, Sweden
K-M. Ho Ames, USAC-Z. Wang
P. Kelires Lemessos, Cyprus
J.K. Norskov Stanford, USA
H. Hakkinen Jyvaskyla, FinlandK. Honkala
http://theory.materials.uoc.gr
http://theory.materials.uoc.gr 27
Theoretical and Computational Materials ScienceTETYTETY
http://theory.materials.uoc.gr