Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems
Andriy Kovalenko
2nd International Conference on Structural Nano Composites – NANOSTRUC 2014
Consejo Superior de Investigaciones Científicas (CSIS), Madrid, Spain. 20-21 May 2014
A Platform of Theory, Modeling, and Simulation
on Multiple Space and Time Scales
Nanoscale
Continuum
Methods Mesoscale
methods Lattice Monte Carlo
Brownian dynamics
Dissipative particle
dynamics
Molecular
Simulations
MM
MD
MC
Semi-empirical
Methods
Ab initio
Methods 10-15
10-12
10-9
10-6
10-3
100
10-10 10-9 10-8 10-7 10-6 10-5 10-4 (nm) (mm)
(fs)
(ps)
(ns)
(ms)
(ms)
LENGTH
[meters]
TIME
[sec] Equilibrium & Nonequilibrium Statistical Mechanics
Integral Equation Theory of Molecular Liquids / Molecular Theory of Solvation
(including 3D-RISM, replica RISM, ss-GLE)
nanodevices,
nanomaterials,
biomolecular
systems Nanoscale physics
chemistry
www.cein.ualberta.ca / research / kovalenko
The Kovalenko Group research program:
3D-RISM-KH molecular theory of solvation – predictive method for REAL systems
)'()'(')( vvuvuv rcdh
rrrr
• three-dimensional reference interaction site model (3D-RISM) integral equation:
- direct correlation function with asymptotics of site interaction potential (force field)
where
1)()( uvuv rr hg - distribution function / total correlation function
)/()()( B
uvuv Tkuc rr
)()()( vvvvvvv rhrr - susceptibility of solvent
molecular geometry
solvent density
intermolecular correlations
• Kovalenko-Hirata closure relation
1)(for )()()/()(1
1)(for )()()/()(exp)(uvuvuv
B
uv
uvuvuv
B
uvuv
rrrr
rrrrr
gchTku
gchTkug
)(uvru
• Solvation structure and thermodynamics in closed analytical form
m )()()())(())(( uvuvuv
21uv2uv
21v
B
urrrrrr cchhhdTk
Solvation free energy:
Enthalpy-entropy Decomposition: v
u1uuvvuvu , mm TTssT VV
m
i
ii
i
i
ugd
R
Rrrr
RRf
)()()(
uvuvv
uuvSolvation forces,
analytical gradients:
Partial molar volume:
)( 1)( 1 vvvuvvv
tot
u rcdcdV rrr
Kovalenko, Hirata, J. Chem. Phys. 1999, 110, 10095 Kovalenko, in: Molecular Theory of Solvation, Kluwer, 2003 Gusarov, Pujari, Kovalenko, J. Comput. Chem. 2012, 33, 1478 Kovalenko, Pure Appl. Chem. 2013, 85, 159
Water around a NaCl ion pair in the CIP and SSIP arrangements
PMFs of NaCl in aqueous solution
Kovalenko and Hirata, JCP, 112, 10391; 10403 (2000)
Cluster arrangement
of Na+ and Cl- ions
and water molecules
in 1 mol/l solution
Potential of mean force between simple ions in aqueous
solution by 3D-RISM molecular theory of solvation
Desolvation
Contact
Ionic Pair Solvent
Separated
Ionic Pair
Yoshida, Yamaguchi, Kovalenko, and Hirata, JPCB (2002)
Neutron diffraction and
compressibility
experiment
vs
RISM-KH theory
Water-rich mixture: Tetrahedral
hydrogen bonding cage
Alcohol-rich mixture:
Zigzag hydrogen bonding chains
Omelyan, Kovalenko, and Hirata, JTCC (2003)
Structural transitions in tert-butanol-water mixture
by RISM-KH molecular theory of solvation
≈500 experimental compounds
Solvation free energy: experiment vs 3D-RISM-KH
ΔG
exp
(kcal/m
ol)
Δμ+PMV correction, 3D-RISM-KH (kcal/mol)
D. Palmer et al, J.Phys: Condens.
Matt. 22 ,492101 (2010) J.-F. Truchon
Role for confined water in chaperonin function [Jeremy L. England, Del Lucent, and Vijay S. Pande, JACS 130, 11838 (2008)]
Chaperonin nanocavity’s capacity for accumulating water near its surface
may correlate with its success in catalyzing folding
Cut-away view of solvation structure
of wild type GroEL+ES. The waters
counted as near the surface are
colored red and white.
Gray bars: the experimentally measured folding rates of DM-MBP
when encapsulated inside different mutants of GroEL. Blue bars:
the best linear fit of the number of surface waters to the measured
refolding rate
Computational challenge:
Large protein ~70,000 atoms (up to 1,000,000 atoms with solvent),
internal solvation is essential
R≈0.78
Water in internal cavity of Chaperonin mutants: Molecular Dynamics simulation vs 3D-RISM-KH
Layers used to count water molecules
in the internal cavity of the GroEL/ES
Occupation numbers of water in the internal cavity
of the WT GroEL and GroEL mutants
3D-RISM-KH speeds up calculation of the occupation numbers in the internal cavity
of GroEL/ES by two order of magnitude, compared to explicit solvent MD
R=0.98
M. Stumpe, N. Blinov, D. Wishart, A. Kovalenko, and V. Pande, J. Chem. Phys. B 115, 205 (2011)
Convergence of MD water density distributions
4Å
2 Å
1 Å
0.5 Å
5 ns De
nsity c
orr
ela
tion
fu
nctio
ns
M. Stumpe, N. Blinov, D. Wishart, A. Kovalenko, and V. Pande,
J. Chem. Phys. B 115, 205 (2011)
Effects of conformation flexibility and ion
distribution on folding rates of chaperonins
3D
-RIS
M-K
H/N
aC
l 0.2
M
3D
-RIS
M-K
H/e
xp
licit io
ns
MD
, explic
it ions
Single snapshot Multiple snapshots
3D-RISM-KH MD
Integration volume for
occupation number calculations
0 5 10 15 20
-80
-40
0
40
Distance (Å)
E (
kJ/m
ol)
msol
(B)
msol
(Q)
Esol
(B)
Esol
(Q)
Thiophene
disaggregation
path
Optimized
geometry
0 5 10 15 20-200
-150
-100
-50
0
50
100
E (
kJ/m
ol)
Distance (Å)
PMF3D-RISM-KH+PW91
(B)
PMF3D-RISM-KH+PW91
(Q)
ECOSMO+PW91
(B)
ECOSMO+PW91
(Q)
Bdisag
Bsol. exp.
Bitumen Fragment Adsorption on Chabazite: 3D-RISM-KH vs COSMO
COSMO:
• Continuum solvation method
• Accounts for solvent properties
such as dielectric screening
3D-RISM-KH molecular
theory of solvation:
• Accounts for solvation
with accuracy comparable to
explicit solvation model
• Predicts desolvation barriers
that have to be overcome by
bitumen molecules
approaching solvated surface
• Predicts monolayer adsorption
)()()()()PMF(
solvPW91solvPW91dμdEdμdEd
Stoyanov, S.R.; Gusarov, S.; Kovalenko, A. Multiscale Modeling of the Adsorption Interaction Between Model Bitumen
Compounds and Zeolite Nanoparticles in Gas and Liquid Phase, in: Industrial Applications of Molecular Simulations,
Meunier, M. (ed.); Taylor and Francis Books, Boca Raton, FL, USA, 2011, pp. 203-230.
Adsorption of indole on kaolinite surface
from solution in toluene and in n-heptane
Aluminum hydroxide face • Indole HN is oriented b/w two or one OH groups
• Orientation of toluene molecules is parallel
Silicon oxide face • Indole molecules are almost parallel to the surface
• Toluene molecules are perpendicular to the surface, pointing
with CH3 site or ring H atoms towards SiO hexagon center
Toluene prefers
Silica face
Indole prefers
Alumina face
guv
Distance, Å
N H
Fafard, J.; Lyubimova, O.; Stoyanov, S. R.; Kenne, G.; Gusarov, S.;
Cuervo, J.; Kovalenko, A; Detellier, C. J. Phys. Chem. C, 2013, 117, 18556
Multilayer adsorption of indole on kaolinite in toluene / n-heptane solution
Results
•
predicts adsorption and depletion layers
• Organic mass loading shows multilayer
formation in organoclays
• Aromatic and hydrogen-bonding solvents
leave only a monolayer of indole
Prospectives:
o Rational design of additives for selective
desorption of bitumen from kaolinite
o Selection of green solvents for
non-aqueous extraction of bitumen
surface
aver ),,( dd)( zyxgyxzg
Fafard, J.; Lyubimova, O.; Stoyanov, S. R.; Kenne, G.;
Gusarov, S.; Cuervo, J.; Kovalenko, A; Detellier, C.
J. Phys. Chem. C, 2013, 117, 18556
Self-assembly, conformational transitions, and functions
of synthetic organic supramolecular nanoarchitectures
GC (Guanine-Cytosine)
motif
rosette ring
rosette nanotube
self-assembly in solution
self-assembly in solution
Inner and outer hydration structure of rosette nanotube
wetting monolayer in rosette nanotube
channel
structural water
Interior shell water stabilizes rosette nanotube
Water binding strength: 4.1 kcal/mol per molecule
J. G. Moralez, J. Raez, T. Yamazaki, R. K. Motkuri, A. Kovalenko, H. Fenniri, J. Am. Chem. Soc. Communications 2005, 127, 8307
R. S. Johnson, T. Yamazaki, A. Kovalenko, H. Fenniri, J. Am. Chem. Soc., 2007, 129, 5735
G. Tikhomirov, T. Yamazaki, A. Kovalenko, H. Fenniri, Langmuir, 2008, 24, 4447
T. Yamazaki, H. Fenniri, A. Kovalenko, ChemPhysChem. 2010, 11, 361
Self-assembly, conformational transitions, and functions
of synthetic organic supramolecular nanoarchitectures
One-pot fabrication
of gold nanoparticles
Au NP 1.4 nm
most stable conformation nucleation pocket
most stable De
xam
eth
aso
ne
initial relaxed initial relaxed
Ta
mo
xif
en
Drug delivery carrier
3D-RISM-KH molecular theory of solvation: an essential part of
multiscale modeling of nanochemical and biomolecular systems
3D-RISM-KH yields the solvation structure and thermodynamics,
and provides self-consistent field effective potentials and solvation forces
in solutions of various composition in a wide range of thermodynamic conditions
)}]({),([)]([)}]({),([ solvationsolute rrrrr m eee nnEnA
N. Blinov et al., Biophys. J. 98, 282 (2010);
S. Genheden et al., An MM/3D-RISM
approach for ligand binding affinities
J.Phys. Chem. B 114, 8505 (2010)
• Ab initio KS-DFT / 3D-RISM-KH molecular theory of solvation;
Implemented in the ADF computational chemistry package:
S. Gusarov, T. Ziegler, and A. Kovalenko,
J. Phys. Chem. A, 110, 6083 (2006);
D. Casanova, S. Gusarov, A. Kovalenko,
and T. Ziegler, J. Chem. Theory Comput. 3,
458 (2007)
i
iii
KH
i
UV
R
RrurgRRf
)()(/)( solvation
m
• Multiple Time Step Molecular Dynamics of a biomolecule
steered with 3D-RISM-KH molecular theory of solvation
Implemented in the Amber molecular modeling package:
• Combined with Molecular Mechanics in a MM/3D-RISM-KH
method for free energy calculations
• As a standalone program available for community free of
charge as a part of the AmberTools
3D molecular theory of solvation coupled
with MD in Amber, T. Luchko et al., J. Chem.
Theory Comput. 6, 607 (2010);
I. P. Omelyan and A. Kovalenko, J. Chem.
Phys. 139, 244106 (2013)
http://ambermd.org/#AmberTools
[T. Luchko, D. Case, S. Gusarov, A. Kovalenko]
Predictive multiscale modeling of nanochemistry and nanocatalysis in solution by ab initio methods coupled with molecular theory of solvation
Reactions: Potential Energy States analysis
Solvation Structure and Thermodynamics
Analytical gradients: Gas phase + Solvation
RRR
solvel)( mEA
Implemented in
ADF computational chemistry package
• Optimal structure
• Properties (NMR,CD,IR,…)
• Reactions / Nanocatalysis
• Spectroscopy/Photochemistry
• ab initio CASSCF, KS-DFT, OFE-DFT coupled with 3D-RISM-KH theory of molecular solvation
• Works at the Car-Parrinello level
• 3D maps of solvation shells at MD level, without noise
• Solvation of macromolecules including inner spaces
• Analytical gradients in solution: geometry optimization, transition states, reactions, nanocatalysis in solution
A. Kovalenko, F. Hirata, J. Chem. Phys. 1999, 110, 10095. H. Sato, A. Kovalenko, F. Hirata, J. Chem. Phys. 2000, 112, 9463. S. Gusarov, T. Ziegler, A. Kovalenko, J. Phys. Chem. A 2006, 110, 6083 D. Casanova, S. Gusarov, A. Kovalenko, T. Ziegler, J. Chem. Theory Comput. 2007, 3, 458 J. Kaminski, S. Gusarov, T. Wesolowski, A. Kovalenko, J. Phys. Chem. A 2010, 114, 6082
Ionic Liquid
Carbon Nanotube
Glycine
Cellulose Nano Crystals
We employ state-of-the-art multiscale theory modeling and simulations
to develop quantitative structure-property relationships (QSPR)
between surface chemical modifications and properties
for rational design of CNC-based materials
CNC modifications so as to: • Tune surface properties
• Retain hydrogen bonding network
• Preserve mechanical properties
• Control colloidal properties (dispersion)
• Control polymer melt / solution flow
Cellulose Nano Crystals (CNC or NCC): • Reinforcing additive in high-value products
• Allows the deepest level of structure control
• Has reduced defect occurrence
• Easy to functionalize
• Need tuning of hydrophilicity/hydrophobicity
Wadood, H. Can. J. Chem. Eng. 2006, 84, 513
Beck-Candanedo, et. al.
Biomacromol. 2005, 6, 1048.
3 –
5 n
m
Cellulose Nano Crystals Cellulose polymers
Acid hydrolysis
Native
cellulose
Crystalline regions
Amorphous region
100 – 300 nm
CNC from wood
CNC particle model and methods
Iα cellulose unit cell Quantum Chemistry Methods (HF, DFT)
o Geometrical and electronic structure
o Missing force field parameters
Molecular Dynamics (Amber11 software)
o GLYCAM06 (carbohydrate force field)
o SPC/E water model
3D-RISM-KH solvation structure and thermodynamics
of nanoparticles in solution
I cellulose crystal structure has been used to build the initial
fibril: 34 chains (every chain consists of 16 glucose units)
Sulfate concentration:
Boluk, Y. Elemental analysis
NCC surface
modified with
SO3– groups
S. R. Stoyanov, S. Gusarov, and A. Kovalenko, in: Production and Application of Cellulose Nanoparticles, M. T. Postek, R. J. Moon, A. Rudie, M. Bilodeau (Eds.), (TAPPI Press, 2013), pp. 147-150.
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014).
top view side view
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014)
Relaxation and twisting of CNC particle
CNC particles twisting: Analysis
CNC surface modified with SO3
– groups
TM-AFM images of microfibrils of Micrasterias denticulata. In both (a) and (b) the microfibrils can be seen to undergo right-handed twist. S.J. Hanley, J-F. Revol, L. Godbout, D. G. Gray. Cellulose (1997), 4, 209-220
Short particle (shown above)
Long particle Short particle (shown above)
Long particle
S. R. Stoyanov, S. Gusarov, and A. Kovalenko, in: Production and Application of Cellulose Nanoparticles, M. T. Postek, R. J. Moon, A. Rudie, M. Bilodeau (Eds.), (TAPPI Press, 2013), pp. 147-150.
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014).
O6d
O5
O3d
O5
O3d
O5
Experimental data: hydrogen bonding in Iα cellulose
1.60Å, α=49°
1.84Å, α=68°
α
O6a
O2
O2
O6d
O2
C6d
O2 2.55Å, α=36°
2.34Å, α=4°
2.60Å, α=29° 3.0Å, α=17°
CH…O
contacts
Hydrogen
bonds
Hydrogen bonding parameters:
o r(D-A) 3.0 Å
o A-D-H angle cutoff of 20
Reorganization of CNC intramolecular hydrogen bonds
O6d-O4
O3d-O5 Bonds parameters are r(D-A) 3.0 Å
A-D-H angle cutoff is 20
NCC
O6d-O3
O6a-O3
O6a-O2
O6d-O2
Hydrogen bonds stabilize twisted CNC structure.
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014)
CNC…water solvent hydrogen bonding
Towards understanding:
Hydrogen bonding, counterion and solvent effects
CNC drying and re-dispersion behavior
Beck, S.; Bouchard, J.; Berry, R.
Biomacromolecules, 2012, 13, 1486
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014)
Charge redistribution upon relaxation of neutral CNC
unrelaxed
CNC
relaxed
CNC
Sections of 3D maps of Na+ distributions
gNa+(r) in solution around CNC particle
gNa+(r)=3.0 (in yellow)
gCl-(r)=3.0 (in gray) 0.030 mol/kg NaCl
Before relaxation:
Thick interfacial layer
of Na+ counterions
After relaxation:
Thin interfacial layer
of Na+ counterions
Even distribution
of Na+ and Cl– ions
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014)
Driving forces of twisting of CNC particles
Driving forces of the twisting of CNC in solution, revealed by MD/3D-RISM-KH modeling:
• Chirality of the sugar polymer (precursor)
• Reorganization of the intramolecular hydrogen bonds
• CNC – water hydrogen bonding
• Relaxation of the surface charge macrodipole and of the interfacial screening charge
Time correlation function
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014)
<- r ->
Solvent mediated effective Interaction between parallel
CNC particles vs distance Spin angle 0°
Pristine particles in water: Attractive interactions at 3-15 Å
Pristine particles in aq. NaCl: Stronger attraction than in water
Sulfated particles in aq. NaCl: Aggregates disturbed by
electrostatic repulsion and stabilized by Na+
Fine structure suggests strong specific solvent-solute interactions.
S. R. Stoyanov, S. Gusarov, and A. Kovalenko, in: Production and Application of Cellulose Nanoparticles, M. T. Postek, R. J. Moon, A. Rudie, M. Bilodeau (Eds.), (TAPPI Press, 2013), pp. 147-150.
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014).
Effective Interaction of CNC rods bridged by Na+ counterions
• 3D distribution functions at isoelectric point show
formation of Na+ bridges stabilizing NCC aggregates
S O O
O
O
O
O
O
O S
S
Isovalue for Na+ ~ 8 Isovalue for Na+ ~ 4
Na+
Hw Ow
6 Å
Towards understanding and control of: cholesteric ordering NCC dispersion in various solvents
S. R. Stoyanov, S. Gusarov, and A. Kovalenko, in: Production and Application of Cellulose Nanoparticles, M. T. Postek, R. J. Moon, A. Rudie, M. Bilodeau (Eds.), (TAPPI Press, 2013), pp. 147-150.
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, Nordic Pulp & Paper Res. J., 29. 144 (2014).
Dispersion of modified CNC in water, benzene, and ionic liquid
64.0×64.0x20.76 Å
Distance
pristine esterified
0 5 10 15 20
-40
-20
0
20
40
60
80
100
Distance, Å
E,
kc
al/
mo
l
water
benzene
IL
0 5 10 15 20
-40
-20
0
20
40
60
80
100
Distance, Å
E,
kc
al/
mo
l
water
benzene
IL
Structures are relaxed using PCFF,
with CNC backbone atoms fixed,
in Accelrys Materials Studio®
No solvent expulsion barrier and
a lower disaggregation barrier
in benzene or in ionic liquid
for esterified CNC
Disaggregation barriers in
benzene and IL are higher
than in water for pristine CNC
Stoyanov, S. R.; Gusarov, S., Kovalenko, A.
in: Production and Application of Cellulose Nanoparticles,
Postek, M. T.; Moon, R. J.; Rudie, A.; Bilodeau, M., Eds.
TAPPI Press, 2013, pp. 147-150.
Cl–
mmim+
gO = 5.0
gH = 2.8
gNa = 2.0
gCl = 2.4
H C O
H Cl– O Na+
CNC-water hydrogen bonds replace
CNC-CNC hydrogen bonding network
gNa = 2.0, gCl = 2.4
Effective interaction between CNC particles vs torsion angle
in NaCl aqueous solution
Torsion angle
• Asymmetry about 90°
highlights torsional anisotropy
and cholesteric ordering
• Anisotropy decreases as NaCl
concentration is increased
Towards enabling:
Understanding and control of chiro-nematic ordering
Rational design of security inks
S. R. Stoyanov, O. Lyubimova, S. Gusarov, and A. Kovalenko, (in preparation).
The Plant Cell Wall
• Cellulose is embedded in a matrix of hemicellulose and lignin
• The non-cellulosic compounds are responsible for providing the cohesive forces that stabilize the cell wall structure
Adapted from: Annu. Rev. Chem. Biomol. Eng. (2011) 2, 121-45
Overcoming plant biomass recalcitrance
A molecular model of hemicellulose Hemicellulose is a highly branched heteropolysaccharide
For example, Xylan occurs in sugar cane, corn and other crops
All of the chemical changes in the xylan structure regard the branches, mainly arabinose and glucuronic acid.
Our cell wall model
Two 4-chain cellulose fibrils immersed in a hydrogel of hemicellulose branches, e.g., arabinose and glucuronic acid monomers, which are considered as the solvent for the 3D-RISM-KH calculations
Glucuronic acid
Arabinose
Cellulose fibril
xylose
glucuronic acid
arabinose
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
Effective interactions (PMF): hydrophobic faces
(A) arabinose (B) glucuronic acid (C) glucuronate
Separation of the
hydrophobic faces of
two cellulose fibrils
Different compositions and concentrations of the hemicellulose branches
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
Effective interactions (PMF): hydrophilic faces
Separation of the
hydrophilic faces of two
cellulose fibrils
(A) arabinose
(B) glucuronic acid
(C) glucuronate
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
Cost of deconstructing the cell wall
Hemicellulose has a strong impact on the stability of the cell wall
The kinetic barrier for aggregation decreases as the hemicellulose concentration is increased
Hydrophobic faces Hydrophilic faces
Cellulose + glucuronate
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
Changes in hemicellulose composition affect cell wall stability
Glucuronic acid & glucuronate are mainly responsible for the recalcitrance
Hydrophobic faces Hydrophilic faces
The hemicellulose composition strongly modulates the cell wall recalcitrance
Aggregation Free Energy
Hydrophilic and basic interactions have comparable contributions to recalcitrance
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
Primary alcohol
Glucuronate and acetate bind the H-bond donors on the cellulose surface (primary alcohols)
Site-specific cellulose-hemicellulose interactions
Arabinose and glucuronic acid bind the H-bond acceptors on the cellulose surface (secondary alcohols)
Secondary alcohol
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
)()()(
2
1)(
2
1)( 2
rrrrr γγγγBγγ cchhTkρ=Φ
γ
γΦ=Δμ )(d rr
Large negative SFED
Smaller negative SFED
hydrogen bonds first layer 3D-SFED isosurfaces:
• are highly localized around polar sites on the cellulose microfiber surface
• indicate hemicellulose-cellulose H-bonding
• show diffuse second layer of hemicellulose monomers stacking over cellulose surface
• show weaker stacking interactions in the second layer, less specific than H-bonding
• show stacking due to hydrophobic and enhanced intermolecular C––H……O interactions
Intensity of solute-solvent effective adhesion over 3D spatial regions of the solvation shells
Φγ(r) < 0 - adhesion Φγ(r) > 0 - expulsion
Cellulose-hemicellulose interactions: 3D solvation free energy density
Silveira, R. L.; Stoyanov, S. R.; Gusarov, S.; Skaf, M. S.; Kovalenko, A. J. Am. Chem. Soc. 203, 135, 19048
CONCLUSIONS
Molecular theory of solvation – an essential part of the platform of multiscale modeling
Statistical-mechanical, 3D-RISM-KH molecular theory of solvation
Solvation structure, thermodynamics, electrochemistry, and photochemistry of liquid and
solution systems of a given composition, thermodynamic conditions, and local environment
non-polar and polar solvents, co-solvents, ionic liquids, electrolyte solutions,
solid-liquid interfaces, macro- and supramolecules, biomolecules, ligands, soft matter,
nanoparticles, and nanoporous materials
Kohn-Sham DFT / 3D-RISM-KH for electronic structure, nanochemistry,
and nanocatalysis in solution
Implemented in Amsterdam Density Functional (ADF) computational chemistry package
Multiple time step MD / Optimized isokinetic Nóse-Hoover thermostat / 3D-RISM-KH
for molecular dynamics of biomolecules steered by effective solvation forces
Implemented in Amber Molecular Dynamics package and Amber Tools
Application to various chemical and biomolecular nanosystems and nanobiomaterials.
including:
Adsorption of organic species on clays
Synthetic organic supramolecular nanoarchitectures (rosette nanotubes)
Protein nanostructures (“nanomachines”)
Celulose nanocrystals (CNC) based nanosystems and nanocomposites
Cellulosic biomass pretreatment
FUNDING
• National Research Council (NRC) of Canada
• Natural Sciences and Engineering Research
Council (NSERC)
• Natural Resources Canada (NRCan),
Energy Research and Development,
Clean Energy Fund
• Alberta Innovates Bio Solution
• Alberta Prion Research Institute
• Alberta Innovates Technology Futures
• PrioNet
• Bill and Melinda Gates Foundation
• West Grid – Compute Canada
• NAREGI Supercomputing Project, Japan
• HPC Cluster, Integrated Nanotools Research
Facility, U of Alberta, Canada
• ArboroNano Forest Nanoproducts Network
• Centre for Oil Sands Innovation (COSI)
• Imperial Oil Research
• Ballard Power Systems
• Automotive Fuel Cell Cooperation (AFCC)
• Xerox Research Centre Canada (XRCC)
• AIST – National Institute of Advanced Industrial
Science and Technology, Japan
• MEXT – Ministry of Education, Culture, Sports,
Science, and Technology of Japan
• CAPES – Brazilian Federal Agency for the
Support and Evaluation of Graduate Education
• CNPq – National Council for Scientific and
Technological Development, Brazil
www.cein.ualberta.ca / research / kovalenko
Acknowledgements
COLLABORATORS
• M. Brett (NINT / U of Alberta)
• H. Fenniri (NINT / U of Alberta)
• R. McCreery, (NINT / U of Alberta)
• L. Unsworth (NINT / U of Alberta)
• D. Wishart (NINT / U of Alberta)
• V. Neburchilov (NRC-IFCI)
• G. Lopinski (NRC-SIMS)
• S. Dew (U of Alberta)
• M. Gray (U of Alberta)
• J. Stryker (U of Alberta)
• J. Tushynski (U of Alberta)
• R. Tykwinski (U of Alberta)
• T. Ziegler (U of Calgary)
• G. Patey (U of British Columbia)
• C. Detellier (U of Ottawa)
• D. Case (Rutgers U)
• V. Pande (Stanford U)
• T. Wesolowski (U of Geneva)
• C. Chiappe (U of Pisa)
• Yu. Dmitriev (U of St. Petersburg)
• M. Holovko (ICMP, Natl. Acad. Sci. Ukraine)
• A. Trokhymchuk (ICMP, Natl. Acad. Sci. Ukraine)
• I. Omelyan (ICMP, Natl. Acad. Sci. Ukraine)
• C. Breitkopf (Technical U of Dresden)
• F. Hirata (Insti. for Molecular Science, Ritsumeikan U)
• M. Kinoshita (Kyoto U)
• H. Sato (Kyoto U)
• T. Imai (RIKEN, Japan)
• M. Yoshida (AIST - Nanosystems Research Institute)
• T. Takanohashi (AIST - Energy Research Institute)
• J. W. M. Carneiro (Federal U of Fluminense)
• L. M. Costa (Federal U of Fluminense)
• M. S. Skaf (U of Campinas)
• P. R. Seidl (Federal U of Rio de Janeiro)
• R. Veregin (Xerox Research Centre Canada)
• K. Moffat (Xerox Research Centre Canada)
• MOE, Chemical Computing Group (J. F. Truchon, P. Labute)
• ADF, Scientific Computing and Modeling (S. van Gisbergen)
• MOLCAS (B.Roos, R.Lindt, P.A.Malmquist, V.Veryazov)
• AMBER (D. Case, T. Luchko)
www.cein.ualberta.ca / research / kovalenko
Acknowledgements
Ack
now
ledg
men
ts Sergey Gusarov
Alex Kobryn
Nikolay Blinov
Maria Stepanova
Stan Stoyanov
Piotr Drabik
Kengo Ichiki
Qingbin Li
Lucian Livadaru
Dragan Nilkolic
Kyrylo Tabunshchyk
Takeshi Yamazaki
Yuri Yu Dmitriev
Ihor Omelyan
Andrij Trokhymchuk
Oh, Canada!..
Lyudmyla Dorosh
Wenjuan Huang
Yansen Lauw
Xianjun Liu
Olga Liubimova
Radha K Motkuri
Nataraj S Pagadala
Bhalchandra S Pujari
Andrey Tokarev
Oleksandr Zelyak
Leonardo M da Costa
Seigo Hayaki
Jakub Kaminski
Viktor Leontyev
Siriporn Pansri
Jackeline Oliveira
Rodrigo Silveira
Joshy Yesudas
Daisuke Yokogawa