Theoretical and Computational Materials Science
TETY
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+PVTS=f(
R
1
,
R
2
, ...,
R
N
; 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 different
Gold 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 = G
b u l k
+
Σ
γ
h k l
A
h 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 NH
3
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

SiO
2
E=0.000
E=0.010
E=0.010
E=0.010
E=0.005
E=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 Science
TETY
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, BECs
Results 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 dynamics
More efficient than first principles, more accurate than empirical potential
calculations
•
Atomic structure, mechanical, electronic, optical properties
Mathioudakis, GK, Kelires, Wang, Ho
PRB 2004
Amorphous and nanostructured carbon
Accurate calculation of imaginary part
of 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 sp
3
fraction
3.24 g/cm
3
88%
2.91 g/cm
3
71%
2.58 g/cm
3
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, GK
PSS
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
Intercept
Optical buffer
memory
Optical
routi ng
switch
Suspect
packet
Firmware
Interface
Optical
Domain
Electronic
Domain
SAP
Interface
General Purpose Processor
Pattern
matching
circuit
Optical routing
switch
Optical
bit
filter
Incoming data
Control signal
Router
Intercept
Optical buffer
memory
Optical
routi ng
switch
Suspect
packet
Firmware
Interface
Optical
Domain
Electronic
Domain
SAP
Interface
General Purpose Processor
Core routers
Metro ring
IP / Ethernet
core
Optical firewall
Optical transmission rates at
hundreds Gb/s
Electronic processors at a few
Gb/s
Bridge the gap by
successfully 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, USA
C

Z. Wang
P. Kelires Lemessos, Cyprus
J.K. Norskov Stanford, USA
H. Hakkinen Jyvaskyla, Finland
K. Honkala
http://theory.materials.uoc.gr
http://theory.materials.uoc.gr
27
Theoretical and Computational Materials Science
TETY
http://theory.materials.uoc.gr
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