Theoretical and Computational Materials Science

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Nov 15, 2013 (3 years and 6 months ago)

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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+PV-TS=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