Transcript Mechanical properties of nanocrystalline materials

TETY
Theoretical and Computational Materials Science
Materials Theory
Photonic, Phononic
and Meta- Materials
C. Soukoulis
I. Remediakis
G. Kopidakis
M. Kafesaki
(to be
appointed)
Materials Theory Group (est. 2007)
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.
Training
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.
From atomistic Simulations Electronic Structure Theory...
Empirical Force Fields plus Classical Monte-Carlo and Molecular
Dynamics Simulations.
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Quantum mechanical simulations (Tight-binding / LCAO).
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Ab initio simulations (Density-functional Theory - DFT).
Variety of home-made, commercial and open-source codes running
on a Beowulf cluster of ~60 nodes.
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… to computer-aided Design of new
Materials
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Surface chemistry and catalysis.
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Carbon-based materials and other superhard ceramics.
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Quantum dots, nanocrystals, nanowires.
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Non-linear dynamics, energy localization and transfer.
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All-optical signal processing and firewalls.
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Hydrogen storage.
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 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 = Gb u l k + Σ γh k l Ah k l
(Gibbs, 1878)
Equilibrium shape: minerals (billions of years to equilibrate) or
nanopart icles (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).
E=0.000
Si quantum dots in a-SiO2
E=0.010
E=0.010
Red : {100} Blue : {110}
Green : {121}
G. Hadjisavvas, I. N. Remediakis, P.
C. Kelires, Phys. Rev. B 74, 165419
(2006);
E=0.010 E=0.061
E=0.005
E=0.050
On-going collaboration with R.
Kalia and P. Vashishta, USC.
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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).
Au nanoparticles in CO gas
G. D. Barmparis & I. N. Remediakis, in preparation.
TETY
Theoretical and Computational Materials Science
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
Diamond, a-D
Density
sp3 fraction
3.24 g/cm3
88%
2.91 g/cm3
71%
2.58 g/cm3
51%
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
Optical transmission rates at
hundreds Gb/s
IP / Ethernet
core
Core routers
Metro ring
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
Control signal
Optical firewall
Suspect
packet
Optical Optical
routing
bit
switch
filter
Optical buffer
memory
Optical routing
switch
Intercept
Pattern
matching
circuit
Router
Incoming data
Optical
Domain
Firmware
Interface
Electronic
Domain
SAP
Interface
http://www.ist-wisdom.org/
General Purpose Processor
External Collaborators
S. Aubry
Saclay, France
M. Johansson
Linkoping, Sweden
K-M. Ho
C-Z. Wang
Ames, USA
P. Kelires
Lemessos, Cyprus
J.K. Norskov
Stanford, USA
H. Hakkinen
K. Honkala
Jyvaskyla, Finland
http://theory.materials.uoc.gr
TETY
Theoretical and Computational Materials Science
http://theory.materials.uoc.gr
http://theory.materials.uoc.gr
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