Title: Lattice, Quasi-continuum
1 Lattice, Quasi-continuum Phase
Transitions
Department of Aerospace Engineering and
Mechanics, University of Minnesota
2Acknowledgements
- Ellad B. Tadmor, University of Minnesota,
Aerospace Engineering and Mechanics - Ryan Elliot, University of Minnesota, Aerospace
Engineering and Mechanics - Emil Polturak, Physics Department, Technion
- Joan Adler, Physics Department, Technion
- Noam Bernstein, Center for Computational
Materials Science and Technology
Division Naval Research Laboratory Washington - Gábor Csányi, University of Cambridge,
Engineering Laboratory - Mitchell Luskin, University of Minnesota, School
of Mathematics - David Ceperley, National Center for
Supercomputing Applications at Illinois - Matteo Cococcioni, University of Minnesota,
Chemical Engineering and Materials Science - David Landau, UGA Physics and Astronomy School
3Part I Multi-scale modelling of materials
- The object of multi-scale modelling is to predict
behaviour of materials using theoretical and
computational techniques that link across spatial
and temporal scales. - This approach can be considered as an alternative
to the empirical methods of today. It offers
great opportunities for tomorrow technological
advances.
The series of images shows details of the crack
tip at the different scales. The atomic-scale
mechanism leads to fracture can be seen. This
picture compliments of the Naval Research Lab
Washington, DC
4Quasicontinuum (QC) method
- The QC method is one of the best possible
strategies devised to couple concurrently micro
and macro scales. - This techniques is a mixed continuum and
atomistic approach for simulating the mechanical
response of crystalline materials. With QC one
can reproduce the results of full atomistic
calculation at a fraction of computational cost.
A crack tip approaching a grain boundary in a
nickel bi-crystal. For frames are shown at
increasing level of external load. The snapshots
show dislocation emission from the grain
boundary, followed by crack extension, and,
finally, grain boundary migration toward the
crack tip. Taken from www.qcmethod.com
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6Quasicontinuum method
- The energies of the 'representative' atoms are
calculated based on their environment either by
using atomistic methodology, or as befitting to
a continuum model. The total energy is
calculated without any assumptions beyond the
form of inter-atomic potentials. - With a knowledge of the total energy one can
study mechanical response of crystalline material
to external load. This can be done by minimizing
the total energy with respect to the
displacements of the 'representative' atoms. - Currently, one of the most important direction
for our research is to extend the QC method from
simple to complex lattices.
7Complex lattices
- The extension of the QC method to complex
lattices permits the study of many
technologically important materials such as
semiconductors, ferroelectrics, and shape-memory
materials. - Unit cell of complex lattices contains more than
one basis atom per Bravais lattice site. In
general, complex lattice can be described as a
set of inter-penetrating sub-lattices with the
same lattice vectors, but different origin
positions.
Adapted from http//www.molecularexpression.com
8Complex Lattices
- When a uniform macroscopic deformation is
applied, all the sub-lattices undergo the same
uniform deformation, but in addition they can
slide relative each other. Therefore, to describe
complex lattices we increase the number of
degrees of freedom to include sub-lattice
displacements into account. - The equilibrium configuration is now obtained by
minimizing the total energy with respect to the
node and sub-lattice displacements concurrently.
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10Uni-axial Stress
- To test the new approach we applied uniaxial
stress to the NiTi crystal with a cubic lattice
structure. An essential unit cell containing two
basis atoms was initially chosen. - The external load was gradually incremented until
the first phonon instability was detected. At
this point the two basis atom unit cell was
replaced by a four basis atom unit cell. The
subsequent minimization led to a drastic increase
in the nominal strain new stable a-IrV phase
was identified. The old approach failed to
reproduce the proper transition. - This simple test illustrates necessity of
flexible description of the underlying lattice
for correct modelling of solid-to-solid
transformations.
11Application
- Using the extended QC method we study properties
of NiTi shape-memory alloy. The shape memory
alloy 'remembers' its shape it can be returned
to that shape after being deformed, by applying
heat to the alloy. - The shape-memory effect is due to
temperature-dependent phase transformation from a
low-symmetry martensite to a high-symmetry
austenite. - In order to validate the capability of the QC
method to reproduce the shape memory effect we
decided to simulate the shape memory cycle
cooling deformation - heating.
http//everythang.wordpress.com
12Shape memory cycle
- Elliot's temperature dependent potentials were
used to model the prototypical NiTi alloy. A two
basis atom unit cell was used to describe the
initial austenite structure of the alloy. - At the first stage temperature of the sample was
gradually reduced. At each step the energy
minimization was accompanied by phonon stability
analysis. - When the temperature reached the critical value
T/Tref 0.667, the phonon instability was
detected, and the unit cell was extended to
include four basis atoms. The subsequent
minimization led to the transformation from the
austenite phase to the martensite phase. This
martensite phase contained both left (blue color)
and right (red color) oriented variants.
(a) Austenite structure of the sample at T/Tref
0.8 (b) Sample is cooled down to T/Tref 0.667
13Shape memory cycle
- Next, we sheared the sample by displacing the
top row nodes to the right. The sample
temperature was kept constant T/Tref 0.65 at
this stage. - As the shear progressed all left-oriented
martensite elements reversed their orientation.
The process started at the bottom and propagated
upward. The simulation was terminated when all
elements are right-oriented. - Finally, we heated up the sample to T/Tref 1.1
at this temperature a reverse martensite-to-auste
nite transformation occurred and the original
shape of the sample was recovered. - In conclusion, we demonstrated the capability of
the extended QC method to simulate shape-memory
cycle.
(c) The sample is deformed at T/Tref 0.65 (d)
The sample is heated up to T/Tref 1.1 and then
cooled down to T/Tref 0.8
14Part II Mechanical Melting
- Melting is a fundamental process, but despite
its common occurrence, understanding this process
is still a challenge. - Over the years, several theories explaining the
mechanism of melting have been proposed. This
research has evolved to a state where two
possible scenarios exist the first scenario of
mechanical melting resulting from lattice
instability, and the second scenario of
thermodynamic melting which begins at a free
surface or at an internal interface (grain
boundary, void).
15Mechanical Melting
- Mechanical melting occurs when the crystal loses
its ability to resist shear. This rigidity
catastrophe is caused by vanishing one of the
elastic shear moduli. At this point the crystal
expands up to a critical specific volume, which
is close to that of the melt. This condition
determines the mechanical melting temperature Ts
of a bulk crystal as it was confirmed in
extensive studies of FCC metals. - The critical volume at which FCC metals melt is
independent of the path through phase space by
which it is reached whether one heats the
perfect crystal or adds point defects to expand
the solid at a constant temperature. - Our aim was to verify whether this scenario of
mechanical melting developed for FCC crystals is
also applicable to crystals with BCC lattice
structure.
16Method and Model
- Mechanical melting transition of vanadium was
modeled using molecular dynamics (MD)
simulations. - Since we are interested in the generic features
of metallic solids with a BCC structure, the
choice of vanadium has no special significance. - The many-body interaction potential developed by
Finnis and Sinclair (FS) was chosen to simulate
vanadium
http//www.neyco.fr/images/vanadium.jpg
17Geometry and Boundary Conditions
- The samples used for the simulations contained
2000 atoms, initially arranged as a perfect BCC
crystal. - We introduced point defects to the samples either
by insertion of extra atoms (self
interstitials) or by removal of atoms from the
lattice (vacancies). - Since solids can undergo mechanical melting only
if they have no free surfaces, periodic boundary
conditions were applied in all three directions.
18Melting Transition
- We carried out our simulations using samples with
various concentrations of point defects. - The initial temperature was chosen far below the
expected melting point. The samples were
gradually heated, and at some point we observed
an abrupt decrease of the order parameter,
together with a simultaneous increase of the
specific volume and the total energy. - This event determined the mechanical melting
temperature, Ts 2500 K.
19Results
- We found that once point defects are introduced,
the melting temperature becomes a function of
their concentration, which has been confirmed
experimentally. - Using the dependency of shear modulus C' (C11
C12)/2 on specific volume we extracted the value
of the critical volume at which the system
melts. - Our results show that the Born model of melting
applies equally to BCC and FCC metals in both
the nominally perfect state and in the case where
point defects are present.
20Part III Thermodynamic melting
21Thermodynamic melting
- The mechanical melting transition cannot be
observed in the laboratory since it is preempted
by the thermodynamic melting transition. Long
before the melting temperature is reached a thin
quasiliquid layer appears at the free surface.
Numerous experiments and computer simulations
confirm that FCC metals start to melt from the
surface. - Our primary motivation was to answer the question
whether premelting phenomena, extensively studied
for FCC metals, are also present in BCC metals.
In addition, our goal was to calculate the
thermodynamic melting temperature, since
the temperature Ts 2500 K at which mechanical
melting occurs is far above the experimental
value Tm 2183K.
22Simulation details
- We modelled the thermodynamic melting transition
of vanadium with a free surface using MD
simulations in canonical ensemble. The same FS
many-body potential was applied for vanadium. - A crystal with a surface was modelled as a thick
slab with the fixed bottom layers to mimic the
presence of the infinite bulk. On top of those
layers there were 24 layers in which atoms are
free to move. Periodic boundary conditions were
imposed along the in-plane (x and y) directions.
23Simulation Details
- Three different samples with various low-index
surfaces were constructed V(001), V(011) and
V(111). All the samples contained about 3000
atoms initially arranged a perfect BCC crystal. - Each simulations started from a low-temperature
solid, and then the temperature was gradually
raised up to a specific value. At this
temperature the samples were equilibrated. - The structural, transport, and energetic
properties were measured in the thermal
equilibrium at various temperatures up to the
melting point.
24Results
- We found that the surface region of the
least-packed V(111) surface began to disorder
first via generation of defect pairs and the
formation of an additional layer at temperature
above T 1000 K. At higher temperatures, the
surface region became quasiliquid. - This process began above T 1600 K for the
V(001) surface. - For the closest-packed V(011), this effects was
observed only in the close proximity to the
melting temperature.
25Results
- We determined the thermodynamic melting
temperature of vanadium as Tm 2220 K, in a
good agreement with experimental value Tm 2183
K. - The results of our simulations of surface
premelting of the BCC metal, vanadium, are
similar to the results obtained for various FCC
metals, in the sense that the onset of disorder
is seen first at the surface with the lowest
density.
26The End
- For help on the Israel Inter-University
Computation Center supercomputers thanks to Dr.
Moshe Goldberg, Dr. Anne Weill, Gabi Koren and
Jonathan Tal - For help on the Minnesota Supercomputing
Institute machines thanks to Dr. Haoyu Yu, Dr.
Shuxia Zhang and Dr. Benjamin Lynch.