SLACS-INFM/CNR Sardinian Laboratory for Computational Materials Science www.slacs.it SLACS Atomically informed modeling of the microstructure evolution.

Slides:



Advertisements
Similar presentations
Time averages and ensemble averages
Advertisements

PWI Modelling Meeting – EFDA C. J. OrtizCulham, Sept. 7 th - 8 th, /8 Defect formation and evolution in W under irradiation Christophe J. Ortiz Laboratorio.
1 Discrete models for defects and their motion in crystals A. Carpio, UCM, Spain A. Carpio, UCM, Spain joint work with: L.L. Bonilla,UC3M, Spain L.L. Bonilla,UC3M,
Simulazione di Biomolecole: metodi e applicazioni giorgio colombo
PHYS466 Project Kyoungmin Min, Namjung Kim and Ravi Bhadauria.
Biological fluid mechanics at the micro‐ and nanoscale Lecture 7: Atomistic Modelling Classical Molecular Dynamics Simulations of Driven Systems Anne Tanguy.
Molecular dynamics modeling of thermal and mechanical properties Alejandro Strachan School of Materials Engineering Purdue University
Transfer FAS UAS SAINT-PETERSBURG STATE UNIVERSITY COMPUTATIONAL PHYSICS Introduction Physical basis Molecular dynamics Temperature and thermostat Numerical.
REBOUNDS WITH A RESTITUTION COEFFICIENT LARGER THAN UNITY IN NANOCLUSTER COLLISIONS Hiroto Kuninaka Faculty of Education, Mie Univ. Physics of Granular.
Fixed charge problem of Modified-BMH potential during molecular dynamic simulation of Si/SiO 2 interface 김세진 1,2, 김상필 1,3, 최정혜 1, 이승철 1, 이광렬 1, 김도연 2,
Technion - Israel Institute of Technology
Computational Solid State Physics 計算物性学特論 第2回 2.Interaction between atoms and the lattice properties of crystals.
ICME and Multiscale Modeling
Aging in short-ranged attractive colloids G. Foffi INFM, Universita’ “La Sapienza”, Roma.
Structure of Amorphous Materials
MOLECULAR DYNAMICS SIMULATION OF STRESS INDUCED GRAIN BOUNDARY MIGRATION IN NICKEL Hao Zhang, Mikhail I. Mendelev, David J. Srolovitz Department of Mechanical.
Computer Simulations, Scaling and the Prediction of Nucleation Rates
The Scaling of Nucleation Rates Barbara Hale Physics Department and Cloud and Aerosol Sciences Laboratory University of Missouri – Rolla Rolla, MO
Glass-Like Behavior in General Grain Boundary During Migration
Stress Driven Migration of Flat Grain Boundaries Hao Zhang, Mikhail I. Mendelev and David J. Srolovitz Princeton University.
Joo Chul Yoon with Prof. Scott T. Dunham Electrical Engineering University of Washington Molecular Dynamics Simulations.
Deformation of Nanotubes Yang Xu and Kenny Higa MatSE 385
Density Functional Theory HΨ = EΨ Density Functional Theory HΨ = EΨ E-V curve E 0 V 0 B B’ E-V curve E 0 V 0 B B’ International Travel What we do Why computational?
Molecular Dynamic Simulation of Atomic Scale Intermixing in Co-Al Thin Multilayer Sang-Pil Kim *, Seung-Cheol Lee and Kwang-Ryeol Lee Future Technology.
Energetics and Structural Evolution of Ag Nanoclusters Rouholla Alizadegan (TAM) Weijie Huang (MSE) MSE 485 Atomic Scale Simulation.
Molecular Dynamics Simulation Solid-Liquid Phase Diagram of Argon ZCE 111 Computational Physics Semester Project by Gan Sik Hong (105513) Hwang Hsien Shiung.
A computational study of shear banding in reversible associating polymers J. Billen, J. Stegen +, A.R.C. Baljon San Diego State University + Eindhoven.
Solid state physics Dr. Abeer Kamal Abd El-Aziz 1.
Mesoscale Priority Research Direction Atomistic to Mesoscale Modeling of Material Defects and Interfaces Opportunity Meso Challenge Approach Impact Atomistic-informed.
Molecular Dynamics Study of Solidification in the Aluminum-Silicon System Supervisor: Dr. Jeffrey J Hoyt Peyman Saidi Winter 2013.
Basics of molecular dynamics. Equations of motion for MD simulations The classical MD simulations boil down to numerically integrating Newton’s equations.
Critical Phenomena in Random and Complex Systems Capri September 9-12, 2014 Spin Glass Dynamics at the Mesoscale Samaresh Guchhait* and Raymond L. Orbach**
Atomic Scale Computational Simulation for Nano-materials and Devices: A New Research Tool for Nanotechnology Kwang-Ryeol Lee Future Technology Research.
Defects in Solids 0-D or point defects –vacancies, interstitials, etc. –control mass diffusion 1-D or linear defects –dislocations –control deformation.
Rebecca Cantrell MAE Professor Zabaras Atomistic Modeling of Materials Final Project Presentation May 7, 2007.
8. Selected Applications. Applications of Monte Carlo Method Structural and thermodynamic properties of matter [gas, liquid, solid, polymers, (bio)-macro-
Byeong-Joo Lee cmse.postech.ac.kr Semi-Empirical Atomistic Simulations in Materials Science and Engineering Byeong-Joo Lee Pohang University of Science.
Inelastic Deformation in Shock Loaded PETN Reilly Eason and Thomas D. Sewell Department of Chemistry University of Missouri-Columbia Funded by Defense.
Comparison of Si/SiO x Potentials for Oxidation Behaviors on Si Sang-Pil Kim, Sae-Jin Kim and Kwang-Ryeol Lee Computational Science Center Korea Institute.
Defects in Solids 0-D or point defects –vacancies, interstitials, etc. –control mass diffusion 1-D or linear defects –dislocations –control deformation.
Algorithms and Software for Large-Scale Simulation of Reactive Systems _______________________________ Metin Aktulga, Sagar Pandit, Alejandro Strachan,
Meta-stable Sites in Amorphous Carbon Generated by Rapid Quenching of Liquid Diamond Seung-Hyeob Lee, Seung-Cheol Lee, Kwang-Ryeol Lee, Kyu-Hwan Lee, and.
Molecular Modelling - Lecture 2 Techniques for Conformational Sampling Uses CHARMM force field Written in C++
Mesoscale Priority Research Direction Microstructure Based Heterogeneity Evolution Leading to Phase Transformation and Damage/Failure Events Meso-Scale.
F. Sacconi, M. Povolotskyi, A. Di Carlo, P. Lugli University of Rome “Tor Vergata”, Rome, Italy M. Städele Infineon Technologies AG, Munich, Germany Full-band.
NIRT: Reduced Degree of Freedom Predictive Methods for Control & Design of Interfaces in Nanofeatured Systems D.W. Brenner, M. Buongiorno-Nardelli, G.
Javier Junquera Introduction to atomistic simulation methods in condensed matter Alberto García Pablo Ordejón.
CAREER: Microstructure & Size Effects on Metal Plasticity at Limited Length Scale Frederic Sansoz, University of Vermont, DMR Animated snapshots.
Peak effect in Superconductors - Experimental aspects G. Ravikumar Technical Physics & Prototype Engineering Division, Bhabha Atomic Research Centre, Mumbai.
Lecture 20: The mechanism of plastic deformation PHYS 430/603 material Laszlo Takacs UMBC Department of Physics.
Molecular Dynamics Simulations and the Importance of
Modelling of the motion of phase interfaces; coupling of thermodynamics and kinetics John Ågren Dept of Materials Science and Engineering Royal Institute.
Korea Institute of Science and Technology Seung-Hyeob Lee, Churl-Seung Lee, Seung-Cheol Lee, Kyu-Hwan Lee, and Kwang-Ryeol Lee Future Technology Research.
Shruthi Kubatur Prof. Mary L. Comer
© 2009 Al-Abdallat Properties of Eng. Material 1 (3) Interfacial defects Interfacial defects: Types: External surfaces, Grain boundaries, Twin boundaries.
Fracture Toughness of Metallic Glasses: A Ductile-to-Brittle Transition? Eran Bouchbinder Weizmann Institute of Science Work with Chris H. Rycroft University.
Plastic deformation Extension of solid under stress becomes
Comp. Mat. Science School Electrons in Materials Density Functional Theory Richard M. Martin Electron density in La 2 CuO 4 - difference from sum.
1 Nanoscale Modeling and Computational Infrastructure ___________________________ Ananth Grama Professor of Computer Science, Associate Director, PRISM.
1 LECTURE 1 M. I. Baskes Mississippi State University University of California, San Diego and Los Alamos National Laboratory.
Multiscale Modelling of Nanostructures on Surfaces
Sanghamitra Mukhopadhyay Peter. V. Sushko and Alexander L. Shluger
Molecular Dynamics Study on Deposition Behaviors of Au Nanocluster on Substrates of Different Orientation S.-C. Leea, K.-R. Leea, K.-H. Leea, J.-G. Leea,
Atomistic simulations of contact physics Alejandro Strachan Materials Engineering PRISM, Fall 2007.
Atomistic materials simulations at The DoE NNSA/PSAAP PRISM Center
Prof. Sanjay. V. Khare Department of Physics and Astronomy,
Kinetic Monte Carlo Simulation of Epitaxial Growth
Instructor: Yuntian Zhu
Molecular Dynamics(MD)
Multiscale Modeling and Simulation of Nanoengineering:
Presentation transcript:

SLACS-INFM/CNR Sardinian Laboratory for Computational Materials Science SLACS Atomically informed modeling of the microstructure evolution of nanocrystalline materials A. Mattoni

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS SLACS CNR-INFM CRS LN LR Regional Laboratories Atomistic investigation: large scale molecular dynamics simulations Large scale electronic structure calculations Continuum modeling: models for growth, interface mobilities Division: Material Physics (Microstructure evolution of nanostructured materials) (6 members,

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS OUTLINE The microstructure of interest for nanocrystalline materials Boundaries between order/disordered phase The theoretical framework Molecular dynamics atomistic simulations Modeling the growth of nanocrstals embedded into an amorphous matrix

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Molecular dynamics The material of interest is described as an assembly of molecular constituents

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Molecular dynamics An interatomic depending on atomic positions The interatomic forces are calculated accordingly Newton’s equations of motion are integrated numerically (“Verlet velocity”) Choose dt “judiciously” (~1fs) and iterate in time (“ad nauseam”)

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Interatomic potentials ”6-12” Lennard-Jones potential: repulsive core 1/r 12 ; VdW attraction 1/r 6 r>r eq ”6-12” Lennard-Jones potential: prototypical interatomic force model for close-packed metals Professor Sir John Lennard-Jones (FRS), one of the founding fathers of molecular orbital theory

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Interatomic potentials Stillinger-Weber potential for anysotropic covalent bonding (1985) F. Stillinger Department of Chemistry Princeton University Princeton, NJ T.A. Weber (EDIP) Environment dependent interatomic potential (1998)

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS MD comes of age… K. Kadau et al. Int. Journal of Modern Physics C (2006) B. J. Alder and T. E. Wainwright, J. Chem. Phys.27,1208(1957) Stillinger-Weber Lennard-Jones Tersoff EDIP 320 BILLION ATOM SIMULATION ON BlueGene/L Los Alamos National Laboratory

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS MD comes of age… more or less Compromise between accuracy and computational workload The bottleneck of standard molecular dynamics: time and length scales In order to properly reproduce fracture related properties of covalent materials of group IV materials (Si, Ge, C) it is necessary to take into account interactions as long as the second nearest neighbors distance A. Mattoni, M. Ippolito and L. Colombo, B 76, (2007) Reliability of the model potentials

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Computational Effort CMPTool: a set of highly efficient parallel numerical libraries for computational materials science developed in collaboration with Caspur, Rome Group of materials science (M. Rosati, S. Meloni, L. Ferraro, M. Ippolito) Typical simulation parameters number of atoms > 10 5 Runs as long as iterations (6 ns) 1ns annealing of atoms requires of the order of 1000 CPU hours on state-of-the-art AMD - Opteron Dual core Linux cluster A. Mattoni et al. Comp. Mat. Sci (2004) S. Meloni et al. Comp. Phys. Comm (2005)

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Nanocrystalline materials Crystalline materials 0-D Points: I,V, clusters, dots Lines: Dislocations 1-D Interfaces: Grain boundaries 2-D 3-D Amorphous materials In the amorphous phase (isotropic) the concept of dislocation is lost The microstructure evolution is controlled by: Recrystallization, normal grain growth Plastically deformed materials Ion implantation

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Mixed phase nanocrystalline systems Nanocrystalline materials (nc-Si) may be prepared through the crystallization of amorphous (disordered) nc grains are embedded into a second phase matrix Experimentally it is found that the smallest grain size is obtained when the amorphous samples are annealed at a crystallization temperature that is close to half the bulk melting temperature Q. Jiang, J. Phys.: Condens. Matter 13 (2001) 5503– 5506 nc Embedding amorphous matrix

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Nc-Si for photovoltaics Nano-crystalline silicon (nc-Si) consists in a distribution of grains embedded into an amorphous matrix Observation of domains separated by amorphous boundaries and (in some cases texturing) Bright field TEM micrograph S. Pizzini et al.Mat. Sci. Eng. B 134 p. 118 (2006)

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Modeling the a-/nc- evolution During annealing of amorphous bulk it is difficult to deconvolve nucleation from growth (impurities, control the temperatures, grains impingement) C. Spinella et al. J. Appl. Phys (1998) Atomistic simulation as a tool to perform numerical experiment under perfectly controlled conditions of temperature and purity What is the equation of motion of an isolated a-c boundary (planar or curved)? Silicon as a prototype of a covalently bonded material Mattoni and Colombo, Phys. Rev. Lett. 99, (2007)

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Why does a grain grow? a-Si/c-Si is a metastable system M. G. Grimaldi et al. Phys. Rev. B (1991) ~ 0.1 eV/atom 1 kJ/mole= eV/atom

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Driving force p a-c Driving force : specific free-energy difference

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Equation of motion Transition state theoryInterface limited growth Equation of motion of the a-c displacement a-Si c-Si

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Transition State Theory a-Si c-Si

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Curved a-c boundary The capillarity is expected to be sizeable up to R~R * and there give rise to an Accelerated -> uniform growth In silicon R * < 1 nm

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Planar a-c boundary Uniform motion: the a-c velocity is constant A. Mattoni et al. EPL (2003) Exponential dependence on T with E b =2.6eV EXP G. L. Olson Mater Sci. Rep. 3, (1988) AS N. Bernstein et al. PRB (2000 )

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Curved a-c boundary c-Si/a-Si: Isolated Crystalline fiber embedded into the amorphous phase nc-Si/a-Si: Crystalline fiber embedded into an amorphous phase [1 0 0] case

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Characterization of the a-nc system

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Structure Factor T/T m amorphous

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Analysis

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Crystallinity Crystallinity of a mixed a-Si/nc-Si: relative number of crystalline atoms

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Fiber recrystallization

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Power law model Power law model the model describes both decreasing and increasing nonuniform growth

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Fiber recrystallization

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Fiber recrystallization There is a dependence of the growth exponents on temperature and there is a clear transition close to the amorphous melting

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Fiber recrystallization

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Fiber recrystallization

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Characterization of defects

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS A simple explanation

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Conclusions Molecular dynamics simulation are emerging as a powerfool tool to help the characterization of the microstructure evolution of nanostructured materialsMolecular dynamics simulation are emerging as a powerfool tool to help the characterization of the microstructure evolution of nanostructured materials An atomically informed continuum model is found to describe recrystallization in both the cases of isolated grain and distribution of grainsAn atomically informed continuum model is found to describe recrystallization in both the cases of isolated grain and distribution of grains Contact: EU-STREP “NANOPHOTO” CASPUR-ROME and CINECA-BOLOGNA computational support A. Mattoni and L. Colombo, Phys. Rev. Lett. 99, (2007) M. Fanfoni and M. Tomellini, Phys. Rev. B 54, 9828 (1996) C. Spinella et al. J. Appl. Phys (1998)

SLACS-INFM/CNR Rome, December 13, 2007 MATHEMATICAL MODELS FOR DISLOCATIONS Recrystallization