Atomistic Models to Study Thermodynamics and Kinetics of Solid-Liquid and Solid-Solid Transitions in Binary Metals

Design of novel materials and novel manufacturing process requires understandingthermophysical properties of materials during their process and working conditions.Microstructure of materials, which is usually, consists of grains, phases, and defectsdetermines the overall physical and mechanical properties of materials. Specifically inmetals, the formation of solid crystal from liquid is considered as one of the most importantfactors during the solidification, which can elucidate the final formation of microstructureof materials. The experimental study of the phenomena related to the coexistence of solidliquid phases is generally arduous, because the experiments are needed to be carried out atthe melting points of the materials. Thanks to recent improvements in computational powerand supercomputing capabilities, many research and industrial institutions have started toemploy computational materials modeling as a suitable alternative to costly and/orimpractical experiments. Molecular dynamic (MD) is a powerful computational approachthat can be used for tracking individual atoms with great accuracy in length scales of tensto hundreds nanometers and timescales of picoseconds to nanoseconds. However, thereliability of MD simulations for each alloy system is based on the reliability of how theatoms talk or interact with each other, through the interatomic potential energy.Interatomic potentials, which are mathematical functions of the coordinates of all atoms inthe system, are essential for determining both equilibrium and non-equilibrium propertiesof materials. The objective of this work is to develop advanced interatomic potentials inthe concept of modified embedded-atom method (MEAM) for alloy system that are capableof predictive modeling of alloys in solid-liquid transitions. Interatomic potentials includingMEAM contain parameters that are determined by fitting model predictions to specificexperimental or first principle data, which are mostly to the 0-K properties. In order tostudy the liquid and solid properties at high and the near melting point, the potential has tobe fitted to the not only 0-K properties but also to the high temperature properties such asmelting point and elastic constants at high temperatures. Therefore, our goal in this thesis,is calculating the thermodynamics and kinetics properties of solid and liquid in metallicsystem at high temperatures by MD simulation through developing reliable interatomicpotential for studying pure Fe, Cu, Ni, Ti, Pb, and Sn and binary system (Pb-Sn)

The MOLDY short-range molecular dynamics package

We describe a parallelised version of the MOLDY molecular dynamics program. This Fortran code is aimed at systems which may be described by short-range potentials and specifically those which may be addressed with the embedded atom method. This includes a wide range of transition metals and alloys. MOLDY provides a range of options in terms of the molecular dynamics ensemble used and the boundary conditions which may be applied. A number of standard potentials are provided, and the modular structure of the code allows new potentials to be added easily. The code is parallelised using OpenMP and can therefore be run on shared memory systems, including modern multicore processors. Particular attention is paid to the updates required in the main force loop, where synchronisation is often required in OpenMP implementations of molecular dynamics. We examine the performance of the parallel code in detail and give some examples of applications to realistic problems, including the dynamic compression of copper and carbon migration in an iron-carbon alloy

Computational characterization and prediction of metal-organic framework properties

In this introductory review, we give an overview of the computational chemistry methods commonly used in the field of metal-organic frameworks (MOFs), to describe or predict the structures themselves and characterize their various properties, either at the quantum chemical level or through classical molecular simulation. We discuss the methods for the prediction of crystal structures, geometrical properties and large-scale screening of hypothetical MOFs, as well as their thermal and mechanical properties. A separate section deals with the simulation of adsorption of fluids and fluid mixtures in MOFs

Simulations of the inelastic response of silicon to shock compression

Recent experiments employing nanosecond white-light X-ray diffraction have demonstrated a complex response of pure, single crystal silicon to shock compression on ultra-fast timescales. We present here details of a Lagrangian code which tracks both longitudinal and transverse strains, and successfully reproduces the experimental response by incorporating a model of the shock-induced, yet kinetically inhibited, phase transition. This model is also shown to reproduce results of classical molecular dynamics simulations of shock compressed silicon

Mechanical models of proteins

textIn general, this dissertation is concerned with modeling of mechanical behavior of protein molecules. In particular, we focus on coarse-grained models, which bridge the gap in time and length scale between the atomistic simulation and biological processes. The dissertation presents three independent studies involving such models. The first study is concerned with a rigorous coarse-graining method for dynamics of linear systems. In this method, as usual, the conformational space of the original atomistic system is divided into master and slave degrees of freedom. Under the assumption that the characteristic timescales of the masters are slower than those of the slaves, the method results in Langevin-type equations of motion governed by an effective potential of mean force. In addition, coarse-graining introduces hydrodynamic-like coupling among the masters as well as non-trivial inertial effects. Application of our method to the long-timescale part of the relaxation spectra of proteins shows that such dynamic coupling is essential for reproducing their relaxation rates and modes. The second study is concerned with calibration of elastic network models based on the so-called B-factors, obtained from x-ray crystallographic measurements. We show that a proper calibration procedure must account for rigid-body motion and constraints imposed by the crystalline environment on the protein. These fundamental aspects of protein dynamics in crystals are often ignored in currently used elastic network models, leading to potentially erroneous network parameters. We develop an elastic network model that properly takes rigid-body motion and crystalline constraints into account. This model reveals that B-factors are dominated by rigid-body motion rather than deformation, and therefore B-factors are poorly suited for identifying elastic properties of protein molecules. Furthermore, it turns out that B-factors for a benchmark set of three hundred and thirty protein molecules can be well approximated by assuming that the protein molecules are rigid. The third study is concerned with the polymer mediated interaction between two planar surfaces. In particular, we consider the case where a thin polymer layer bridges two parallel plates. We consider two models of monodisperse and polydisperse for the polymer layer and obtain an analytical expression for the force-distance relationship of the two plates.Engineering Mechanic

Multiscale Modelling of Molecules and Continuum Mechanics Using Bridging Scale Method

his PhD dissertation is about developing a multiscale methodology for coupling two different time/length scales in order to improve properties of new space materials. Since the traditional continuum mechanics models cannot describe the influence of the nanostructured upon the mechanical properties of materials and full atomistic description is still computationally too expensive, millions of degrees of freedom are needed just for modeling few hundred cubic nanometers, this leads to a coupled system of equations of finite element (FE) in continuum and molecular dynamics (MD) in atomistic domain. Coupling efficiently and accurately two dissimilar domains presents challenges especially in handshaking area where the two domains interact and transfer information. The objective of this study is (i) develop a novel nodal position FE method that can couple with the MD easily, (ii) develop a proper methodology to couple the FE with MD for FE/MD multi-scale modeling and let the information transfer in a seamless manner between the two domains, and (iii) implement complicated cases to confirm accuracy and validity of the proposed model

Multi-Scale Modeling of Mechanical and Electrochemical Properties of 1D and 2D Nanomaterials, Application in Battery Energy Storage Systems

Material properties play a critical role in durable products manufacturing. Estimation of the precise characteristics in different scales requires complex and expensive experimental measurements. Potentially, computational methods can provide a platform to determine the fundamental properties before the final experiment. Multi-scale computational modeling leads to the modeling of the various time, and length scales include nano, micro, meso, and macro scales. These scales can be modeled separately or in correlation with coarser scales. Depend on the interested scales modeling, the right selection of multi-scale methods leads to reliable results and affordable computational cost. The present dissertation deals with the problems in various length and time scales using computational methods include density functional theory (DFT), molecular mechanics (MM), molecular dynamics (MD), and finite element (FE) methods. Physical and chemical interactions in lower scales determine the coarser scale properties. Particles interaction modeling and exploring fundamental properties are significant challenges of computational science. Downscale modelings need more computational effort due to a large number of interacted atoms/particles. To deal with this problem and bring up a fine-scale (nano) as a coarse-scale (macro) problem, we extended an atomic-continuum framework. The discrete atomic models solve as a continuum problem using the computationally efficient FE method. MM or force field method based on a set of assumptions approximates a solution on the atomic scale. In this method, atoms and bonds model as a harmonic oscillator with a system of mass and springs. The negative gradient of the potential energy equal to the forces on each atom. In this way, each bond's total potential energy includes bonded, and non-bonded energies are simulated as equivalent structural strain energies. Finally, the chemical nature of the atomic bond is modeled as a piezoelectric beam element that solves by the FE method. Exploring novel materials with unique properties is a demand for various industrial applications. During the last decade, many two-dimensional (2D) materials have been synthesized and shown outstanding properties. Investigation of the probable defects during the formation/fabrication process and studying their strength under severe service life are the critical tasks to explore performance prospects. We studied various defects include nano crack, notch, and point vacancy (Stone-Wales defect) defects employing MD analysis. Classical MD has been used to simulate a considerable amount of molecules at micro-, and meso- scales. Pristine and defective nanosheet structures considered under the uniaxial tensile loading at various temperatures using open-source LAMMPS codes. The results were visualized with the open-source software of OVITO and VMD. Quantum based first principle calculations have been conducting at electronic scales and known as the most accurate Ab initio methods. However, they are computationally expensive to apply for large systems. We used density functional theory (DFT) to estimate the mechanical and electrochemical response of the 2D materials. Many-body Schrödinger's equation describes the motion and interactions of the solid-state particles. Solid describes as a system of positive nuclei and negative electrons, all electromagnetically interacting with each other, where the wave function theory describes the quantum state of the set of particles. However, dealing with the 3N coordinates of the electrons, nuclei, and N coordinates of the electrons spin components makes the governing equation unsolvable for just a few interacted atoms. Some assumptions and theories like Born Oppenheimer and Hartree-Fock mean-field and Hohenberg-Kohn theories are needed to treat with this equation. First, Born Oppenheimer approximation reduces it to the only electronic coordinates. Then Kohn and Sham, based on Hartree-Fock and Hohenberg-Kohn theories, assumed an equivalent fictitious non-interacting electrons system as an electron density functional such that their ground state energies are equal to a set of interacting electrons. Exchange-correlation energy functionals are responsible for satisfying the equivalency between both systems. The exact form of the exchange-correlation functional is not known. However, there are widely used methods to derive functionals like local density approximation (LDA), Generalized gradient approximation (GGA), and hybrid functionals (e.g., B3LYP). In our study, DFT performed using VASP codes within the GGA/PBE approximation, and visualization/post-processing of the results realized via open-source software of VESTA. The extensive DFT calculations are conducted 2D nanomaterials prospects as anode/cathode electrode materials for batteries. Metal-ion batteries' performance strongly depends on the design of novel electrode material. Two-dimensional (2D) materials have developed a remarkable interest in using as an electrode in battery cells due to their excellent properties. Desirable battery energy storage systems (BESS) must satisfy the high energy density, safe operation, and efficient production costs. Batteries have been using in electronic devices and provide a solution to the environmental issues and store the discontinuous energies generated from renewable wind or solar power plants. Therefore, exploring optimal electrode materials can improve storage capacity and charging/discharging rates, leading to the design of advanced batteries. Our results in multiple scales highlight not only the proposed and employed methods' efficiencies but also promising prospect of recently synthesized nanomaterials and their applications as an anode material. In this way, first, a novel approach developed for the modeling of the 1D nanotube as a continuum piezoelectric beam element. The results converged and matched closely with those from experiments and other more complex models. Then mechanical properties of nanosheets estimated and the failure mechanisms results provide a useful guide for further use in prospect applications. Our results indicated a comprehensive and useful vision concerning the mechanical properties of nanosheets with/without defects. Finally, mechanical and electrochemical properties of the several 2D nanomaterials are explored for the first time—their application performance as an anode material illustrates high potentials in manufacturing super-stretchable and ultrahigh-capacity battery energy storage systems (BESS). Our results exhibited better performance in comparison to the available commercial anode materials

The interactions between gold nanoparticles and their self-assembly

Gold nanoparticles (AuNPs) are one of the most promising building blocks to fabricate versatile nanostructures. Such nanostructures have the great potential to enable new gold-based nanomaterials or nanocomposites with specific properties by precisely controlling the interactions (potential energies and/or forces) between them. In other words, the interactions between AuNPs are therefore regarded as one of the key factors governing particles’ self-assembly process that can drive multiple AuNPs to form ordered structures as required. Quantifying the interactions between them and understanding of their self-assembly process are of great importance and yet still challenging. In this study, molecular dynamics (MD) simulations are performed to calculate the interactions (e.g., potential energies) between AuNPs. The MD results reveal that a more effective force model between AuNPs can be developed as a function of their surface separation compared with the conventional Hamaker equation. In addition, MD simulations examine several effects (i.e., particle size, shape, rotation, surface patch, surfactant, as well as configuration) on their interactions. The results demonstrate that the different impacts of these factors (e.g., the hindrance of surfactant). Apart from spherical gold nanoparticles, interactions between gold nanorods (AuNRs) are also be quantified by MD simulations. The interparticle forces of AuNRs can be expressed as a function of their surface separation and the rotation angle since the rotational movement is applied on AuNR. Further, the MD-derived interparticle force models of gold nanospheres are integrated into discrete element method (DEM) to explore their self-assembly process. To the best of our knowledge, this might be the first time that the MD-based interparticle force models are integrated into DEM to explore the self-assembly process of gold nanoparticles. The results show that ordered nanostructures are ultimately constructed. Specifically, the mean coordination number (CN) of AuNPs (3 nm in size) is up to 5.99 and two major large clusters is observed under the simulation conditions at the equilibrated state. The completion of this study not only allows us to evaluate the interactions between AuNPs by MD simulation, but profoundly, the MD-DEM coupling approach opens a new window to unfold the self-assembly process of AuNPs