MSE-305 Introduction to Atomic Scale Modeling
MSE-305 Introduction to Atomic Scale Modeling
Simulation and modeling has become an integral part of the process of designing and optimizing materials for the most diverse applications. Truly predictive simulations, that can estimate the properties of materials before they have ever been synthesized, require atomistic resolution. This course provides an introduction to some of the techniques that underlie atomic-scale simulations of materials. With a strong hands-on component, based on interactive Jupyter notebooks, we will revisit, and see in a new light, several basic concepts on the nanometer-scale description of matter, and see a number of different modelling techniques in action, from molecular dynamics to atomic-scale machine learning.
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Make atoms dance by integrating Newton's equations, following the forces generated by the interatomic potential.
06 - Molecular dynamics
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The 1D harmonic chain as a simple model of lattice vibrations in solids.
03 - Lattice dynamics
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Dimensionality reduction and linear regression: the basics of data-driven materials modeling
07 - Machine learning
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What are the structure and stability of defects in crystals? In this video we review the most common type of defects - point defects, surfaces, dislocations - and use…
05 - Defects
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The interatomic potential measures the stability of an arrangement of atoms. We discuss both the construction of potentials as an approximation to physical interactions…
04 - Potentials
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Crystal structures, direct and reciprocal lattices, and the calculation of the diffraction pattern from a crystal.
02 - Crystallography
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How to represent a structure on a computer in terms of the nature and positions of its atoms? This module provides an overview of this basic problem, and gently…
01 - Atomic scale structures
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A brief overview of some Python concepts used in this course.
00 - Python recap
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Overview of the course
00 - Getting started
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