Faculty：Mechanical Engineering

Targeted Student：undergraduate

Course Credit：1

Lecture Hours：16

（consisted of _16_ theoretical hours）

Course Leader：

Name：Yuzheng Guo

E-mail：yguo@whu.edu.cn

Office：

Mobile：

Course Staff：

Name：Zhaofu Zhang

E-mail：zhaofuzhang@whu.edu.cn

Office：

Mobile：

Course Type：一般通识课程General Course

Related Preview Courses：

General Physics, Semiconductor Physics

Introduction   to Multi-Field, Multi-Scale Simulation

• Overview of simulation methods in materials science and electrical engineering

• Introduction to DFT, MD, and FEM

• Basics of programming and simulation languages

• Examples:

• DFT: calculation of the electronic structure of a simple metal (e.g. lithium)

• MD: simulation of the motion of a small molecule (e.g. water)

• FEM: analysis of the thermal conductivity of a simple material (e.g. copper)

1

Density   Functional Theory

• Fundamentals of DFT

• Kohn-Sham equations

• Exchange-correlation functionals

• Examples of DFT applications in materials science and electrical engineering

• Examples:

• DFT calculation of the electronic structure of a semiconductor (e.g. silicon)

• DFT calculation of the optical properties of a metal (e.g. gold)

• DFT calculation of the superconducting properties of a material (e.g. niobium)

2

Molecular   Dynamics

• Fundamentals of MD

• Verlet algorithm

• Velocity-Verlet algorithm

• Examples of MD applications in materials science and electrical engineering

• Examples:

• MD simulation of the motion of a protein molecule

• MD simulation of the dynamics of a nanoscale device

• MD simulation of the phas transition in a material (e.g. phase transition in a polymer)

2

Finite   Element Method

• Fundamentals of FEM

• Weak form and variational formulation

• Element types and assembly

• Examples of FEM applications in materials science and electrical engineering

• Examples:

• FEM analysis of the thermal conductivity of a complex material (e.g. composite material)

• FEM analysis of the mechanical properties of a complex material (e.g. composite material)

• FEM analysis of the electromagnetic properties of a complex material (e.g. metamaterial)

2

Machine   Learning in Simulation and Modeling

• Introduction to machine learning and its application to simulation and modeling

• Overview of popular ML algorithms and their applications

• Examples of ML applications in materials science and electrical engineering

• Examples:

• ML-based prediction of material properties (e.g. mechanical properties of a material)

• ML-based prediction of device behavior (e.g. electrical properties of a transistor)

• ML-based prediction of system behavior (e.g. thermal conductivity of a complex material)

1