Teaching

Fall 2023

EECE /MSE 580K Quantum Mechanical Computation of Materials

Course Syllabus:

Suggested Textbook:

Lecture slides are the only required reading material. Suggested reading will be given as handouts: Electronic Structure: Basic Theory and Practical Methods by Richard Martin (More information about the book at http://electronicstructure.org/).

Description:

The goal of this course is to teach students basic theory and computational methods to understand and predict materials properties and functions. We feature hands-on in-class exercises that teaches students how to use the computational code and python programming to understand the electronic structures of materials, with a special focus on semiconductors. We will start with providing an overview of quantum mechanics and solid-state physics that are important to the understanding of basic concepts underlying the computational methods. We will then introduce foundations of density functional theory and discuss practical implementations: students will learn to run the actual first-principles computational code VASP (https://www.vasp.at/) on supercomputers, interpret and present the results. We will illustrate examples to show how computational methods can be used to understand materials structures, defects, and functions for real-world applications, including renewable energy, (opto)electronics, and quantum information. We will also introduce python programming and the application of machine learning algorithms in computational materials science.

Topics:

Basics of quantum mechanics and solid-state physics; Foundations of density functional theory; Practical computations of atoms, molecules, and solids; Predicting materials properties: bulk, surfaces, interfaces of solids; defects, conductivities, and optical properties of semiconductors. Python programming and machine learning.

Prerequisites: EECE 332 or PHYS 323 or permission of instructor

Homework Assignments and final project:

Homework problems, lecture notes, and recorded lectures will be posted on Brightspace. Mid-term exam questions will resemble homework problems or examples from lectures. For final projects, students will propose a research topic, perform calculations, obtain and analyze data, and prepare the final project presentation.

Grading:

· Homework Assignments (30%)

· Mid-term exam (30%) (open book; notes and books allowed)

· Final project (40%) (in-class presentation; 12-min per student)

Spring 2023

EECE/MSE 535X Quantum Physics of Semiconductor Materials (New graduate level course proposed by Dr. Wang)

Course Syllabus:

Suggested Textbook:

Lecture slides are the only required reading material. Suggested reading will be given as handouts: D. Jena (Quantum Physics of Semiconductor Materials and Devices)

Description:

This course covers basic solid-state physics, quantum mechanics, and semiconductor physics relevant for understanding semiconductor materials and devices. The goal of this course is for you to learn the relationship between basic science and engineering applications, and how to engineer materials at the nanoscale to enable novel electronic and photonic properties.

Topics include quantum mechanics in a nutshell, crystalline structures, energy bands in solids, electronic and optical properties of semiconductor materials, doping of semiconductors, and frontiers of semiconductor materials research in energy, quantum communication and quantum computing.

Prerequisites:

EECE 332 or PHYS 323 or permission of instructor

Homework Assignments and final project:

Homework problems and lecture notes will be posted. Mid-term and final exam questions will resemble homework problems or examples from lectures.

Grading:

· Homework Assignments (40%)

· Mid-term exam (30%)

· Final project (literature review) (30%)

Fall 2022

EECE 580K Quantum Mechanical Computation of Materials (New graduate level course proposed by Dr. Wang)

Course Description:

Quantum mechanical description of materials is important to understand structure-property-performance relationships in materials science. Theoretical computation is a power tool and complementary approach to experiments. This course will firstly provide an overview of quantum mechanics and solid-state physics that are important to the understanding of basic concepts underlying the computational methods. We will then introduce foundations of density functional theory and discuss practical implementations: students will learn to run the actual first-principles computational code VASP (https://www.vasp.at/) on supercomputers, interpret and present the results. We will illustrate examples to show how computational methods can be used to understand materials structures, defects, and functions for real-world applications, including recent literatures in renewable energy, electronics, and quantum information.