EE488 : Modern Semiconductor Device Physics

Overview

This course will survey key concepts of quantum mechanics, solid-state physics, and semiconductor physics in view of realizing nano/quantum electronic devices. Rather than the traditional approach to semiconductor devices based on the drift-diffusion equation, the first-principles approach starting from quantum transport theory will be presented.

Requirements

Undergraduate-level quantum mechanics & solid-state physics; matrix algebra; programming (e.g. MATLAB). Working knowledge of solid-state or semiconductor physics is desirable but not mandatory.

Evaluation Criteria

* N.B.: Undergraduate and graduate students will be graded separately

EE479: Scientific Computing and Data

Overview

Using the Python programming language, this course surveys scientific computing methods. In the first part, traditional numerical analysis techniques for the solution of ordinary and partial differential equations will be covered in the context of representative scientific problems. In the second part, as a modern numerical analysis framework, we will survey data-driven scientific computing methods that employ machine learning and other related techniques. The connection between traditional (“numerical analysis”) and modern (“machine learning”) approaches will be emphasized. Scientific computing know-hows (selected from symbolic computing, data input/output, revision control, profiling, optimization, and high-performance computing, etc.) will be also discussed.

Requirements

Undergraduate-level matrix algebra; programming (e.g. MATLAB, Python)

Evaluation Criteria

* N.B.: Undergraduate and graduate students will be graded separately

EEW522: Quantum Transport in Semiconductors

Overview

Quantum electrical and thermal transport processes lie at the heart of modern electronic, energy, and bio-devices. This course develops a microscopic understanding of the charge, spin, and energy transport phenomena in nanoscale materials and devices. Particular emphasis will be placed on the atomic-scale descriptions and computational modeling.

Course Outcomes

• Understanding of the basic theory to describe quantum charge, spin, and energy transport.
• Ability to use modern software to model and simulate nanojunctions.
• Ability to analyze and design advanced electronic/energy/bio-devices based on functional nanomaterials.

Requirements

Undergraduate-level quantum mechanics & solid-state physics; matrix algebra; programming (e.g. MATLAB). Working knowledge of solid-state or semiconductor physics is desirable but not mandatory.

Evaluation Criteria

Attendance 10%, homework 30%, midterm exam 30%, final project & presentation 30%

EEW521: First-Principles Calculations for Nano Materials

Overview

Atomistic computer simulations are currently playing a crucial role in the research and development of advanced nanomaterials and nanodevices. This course will provide introduction to first-principles (ab initio) electronic structure calculations and their extensions that lie at the heart of atomistic materials modeling and simulations. Much emphasis will be placed on density functional theory and its applications. Students will be able to achieve deeper understanding of the subject by carrying out hands-on simulations.

Course Outcomes

• Understanding of the formal ground of DFT and its extensions (exchangecorrelation functionals, pseudopotentials, time-dependent DFT, etc.)
• Understanding of the practical applications of DFT to nanomaterials and nanodevices.
• Ability to use modern software (particularly, SIESTA) to model and simulate nanomaterials via homework and projects.

Requirements

Undergraduate-level quantum mechanics & solid-state physics; matrix algebra; programming (e.g. MATLAB). Working knowledge of solid-state or semiconductor physics is desirable but not mandatory.

Evaluation Criteria

Attendance 10%, homework 40%, project presentation & report 50%

EEW520: Solid State Physics for Nanodevice

Overview

This course will provide an introduction to solid-state physics, with an emphasis on the nanostructures/nanodevices, atomic-scale descriptions, and computational modeling. By performing hands-on simulations and projects, students will be able to acquire not only the basic concepts of solid state physics but also the ability to carry out atomistic materials modeling and electronic structure calculations.

Course Outcomes

• - Understanding of the basic theory of solid-state physics.
• - Ability to use modern software to model and simulate solids.
• - Ability to analyze and design advanced electronic/energy/bio-devices and solids they are made of.

Requirements

Undergraduate-level quantum mechanics & solid-state physics; matrix algebra; programming (e.g. MATLAB). Working knowledge of solid-state or semiconductor physics is desirable but not mandatory.

Evaluation Criteria

Attendance 10%, homework 30%, midterm exam 30%, final project & presentation 30%