AMAT
• AMAT 5200
Machine Learning for Materials Science
[3-0-0:3]
Background
Calculus, linear algebra, probability, coding in Python, some knowledge in differential equations will be very helpful but not required.
Description
This course aims to provide students training with a convergence of the two disciplines of Materials Science and Machine Learning (ML). We will start from machine learning basics, its mathematical foundations, then move on to modern machine learning methods for materials science problems and hands-on study with Python. Particularly, students will learn about how to combine the data-driven ML techniques with existing knowledge of materials science to give reliable physical predictions. Various case studies will be discussed, with real-world materials science applications.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Understand a variety of modern machine learning methods.
• 2.
Understand the importance of incorporating physical knowledge into machine learning algorithms.
• 3.
Understand how to evaluate models generated from data.
• 4.
Develop an appreciation for physics-based machine learning models for material design/prediction.
• 5.
Apply the machine learning algorithms to a real materials science problem, optimize the models learned and report on the expected accuracy that can be achieved.
• AMAT 5230
Introduction to Acoustic Metamaterials and Applications
[3-0-0:3]
Background
Undergraduate-level physics, basic calculus, and differential equations.
Description
This course will provide knowledge about acoustic metamaterials to graduate students. We will start from the physics of sound waves, then we will discuss conventional acoustic materials. From the discussion, we will understand the limits of conventional acoustic materials due to the weak wave-matter interactions. Then, we will discuss how we can control the wave-matter interactions and bypass natural limits through acoustic metamaterials, including in fluids and solids (elastic metamaterials). In particular, students will learn about various interesting metamaterial devices, such as acoustic cloaks, negative-refraction metalens, and acoustic “black holes”. Finally, students will also have the opportunities to design their own acoustic metamaterials.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Learn the dynamics of acoustic waves in fluids and solids.
• 2.
Know conventional acoustic materials and identify their natural limits.
• 3.
Understand and design basic acoustic and elastic metamaterials.
• 4.
Describe the working principles of metamaterials and phononic crystals.
• 5.
Apply the knowledge of acoustic materials and metamaterials to practical scenarios.
• AMAT 5250
Mathematical Methods for Materials Science and Engineering
[3-0-0:3]
Background
College-level physics, calculus, differential equations.
Description
This course will focus on mathematical methods, with specific concern about construction, analysis, and interpretation of mathematical models that shed light on significant problems in materials science and engineering. There are many courses that present collection of math techniques, but this course will be different: typically, we will use a “case-study” approach, i.e., select a series of important scientific problems, whose solution will involve some useful mathematics. We will start with the scientific background, then formulate relevant mathematical problem with care. The formulation step is usually more challenging than just learning the mathematics. Through the case studies, useful math techniques will be introduced naturally. Some typical case studies include: collective motions and aggregations, heat conduction and elasticity of materials, charge transport, plasmonic effects and bio-chemical kinetics, etc.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Understand how to formulate mathematical models based on physical laws/observations.
• 2.
Understand various useful mathematical methods for problem solving.
• 3.
Understand how to pick the right mathematical tools for specific problems.
• 4.
Know how to physically interpret the mathematical solutions obtained.
• 5.
Know how to analyze the possible physical outcomes, so as to make predictions.
• 6.
Apply the methods learned to a real materials science problem, and reveal the mechanism or make predictions.
• AMAT 5315
Modern Scientific Computing
[3-0-0:3]
Background
Familiar with linear algebra and at least one programming language.
Description
This is an introductory course about computational methods for physical systems such as quantum physics, spin glass et al. It requires knowledge about linear algebra and familiarity of any programming language. The course covers not only computational methods related to matrix/tensor computation, differential programming, and combinatorial optimization, but also techniques related to CUDA programming and the Julia programming language.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Know how to estimate the condition number and round-off errors of a linear algebra function.
• 2.
Know how to estimate the time and space complexity of an algorithm.
• 3.
Know the matrix/tensor decomposition, tensor networks and Monte Carlo methods.
• 4.
Use GPU for parallel computing.
• 5.
Use automatic differentiation to inverse engineer a problem.
• 6.
Use the Julia programming technique to solve computational problems.
• AMAT 5500
[3-0-0:3]
Description
Optics as one of the key branches of physics, plays an essential role in our daily life. In this course, we will present comprehensive aspects of modern optics, covering geometrical optics, wave optics, crystal optics, quantum optics and metasurfaces optics. We will highlight novel optical applications in quantum information science, atomic and molecule physics, precision metrology and materials sciences.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Understand fundamentals of geometrical optics.
• 2.
Understand fundamentals of wave optics.
• 3.
Understand basic functions of optical materials and polarization optics.
• 4.
Gain knowledge of quantum optics.
• 5.
Gain knowledge of metasurfaces optics.
• 6.
Know the applications of optics in quantum information sciences.
• 7.
Know the applications of optics in quantum physics.
• 8.
Know the applications of optics in materials sciences.
• AMAT 5600
Solid State Physics and Quantum Materials
[3-0-0:3]
Background
Basic background knowledge on solid state materials and quantum mechanics.
Description
This is an introductory course for postgraduate students with materials science background. Basic topics of solid state physics including electronic band structure, phonons, electron interactions and spin correlations will be covered. In addition, modern topics of high temperature superconductors, topological electrons, spin liquids and low dimensional systems will be introduced, providing a beginner’s guide to quantum materials.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Understand crystal structure, reciprocal lattice, and know how to draw Brillouin zones.
• 2.
Understand electron band structure, energy gaps and know how to calculate simple tight binding model.
• 3.
Obtain the basic knowledge of topological electronic system.
• 4.
Understand lattice vibration modes and phonons.
• 5.
Obtain the basic knowledge of high temperature superconductivity and the research forefront.
• 6.
Know different types of magnetism and understand spin interactions.
• 7.
Obtain the basic knowledge of quantum spin liquids and low dimensional systems.
• 8.
Collect and process literature in the field of quantum materials and propose new research directions.
• AMAT 5678
Structure-property Relationship of Advanced Polymer Materials
[3-0-0:3]
Background
Basic understanding of polymers; general physical and organic chemistry.
Description
This course is designed for understanding the correlation between molecular structure, chain conformation, condensed structure, physical properties, and mixing thermodynamics. The knowledge learned in the course will equip students with the rationale to design polymer materials for various applications with advanced mechanical, optical, thermal, electrical, and/or magnetic properties.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Understand the molecular characteristics of polymer materials.
• 2.
Access the phase transition and solid-state structures in polymers.
• 3.
Understand the thermodynamics in polymer mixtures.
• 4.
Articulate the general strategies to optimize the physical properties of polymer materials and their structure-property relationship.
• 5.
Conceptually design a polymer product including chemical composition, molecular structure, processing, and properties.
• AMAT 5700
High-throughput Experimental Processing for New Materials Development
[3-0-3:4]
Description
High-throughput experimental methods together with material-based modelling will be introduced for the accelerated discovery of new materials. We will use case studies ranging from polymer synthesis, polymer fabrication to illustrate how the properties such as optical, electronic, mechanical, thermal and others are related to the structures of the materials for use in energy, transportation and biotechnology. The students can then appreciate the high-throughput experimental methods to real-world materials discovery and characterization problems.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Identify the key events in high-throughput materials design.
• 2.
Describe the physical significances of high-throughput methods (both computational and experimental).
• 3.
Explain the principles of high-throughput characterizations.
• 4.
Explain the principles of high throughput methods for materials screening for materials discovery.
• 5.
Find processing-property-structure relationships for new material discovery.
• AMAT 5750
Statistical Thermodynamics of Chain Molecules
[3-0-3:4]
Description
This course will introduce the statistical models to describe the equilibrium and dynamics of polymer chains in equilibrium. First, various models of polymer chains in statics (or equilibrium) will be described. Then the statics of polymer chain in solution will be introduced. Finally, the non-equilibrium polymer chain dynamics will be introduced through molecular dynamics simulation of various ensembles.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Identify significance of thermodynamics and statistical physics in soft mater research.
• 2.
Define the fundamental principles in the development of computational and theoretical models.
• 3.
Apply the contemporary research techniques and their applications.
• AMAT 5800
Characterization and Processing of Functional Materials
[3-0-3:4]
Description
This course covers the fundamental concepts that govern the properties of some functional materials which are important to current technologies. It will also cover the experimental tools to characterize these properties. Focus will be on peculiar property of these functional materials, for example, electrical properties of perovskites in terms of piezoelectricity, pyroelectricity and ferroelectricity. Materials formulation and fabrications will be described and limitations of the materials and processing of these functional materials will be highlighted from the perspective of new materials requirement and industry demands.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Define the principles, processing and functional properties of functional materials.
• 2.
Elucidate the properties of functional materials with their structure.
• 3.
Describe the processing methods for the fabrication of these functional materials.
• 4.
Perform various characterization experiments and analyze the structure property relationships.
• AMAT 5850
Molecular Dynamics Simulations for Biomolecules
[3-0-0:3]
Background
Basic knowledge of calculus is required. Prior knowledge of thermodynamics and statistical mechanics and preliminary experiences with computer programming and Unix-based operating systems are desirable but not required.
Description
Molecular dynamics simulation provides the evolution of the system at the atomistic level. As a computational microscope, molecular dynamics simulation has attracted unprecedented attention and rendered a wide range of applications in current scientific and industrial research, particularly for biomolecular systems. This course will introduce an overview of the molecular dynamics simulation, then describe the principles underlying this advanced technique, and discuss its applications in studying the structure and dynamics of biomolecules, such as proteins and nucleic acids.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Have a general knowledge of the state-of-the-art molecular dynamics simulation.
• 2.
Set up and run the simulations of biomolecular systems of interest.
• 3.
Perform the preliminary analysis to post-process the simulation trajectory.
• 4.
• 5.
Design the molecular dynamics simulation strategy for solving the specific problem.
• 6.
Gain an overview of biomolecular structure-function relationship.
• AMAT 5900
Molecular Physics and Optoelectronic Processes
[3-0-0:3]
Description
This course will cover the physics of the electronic structure of pi-conjugated materials and their neutral, excited and charged states (excitons, polarons), their optical properties (absorption, emission), photophysical processes, photochemistry, energy transfer and charge transport. It will introduce the principles of design and operation of molecular based light emitting devices, solar cells etc. as well as providing an introduction to device fabrication and device engineering for maximum performance and lifetime.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Understand the basic physics of organic semiconductors introducing the concept of π-conjugation and the electronic structure of π-conjugation materials.
• 2.
Understand the optoelectronic processes occurring at these materials including their neutral, excited and charged states.
• 3.
Evaluate the basic performance of molecular based LEDs and solar cells.
• 4.
Identify the key design principles and operations of molecular based LEDs and solar cells.
• 5.
Engage critical thinking skills that are essential for materials science and engineering.
• AMAT 5910
Compound Semiconductor Materials Technology
[3-0-0:3]
Description
Compound semiconductor materials have been deeply integrated in various gadgets nowadays, shaping the new world in an unimaginable way. Understanding compound semiconductor materials is critical as one of the first steps towards understanding how the advanced technology evolves continuously, from the past to the future. This course aims to introduce an overview of compound semiconductor materials, linking the fundamental physics, materials and devices to the point where the students can specialize and assist them in their supervised research. The course contains fundamentals of semiconductor physics and semiconductor specifics including technologically relevant materials and their properties, doping and defects and heterostructures. General and detailed discussions on linking materials and devices for applications will be covered at the later stage in the course.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Know the role of semiconductor materials in device technologies.
• 2.
Explain the underlying physics in the operation of semiconductor devices.
• 3.
Analyze the characteristics of semiconductor materials.
• 4.
Be familiar with the semiconductor growth process and basic characterizations.
• 5.
Demonstrate ability in material modeling through computational tools.
• AMAT 5950
The Physics of Photon Energy Conversion
[3-0-0:3]
Description
Photon energy conversion is a key research area of renewable energy which produces electricity and chemical fuel from the sunlight or artificial light and photo sensing. However, this research area presents major material challenges, both in terms of electronic kinetics and thermodynamics. This course will introduce the major research area of photon energy conversion applications: photovoltaic, photochemical fuels and photodetectors; then introduce the operation of solar cells, solar fuels and photodetectors, and their underlying mechanisms in terms of device physics, photophysics and related quantum physics.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Know the state of the art solar energy applications and technologies.
• 2.
Understand the basic operation principles of solar cells and solar fuels.
• 3.
Understand the optoelectronic processes occurring at these materials including their neutral, excited and charged states, and charge transport.
• 4.
Know the material challenges of solar cells and photocatalysts.
• 5.
Evaluate the basic performance of solar cells and solar fuels.
• 6.
Know the bias characterization techniques.
• AMAT 6000
[1-4 credits]
Description
Selected topics in advanced materials of current interest in emerging areas and not covered by existing courses. May be repeated for credit if different topics are covered.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Identify the latest development in advanced materials.
• 2.
Explain the theories and applications in the chosen topics.
• 3.
Apply the methodologies and techniques to real problems in the chosen topics.
• AMAT 6900
Independent Study
[1-3 credit(s)]
Description
An independent study on selected topics carried out under the supervision of a faculty member.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Demonstrate mastery of the knowledge and skills in the selected topics related to advanced materials.
• 2.
Apply an interdisciplinary approach in examining the selected topics.
• 3.
Critically evaluate different aspects of the selected topics.
• 4.
Communicate findings effectively in written reports.
• AMAT 6990
MPhil Thesis Research
Description
Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Design, develop and conduct cross-disciplinary research in Advanced Materials.
• 2.
Communicate research findings effectively in written and oral presentations.
• 3.
Synthesize and create new knowledge, and make a contribution to the field.
• AMAT 7990
Doctoral Thesis Research
Description
Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.
Intended Learning Outcomes

On successful completion of the course, students will be able to:

• 1.
Design, develop and conduct cross-disciplinary research in Advanced Materials.
• 2.
Communicate research findings effectively in written and oral presentations.
• 3.
Demonstrate mastery of knowledge in the chosen field of research.
• 4.
Synthesize and create original new knowledge.
• 5.
Make substantial original contributions to the field of study.