POSTGRADUATE
PROGRAMS
PROGRAMS
Postgraduate Programs 2022/23
Master of Philosophy and Doctor of Philosophy Programs in Advanced Materials
Award Title
Master of Philosophy in Advanced Materials
Doctor of Philosophy in Advanced Materials
Program Short Name
MPhil(AMAT)
PhD(AMAT)
Mode of Study
Both full- and part-time
Normative Program Duration
MPhil
Full-time: 2 years
Part-time: 4 years
PhD
Full-time: 3 years (with a relevant research master’s degree), 4 years (without a relevant research master’s degree)
Part-time: 6 years
Offering Unit
Advanced Materials Thrust Area
Function Hub
Program Advisor
Program Director:
Prof Ping GAO, Professor of Advanced Materials
Enquiry
Advanced Materials are concerned with the structure and properties of materials which are enablers for technological innovation in biomedical devices, new energy, sustainable environment and new transportation. New materials developments have led to recent breakthroughs in “meta materials”, nanotechnology and biomimetics, etc.
The Master of Philosophy (MPhil) and Doctor of Philosophy (PhD) Programs in Advanced Materials aim to provide rigorous training in both fundamental investigation of mesoscopic and atomic-scale mechanisms and related novel nanostructures, as well as engineering our original research results in various areas such as biomedicals, functional polymers, and smart meta-materials. New pedagogical training will be provided so that research students can acquire specialized and transferrable skills in new materials engineering that serve the related industries.
On successful completion of the MPhil program, graduates will be able to:
- Identify scientific and engineering significances in new materials design/discovery;
- Engage critical thinking skills that are essential for materials science and engineering;
- Apply a range of qualitative and quantitative research methods for conducting basic or applied research in materials discovery; and
- Demonstrate effective communication skills in reporting research findings.
On successful completion of the PhD program, graduates will be able to:
- Identify scientific and engineering significances in new materials design/discovery and new processes particularly structure property relationships;
- Engage critical thinking skills that are essential for materials science and engineering;
- Apply a range of qualitative and quantitative research methods for conducting original research in materials discovery and innovation; and
- Demonstrate independent and critical communication skills in reporting scientific findings.
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Minimum Credit Requirement
MPhil: 15 credits
PhD: 21 credits -
Credit Transfer
Students who have taken equivalent courses at HKUST(GZ) or other recognized universities may be granted credit transfer on a case-by-case basis, up to a maximum of 3 credits for MPhil students, and 6 credits for PhD students.
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Cross-disciplinary Core Courses
2 credits
UCMP 6010
Cross-disciplinary Research Methods I
2 Credit(s)
Description
This course focuses on using various approaches to perform quantitative analysis through real-world examples. Students will learn how to use different tools in an interdisciplinary project and how to acquire new skills on their own. The course offers different modules that are multidisciplinary/multifunctional and generally applicable to a wide class of problems.
UCMP 6020
Cross-disciplinary Research Methods II
2 Credit(s)
Description
This course focuses on using various approaches to perform quantitative analysis through real-world examples. Students will learn how to use different tools in an interdisciplinary project and how to acquire new skills on their own. The course offers different modules that are multidisciplinary/multifunctional and generally applicable to a wide class of problems.
UCMP 6030
Cross-disciplinary Design Thinking I
2 Credit(s)
Description
This course focuses on user-collaborative design methods for generating inclusive product solutions that integrate stakeholder and product functionality perspectives. Students will create specified product/process/policy/protocol/plan (5P) concept models through the use of recursive user feedback engagement methods, experimental prototyping, and divergent and convergent ideation strategies. Featured topics include design thinking; stakeholder research; concept development, screening, and selection; and interaction design.
UCMP 6040
Cross-disciplinary Design Thinking II
2 Credit(s)
Description
This course focuses on user-collaborative design methods for generating inclusive product solutions that integrate stakeholder and product functionality perspectives. Students will create specified product/process/policy/protocol/plan (5P) concept models through the use of recursive user feedback engagement methods, experimental prototyping, and divergent and convergent ideation strategies. Featured topics include design thinking; stakeholder research; concept development, screening, and selection; and interaction design.
All students are required to complete either UCMP 6010 or UCMP 6030. Students may complete the remaining courses as part of the credit requirements, as requested by the Program Planning cum Thesis Supervision Committee.
- Hub Core Courses
4 Credits
Students are required to complete at least one Hub core course (2 credits) from the Function Hub and at least one Hub core course (2 credits) from other Hubs.
Function Hub Core Course
FUNH 5000
Introduction to Function Hub for Sustainable Future
2 Credit(s)
Description
This course covers background knowledge in the thrust areas of the Function Hub, including Advanced Materials, Sustainable Energy and Environment, Microelectronics, and Earth, Ocean and Atmospheric Sciences.
Other Hub Core Courses
INFH 5000
Information Science and Technology: Essentials and Trends
2 Credit(s)
Description
This inquiry-based course aims to introduce students to the concepts and skills needed to drive digital transformation in the information age. Students will learn to conduct research, explore real-world applications, and discuss grand challenges in the four thrust areas of the Information hub, namely Artificial Intelligence, Data Science and Analytics, Internet of Things, and Computational Media and Arts. The course incorporates various teaching and learning formats including lectures, seminars, online courses, group discussions, and a term project.
SOCH 5000
Technological Innovation and Social Entrepreneurship
2 Credit(s)
Description
This course discusses both opportunities and risks that technological breakthrough has brought to the human society. What would be the policy responses required to maximize its positive benefit and minimize its social costs? In particular, how could we utilize the technological advancement, entrepreneurial thinking to address the challenges our societies are facing, such as job loss/unemployment, income inequality and societal polarization, environmental degradation, health disparity, population aging, and among others. The course uses either case studies or cross-country and time-series data analyses to facilitate the discussion of various social issues and look for innovative solutions of in the real world.
SYSH 5000
Model-Based Systems Engineering
2 Credit(s)
Description
Model-based systems engineering (MBSE) is a contemporary systems engineering methodology that uses conceptual models for communication between system architects, designers, developers, and stakeholders. Object-Process Methodology (OPM) is an MBSE language and methodology for constructing domain-independent conceptual models of all kinds of systems. The course provides students with basic knowledge and tools for MBSE, focusing on conceptual modeling of systems, giving learners a competitive advantage over their peers.
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Courses on Domain Knowledge
MPhil: minimum 9 credits of coursework
PhD: minimum 15 credits of coursework
Under this requirement, each student is required to take elective courses to form an individualized curriculum relevant to the cross-disciplinary thesis research. To ensure that students will take appropriate courses to equip them with needed domain knowledge, each student has a Program Planning cum Thesis Supervision Committee to approve the courses to be taken soonest after program commencement and no later than the end of the first year. Depending on the approved curriculum, individual students may be required to complete additional credits beyond the minimal credit requirements.
Sample Course List
To meet individual needs, students will be taking courses in different areas, which may include but not limited to courses and areas listed below.
FUNH 5100
Introduction to Materials Informatics
3 Credit(s)
Description
Materials informatics integrates materials science and engineering with artificial intelligence (AI), machine learning (ML), and database to accelerate the innovation in the whole materials development continuum and to speed up the process from data to material knowledge. This course will introduce essential and fundamental AI
and ML knowledge and algorithms through vivid and practical examples from materials science and engineering.Notably, this course is designed for students whose majors are not in mathematics or computer science but other broader fields, such as materials science and engineering, mechanics science and engineering, physics, and chemistry. This course will empower those with limited knowledge of statistics, probability, and optimization to learn Materials Informatics without difficulty.
and ML knowledge and algorithms through vivid and practical examples from materials science and engineering.Notably, this course is designed for students whose majors are not in mathematics or computer science but other broader fields, such as materials science and engineering, mechanics science and engineering, physics, and chemistry. This course will empower those with limited knowledge of statistics, probability, and optimization to learn Materials Informatics without difficulty.
AMAT 5200
Machine Learning for Materials Science
3 Credit(s)
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.
AMAT 5230
Introduction to Acoustic Metamaterials and Applications
3 Credit(s)
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.
AMAT 5250
Mathematical Methods for Materials Science and Engineering
3 Credit(s)
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.
AMAT 5315
Modern Scientific Computing
3 Credit(s)
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.
AMAT 5500
Advanced Optics
3 Credit(s)
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.
AMAT 5600
Solid State Physics and Quantum Materials
3 Credit(s)
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.
AMAT 5678
Structure-property Relationship of Advanced Polymer Materials
3 Credit(s)
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.
AMAT 5700
High-throughput Experimental Processing for New Materials Development
4 Credit(s)
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.
The students can then appreciate the high-throughput experimental methods to real-world materials discovery and characterization problems.
AMAT 5750
Statistical Thermodynamics of Chain Molecules
4 Credit(s)
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.
AMAT 5800
Characterization and Processing of Functional Materials
4 Credit(s)
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.
AMAT 5850
Molecular Dynamics Simulations for Biomolecules
3 Credit(s)
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.
AMAT 5900
Molecular Physics and Optoelectronic Processes
3 Credit(s)
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.
AMAT 5910
Compound Semiconductor Materials Technology
3 Credit(s)
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.
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.
AMAT 5950
The Physics of Photon Energy Conversion
3 Credit(s)
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.
AMAT 6900
Independent Study
1-3 Credit(s)
Description
An independent study on selected topics carried out under the supervision of a faculty member.
- Additional Foundation Courses
Individual students may be required to take foundation courses to strengthen their academic background and research capacity in related areas, which will be specified by the Program Planning cum Thesis Supervision Committee. The credits earned cannot be counted toward the credit requirements.
- Graduate Teaching Assistant Training
PDEV 6800
Introduction to Teaching and Learning in Higher Education
0 Credit(s)
Description
The course is designed to strengthen students’ competence in teaching. It comprises 2 parts: Part 1 aims to equip all full-time research postgraduate (RPg) students with basic teaching skills before assuming teaching assistant duties for the department. Good teaching skills can be acquired through learning and practice. This 10-hour mandatory training course provides all graduate teaching assistants (GTA) with the necessary theoretical knowledge with practical opportunities to apply and build up their knowledge, skills and confidence in taking up their teaching duties. At the end of the course, GTAs should be able to (1) facilitate teaching in tutorials and laboratory settings; (2) provide meaningful feedback to their students; and (3) design an active learning environment to engage their students. In Part 2, students are required to perform instructional delivery assigned by their respective departments to complete this course. MPhil students are required to give at least one 30-minute session of instructional delivery in front of a group of students for one term. PhD students are required to give at least one such session each in two different terms. Graded PP, P or F.
All full-time RPg students are required to complete PDEV 6800. The course is composed of a 10-hour training offered by the Institute of Educational Innovation and Practice (IEIP), and session(s) of instructional delivery to be assigned by the respective Thrusts/Base. Upon satisfactory completion of the training conducted by IEIP, MPhil students are required to give at least one 30-minute session of instructional delivery in front of a group of students for one term. PhD students are required to give at least one such session each in two different terms. The instructional delivery will be formally assessed.
- Professional Development Course Requirement
PDEV 6770
Professional Development for Research Postgraduate Students
1 Credit(s)
Description
This course aims at equipping research postgraduate students with transferrable skills conducive to their professional development. Students are required to attend 3 hours of mandatory training on Professional Conduct, and complete 12 hours of workshops, at their own choice, under the themes of Communication Skills, Research Competency, Entrepreneurship, Self‐Management, and Career Development. Graded PP, P or F.
Students are required to complete PDEV 6770. The 1 credit earned from PDEV 6770 cannot be counted toward the credit requirements.
PhD students who are HKUST MPhil graduates and have completed PDEV 6770 or other professional development courses offered by the University before may be exempted from taking PDEV 6770, subject to prior approval of the Program Planning cum Thesis Supervision Committee.
FUNH 6770
Professional Development for Function Hub
1 Credit(s)
Description
This course aims at providing research postgraduate students basic training in scientific ethics in research studies in advanced materials, sustainable energy and environment, earth, ocean and atmospheric sciences and microelectronics, research management, professional career development, and related professional skills. Guest speakers from various professional areas will be invited to share their career paths in professional career developments. Students will have chances to connect to talents in various professional areas. Graded PP, P or F.
Students are required to complete FUNH 6770. The 1 credit earned from FUNH 6770 cannot be counted toward the credit requirements.
PhD students who are HKUST MPhil graduates and have completed FUNH 6770 or other similar professional development courses offered by the University before may be exempted from taking FUNH 6770, subject to prior approval of the Program Planning cum Thesis Supervision Committee.
- English Language Requirement
LANG 5000
Foundation in Listening & Speaking for Postgraduate Students
1 Credit(s)
Description
For students whose level of spoken English is lower than ELPA Level 4 (Speaking) when they enter the University. The course addresses the immediate linguistic needs of research postgraduate students for oral communication on campus using English. To complete the course, students are required to attain at least ELPA Level 4 (Speaking). Graded P or F.
Full-time RPg students are required to take an English Language Proficiency Assessment (ELPA) Speaking Test administered by the Division of Language Education before the start of their first term of study. Students whose ELPA Speaking Test score is below Level 4, or who failed to take the test in their first term of study, are required to take LANG 5000 until they pass the course by attaining at least Level 4 in the ELPA Speaking Test before graduation. The 1 credit earned from LANG 5000 cannot be counted toward the credit requirements.
LANG 5001
Postgraduate English for Engineering Research Studies
1 Credit(s)
Description
This course aims to help research students in engineering communicate their research effectively. It highlights the characteristics of academic discourse, and provides training in the production of research-type documents, including abstracts, journal papers and theses. The course also gives extensive practice in the presentation and seminar skills necessary for academic study. Students who fail to fulfill the spoken English language requirement of the University are advised to take LANG 5000 before enrolling for this course (for students admitted in 2009/10 and onwards). Graded P or F.
LANG 5002
Postgraduate English for Business and Social Science Studies
1 Credit(s)
Description
This course is intended to provide RPG students of SBM and SOSC with essential training in academic writing, speaking and critical reading relevant to the study of a research postgraduate degree. Students who fail to fulfill the Spoken English language requirement of the University are advised to take LANG 5000 before enrolling for this course (for students admitted in 2009/10 and onwards). Graded P or F.
LANG 5010
Postgraduate English for Science Studies
1 Credit(s)
Description
This course teaches common skills postgraduate science students need to write and speak about their research. The course is compulsory for all RPG students of SSCI (for students admitted in 2012/13 and onwards). Students who fail to fulfill the English language requirement of the University are advised to take LANG 5000 before enrolling for this course (for students admitted in 2009/10 and onwards). Graded P or F.
Students are required to take one of the above three courses. The credit earned cannot be counted toward the credit requirements. Students can be exempted from taking this course with the approval of the Program Planning cum Thesis Supervision Committee.
- Postgraduate Seminar
FUNH 6800
Function Hub Seminar
0 Credit(s)
Description
Seminar topics presented by students, faculty and guest speakers. Students are expected to attend regularly and demonstrate proficiency in presentation in accordance with the program requirements. Graded P or F.
MPhil:
Full-time students must take and pass FUNH 6800 in at least two terms.
PhD:
Full-time students must take and pass FUNH 6800 in at least four terms.
- PhD Qualifying Examination
PhD students are required to pass a qualifying examination to obtain PhD candidacy following established policy.
- Thesis Research
AMAT 6990
MPhil Thesis Research
0 Credit(s)
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.
AMAT 7990
Doctoral Thesis Research
0 Credit(s)
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.
MPhil:
- Registration in AMAT 6990; and
- Presentation and oral defense of the MPhil thesis.
PhD:
- Registration in AMAT 7990; and
- Presentation and oral defense of the PhD thesis.
Last Update: 1 March 2023
To qualify for admission, applicants must meet all of the following requirements. Admission is selective and meeting these minimum requirements does not guarantee admission.
1. General Admission Requirements of the University
Please refer to Admission Requirements.
2. English Language Admission Requirements
Please refer to Admission Requirements.
