Teaching & Education

Classes that are currently taught:

MSE 723: Materials Informatics

(Distance Education and in person at NCSU)

Class Goals: The course aims to introduce the emergent field of materials informatics and current approaches that employ machine learning and experimental and computational data to accelerate the process of materials optimization, discovery, and development. An emphasis will be placed on the practical implementation of machine learning techniques to various materials science problems.

• STUDENT LEARNING OUTCOMES After completing this course, students will be able to:
  ·Demonstrate an understanding of key materials informatics concepts and components;
  ·Explain the relationship between materials and data-driven techniques
  ·Interpret the informatics problems and capabilities associated with different types of materials
  ·Describe available machine learning techniques and materials databases
  ·Identify a machine learning algorithm with the desired properties for a given materials problem
  ·Evaluate existing and emerging machine learning technologies and analyze trends in data-driven techniques to anticipate how materials informatics evolve to meet changing needs

Publication: Thomas J. Oweida, Akhlak Ul-Mahmood, Matthew D. Manning, Sergei Rigin, Yaroslava G. Yingling, MRS Advances 5 (2020) 1-18 DOI: 10.1557/adv.2020.171
In this paper, we discuss the growing use of materials informatics in academia and industry, highlight the need for educational advances in materials informatics, and discuss the implementation of a materials informatics course into the curriculum to jump-start interested students with the skills required to succeed in materials informatics projects.

MSE 721: Nanoscale Simulations and Modeling

(Distance Education and in person at NCSU)

Class Goals: The course is designed to assist engineering students in learning the fundamentals and cutting-edge nature of various simulations methods and their application to nanostructures and nanotechnology. The modeling tools range from accurate first-principles quantum-based methods to multi-scale approaches that combine atomic and continuum modeling. An emphasis is placed on using computational methods for data-driven approaches for the design of new materials.

• STUDENT LEARNING OBJECTIVES After completing this course, students will be able to:
  • Identify and explain the advantages and limitations of various computational techniques;
  • Explain the properties of various nanomaterials and nanosystems;
  • Select appropriate computational methods that can help address specific materials, properties and processing;
  • Evaluate literature based on the use of computational techniques;
  • Design research problems with the use of computational techniques.

MSE 485/MSE791: Biomaterials

(Distance Education and in person at NCSU)

Class Goals: The course introduces fundamental aspects associated with synthesis, properties, processing/fabrication and application of materials derived from or associated with bio-entities.  The course focuses on biomaterials with broad applications beyond medical or clinical uses.  The course emphasizes the biological systems unique machinery and function in the context of desired outcome that utilizes a material or materials’ systems.  Fundamental concepts covered in the course include: differences among classes of biomaterials; toxicity vs biocompatibility of biomaterials; bulk vs surface properties of biomaterials; interactions of biomaterials with different environments; biomaterials stability and degradation; biomaterials for sensing and bioelectronics applications; biomaterials for energy, soft robotics and responsive materials applications; biomaterials for drug delivery, multiplexing and theranostic applications.

STUDENT LEARNING OBJECTIVES After completing this course, students will be able to:

• Explain the properties of various biomaterials;
• Select appropriate methods that can help address specific materials, properties and processing;
• Apply the chemistry and engineering knowledge gained to solve challenges in biomaterials;
• Critically review papers from the scientific literature and identify areas of research opportunities.