(6gx) Functional Nanomaterials Via Self-Assembly: Theory and Simulation

Malmir, H., Yale University

Since September 2017, I am a postdoctoral research associate at Yale University Department of Chemical and Environmental Engineering, working in the group of Computational Soft Matter. Prior to joining Yale, for two years, I was a postdoctoral research scholar in the group of Professor Muhammad Sahimi in the department of Chemical Engineering and Materials Science at the University of Southern California. I am a computational scientist with research interests mostly in the fields of Soft Condensed Matter and Materials Science. Furthermore, I am currently teaching undergraduate courses as an adjunct lecturer at the University of New Haven.

Research Interests:

Self-assembly is an effective bottom-up technique to fabricate ordered and novel functional nanomaterials. There are various types of building blocks, including nanoparticles (NPs), and polymers, as well as other organic and inorganic molecular structures such as proteins, DNA, and organometallic complexes, which can, under some controllable thermodynamic and statistical-mechanic circumstances, self-assemble and form functional nanomaterials.

In my research, owing to my extensive experience with packing, jamming and self-assembly of nanoparticles as well as my recent works on molecular self-assembly of organometallic compounds on 2D materials, I plan to extend the theory of self-assembly for rational design of functional nanomaterials through molecular simulation and methods of computational statistical mechanics.

My research interests include but are not limited to:

  1. Packing, jamming, and self-assembly of nanoparticles
  2. Molecular self-assembly on 2D materials
  3. Self-assembly of functionalized nanoparticles: Superlattices
  4. Structural characterization of nanostructures

Teaching Interests:

My research and teaching interests and experiences lie at the interface of Thermodynamics, Statistical Mechanics, and Computational Materials Science. I believe a very strong computational background in Chemical Engineering and Materials Science is central to all the applications from Pharmaceutical Science and Engineering to Petroleum Engineering to Additive Manufacturing and so on. Hence, I plan to design novel and interesting approaches to teach courses under this category to both undergraduate and graduate students. My teaching approach is mostly example/application based and I believe without real-world applications, theories are imperfect and hard to follow by most of students.

My teaching interests include but are not limited to:

1. Computational Materials Science

2. Thermodynamics

3. Statistical Mechanics

4. Heterogeneous Materials

5. Transport Phenomena

I also plan to develop a course for graduate students of Chemical Engineering, on "Transport Theory and Stochastic Processes".