(2lh) Nanoscale Thermodynamics in Liquids and Soft Materials

The sustainable development of our society is facing global challenges in energy management, climate change, environment protection, information technology, and human health. Throughout my academic career, I have been interested in developing computational methods and theoretical models to solve fundamental problems in physical chemistry. My research areas are focusing on thermal physics, polymers, interfacial chemistry, nanotechnology, computational and theoretical chemistry. I have been working on five projects: (1) structure and thermal conductivity relationships in different types of polymers; (2) interfacial thermal conductance enhancement using different surface functionalization ligands; (3) thermodynamics of water, ion, and gas in nanostructures; (4) data storage and information processing in networked engineered nanoparticles; (5) self-assembly of quantum dot and DNA origami nanostructures. My current projects are aiming to developing new materials for energy, mass, and information applications.

Looking forward, I also want to look for sustainable solutions to developing advanced materials. Biomaterials from plants, animals, and microbes have been used in many applications, such as packaging, construction, and energy. Understanding the structure and property relationships of biomaterials at molecular level is the key to apply these materials in new nanotechnologies. I plan to develop physics-based theoretical models and data-based artificial intelligence models to explore a variety of biomaterials. My projects will be related to engineering sustainable materials for thermal transport, CO₂ capture, water separation, data storage and computing.

Climate change and sustainability are important topics we need to emphasize in our research and education as we motivate the next generation of students and practitioners. I will use physical models, high performance computers and information technologies to look for innovative solutions from nature. Through rigorous research and interdisciplinary collaboration, I will aim to develop new advanced biomaterials and nanotechnologies for a sustainable future.

Teaching Interests

I am interested in teaching multiple courses in Chemical Engineering at both undergraduate and graduate levels, including Thermodynamics, Statistical Mechanics, Transport Phenomena, Physical Chemistry, and Computational Modeling. I will use active learning to help students be more engaged during lectures so they can learn more effectively. Various types of active learning methods will be implemented within my course, such as in-class discussion, think-pair-share, in-class video demonstrations paired with breakout discussions, and . I plan to use an iPad as my blackboard to write most of my lecture notes in real time. I will also take advantage of limited preloaded materials in Power point slides with pictures, figures, and videos as they can help students visualize concepts while attracting their attention. I will also implement emerging tools and teaching methods. This included by mixing face-to-face and online lecturing, project-based learning by teaching each students finishing their research projects, and engaging students using augmented reality (AR) and virtual reality (VR) tools to explore 3D molecular structures.

I would also like to develop a new course aimed for senior undergraduate and new graduate students about new computational methods in Chemical Engineering. In general, this course will expose students to how modern-day chemical engineers use computers to solve their problems, which covers fundamentals in Computational Chemistry, Simulation, Programming, Data Science, Materials Science, and Artificial Intelligence. As an example, I plan to walk them through case studies using computing packages to solve the quantum structure of an isolated water molecule and the structure of a solution of thousands of water molecules. I will also show them how machine learning (ML) and deep learning (DL) methods can be used to analyze the simulation results. In the course, students will use Python or Matlab for programming, compile and modify simulation codes such as LAMMPS, and apply ML and DL methods. I plan to demonstrate in-class how to use ChatGPT for modeling, coding, and data analysis.