Computational Materials Design Laboratory

Developing Computational Methods to Accelerate Scientific Discovery

Welcome to Our Lab

My lab aims at using computational and theoretical methods to develop new materials for applications in energy management, mass transport, information processing, and human health. My research area includes thermodynamics, transport process, polymer structure-property relationship, interfacial physical chemistry, and nanotechnology. My team will develop multi-scale simulation models, machine learning/artificial intelligence (ML/AI) models, and theoretical methods to accelerate materials design. We will use High Performance Computers (HPCs) to help experimentalists solve materal develop problems. Through rigorous computation and interdisciplinary collaboration, my lab will have a broad impact in thermal physics, materials science, computational chemistry, physical chemistry, and data science.

Research Areas

Thermodynamics

thermo

Understand energy, temperature, entropy, and phase/state transition from molecular level to macroscopic scale. Develop theoretical methods to solve thermal physics problems.

Multi-scale simulation

multiscale simulation

Develop multi-scale computational methods, including ab initio, classical molecular dynamics (MD), coarse-grain (CG), Monte Carlo (MC), and hydrodynamic models.

ML/AI models

AI models

Integrate low-fidelity and high-quantity simulation dataset with high-fidelity and low-quantity experimental dataset to train ML/AI models, then apply physical rules to improve the accuracy.

Publications

Google Scholar
Research Gate



Here is the list of all research papers.

Our Team

Principal Investigator

Dr. Xingfei Wei

Principal Investigator

Contact Us

Xingfei Wei, Postdoctoral Schoolar
Department of Chemistry
Johns Hopkins University
Baltimore, MD 21218
Email: xwei20@jhu.edu

Fundings and Compuational Resources

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