Welcome to the Research Group of Hanyu Gao
Modeling techniques have played an important role in chemical reaction and process engineering in multiple aspects. For example, microkinetic modeling provides ways of exploring complex reaction systems for which experimental measurements are challenging; optimization algorithms can be used to guide efficient design of experiments and improvement of processes. More recently, advances in data science and machine learning have also demonstrated their strength in elucidating complicated patterns from molecular structures and reaction systems. Although they have already been powerful individually, the synergies between these modeling techniques would provide even more benefits.
Our group focuses on developing and applying both theoretical and data-driven models to solve problems in chemistry and chemical engineering, in order to facilitate chemical discovery and process development.
[Dec. 2023] Congratulations to Haifan on the acceptance of Using Active Learning for the Computational Design of Polymer Molecular Weight Distributions by ACS Engineering, and to Puqing for Systematic Discovery and Feature Analysis of Intertwined Symmetric Protein Motifs for Topology Engineering being accepted by Giant.
[Nov. 2023] Congratulations to Yue Fang on the publication of Scaling Acceleration Algorithm for Hybrid Kinetic Monte Carlo Simulation of Linear Radical Polymerization by Macromolecules.
[Oct. 2023] The paper, Machine learning and molecular fingerprint screening of high-performance 2D/3D MOF membranes for Kr/Xe separation, is accepted by Chemical Engineering Science.
[Sep. 2023] Thrilled to welcome Haifan Zhou, Yufan Chen, and Yuxuan Zhang as the newest PhD students in our lab, with special congratulations to Haifan for receiving the Hong Kong PhD Fellowship Scheme!
[Jul. 2023] Congratulations to Yue Fang on the acceptance of their paper, Effect of SiO2 Nano-Interphase on the Water Absorption Mechanism of Natural Fiber Reinforced Composites: A Multi-Scale Study, by Applied Surface Science!
[Jun. 2023] The paper, Machine learning and molecular fingerprint screening of high-performance 2D/3D MOF membranes for Kr/Xe separation, is accepted by Chemical Engineering Science.
[Jan. 2023] Delighted to welcome Fungho Hung as a new MPhil student in our lab!
[Dec. 2022] Delighted to announce Min Hu joining our lab as a Postdoc!
[Sep. 2022] Excited to welcome Puqing Deng as our latest PhD student and congratulate him on receiving the HKUST Redbird PhD Scholarship!
[Jun. 2022] The paper, Machine learning for design principles for single atom catalysts towards electrochemical reactions, is accepted by Journal of Materials Chemistry.
[Sep. 2021] Welcome Yue Fang as the newest member of our research group!
[Jan. 2021] The paper, Direct Optimization across Computer-Generated Reaction Networks Balances Materials Use and Feasibility of Synthesis Plans for Molecule Libraries, is accepted by Journal of Chemical Information and Modeling.