• Professor, Chemical Engineering
  • George Armistead ’23 Faculty Fellow
  • Affiliated Faculty, Industrial & Systems Engineering and Materials Science & Engineering
Qingsheng Wang

Educational Background

  • Ph.D., Chemical Engineering, Texas A&M University – 2010
  • M.S., Physical Chemistry, Zhejiang University – 2005
  • B.S., Chemistry, Zhejiang University – 2003

Research Interests

    • Process Safety
    • Energy Safety (CO2, LNG, H2)
    • Flame-Retardant Polymers
    • CFD for Energy and Process Systems
    • AI and Machine Learning for Safety

Awards & Honors

  • Susan Howard Award, U.S. Department of Labor – 2024
  • “World’s Top 2% Scientists”, Stanford University/Clarivate – 2023-2025
  • Best Fundamental Paper Award, AIChE South Texas Section – 2022
  • BCSP Foundation Research Award – 2022
  • Global Innovation Contest Award, LG Chem – 2020
  • Inaugural Holder of Dale F. Janes Endowed Professorship, OSU – 2015-2018
  • Halliburton Outstanding Young Faculty Award, OSU – 2015

Selected Publications

  • J.A.D. Marquez, Y. Quan, X. Zhu, H.-J. Sue, Q. Wang*, “Predicting the Processability of Polymers in a Twin-screw Extruder: CFD Simulation and Experimental Validation”, Industrial & Engineering Chemistry Research, 2024, 63 (22), 9823–9832.
  • H. Escobar-Hernandez, Y. Quan, M.I. Papadaki, Q. Wang*, “Life Cycle Assessment (LCA) of Metal-Organic Frameworks (MOFs): Sustainability Study of ZIF-67”, ACS Sustainable Chemistry & Engineering, 2023, 11 (10), 4219–4225.
  • R. Ma, M. Zeng, D. Huang, Q. Wang*, “Zwitterionic Graphene Quantum Dots to Stabilize Pickering Emulsions for Controlled-release Applications”, ACS Applied Materials & Interfaces, 2022, 14 (5), 7486-7492.
  • Y. Quan, R. Shen, R. Ma, Z. Zhang, Q. Wang*, “Sustainable and Efficient Manufacturing of Metal-Organic Frameworks Based Polymer Nanocomposites by Reactive Extrusion”, ACS Sustainable Chemistry and Engineering, 2022, 10(22), 7216–7222.
  • H. Escobar-Hernandez, L.M. Pérez, P. Hu, F.A. Soto, M.I. Papadaki, H.C. Zhou, Q. Wang*, “Thermal Stability of Metal–Organic Frameworks (MOFs): Concept, Determination, and Model Prediction Using Computational Chemistry and Machine Learning”, Industrial & Engineering Chemistry Research, 2022, 61(17), 5853–5862.