Welcome to the Multiscale Process Safety Laboratory (MPSL) in the Artie McFerrin Department of Chemical Engineering, associated with the Mary Kay O’Connor Process Safety Center at Texas A&M University. The MPSL is directed by Professor Qingsheng Wang. Our research covers several core domains: traditional and advanced process safety, quantitative fire risk assessment (battery fires, wildland fires, data center fires), data‑driven safety analytics, AI-enabled materials discovery and evaluation (MOF, PPN), and safety of emerging energy systems including CO₂, LNG, and hydrogen technologies.
We uses multiscale and multidisciplinary approaches, including both experiment and modeling:
- Experiment
- Large-Scale Field Testing
- Fire Testing
- Composite Manufacturing
- Synthetic Chemistry
- Modeling
- Machine Learning (ML) and Artificial Intelligence (AI)
- Computational Fluid Dynamics (CFD)
- Life Cycle Assessment (LCA)
- Process Modeling and Simulation
The research team aims to bring perspectives of chemical engineering, machine learning, chemistry, and materials engineering to chemical process industries and hence yields systematic solutions to improve process safety, energy safety, and safety for critical infrastructure. The Wang group is organized into four teams (A-D):
- A Team – Process Safety
- B Team – Machine Learning and AI
- C Team – Flame Retardant
- D Team – Large-Scale Testing
A new book “Machine Learning in Chemical Safety and Health: Fundamentals with Applications” is published by Wiley, ISBN 111981748X, 9781119817482.
Spring 2022 Group Picture
Fall 2023 Group Picture
Spring 2024 Group Picture
