Pioneering a Cleaner, Safer, and More Sustainable Energy Future
Welcome to the Computational Engineering and Energy Lab (CEELab)!
CEELab dedicated to accelerating the global transition toward net-zero emissions requires two fundamental breakthroughs: storing energy safely and converting it with maximum efficiency. At CEELab, we bridge the gap between fundamental physics and real-world engineering by integrating high-fidelity multiphysics simulations, experiments, advanced materials, and artificial intelligence (AI). Our mission is to solve critical bottlenecks in modern energy, propulsion, and automotive systems.
Our research is organized around four synergistic pillars:
1. Battery Systems, Thermal Safety & Reliability
We address the critical safety and longevity challenges of electrified transport and grid storage. Our work encompasses multiphysics thermal management for Battery Management Systems (BMS) and Battery Energy Storage Systems (BESS), fundamental mechanisms of thermal runaway and propagation, fire and explosion mitigation, and data-driven aging and lifetime prediction.
2. Renewable Energy, Alternative Fuels & Clean Combustion
To decarbonize power generation, aviation, and heavy transport, we investigate multiscale, multiphase reacting thermo-fluid systems. Utilizing fundamental kinetics (via shock tubes and rapid compression machines) and high-fidelity numerical modeling, we optimize next-generation energy conversion technologies—including gas turbines, rotating detonation engines (RDE), plasma-assisted combustion, and advanced internal combustion (IC) engines—operating on zero- and low-carbon fuels such as hydrogen, ammonia, and biofuels. Our goal is to push the boundaries of clean and renewable energy technologies, contributing to a more sustainable energy future.
3. Nano & Advanced Materials for Automotive and Energy
We design and characterize next-generation functional materials that underpin energy transition technologies. Key areas include nano-engineered electrodes for high-performance supercapacitors and batteries, solid-state hydrogen storage materials, catalysts for water electrolysis, and shape-memory or impact-energy-absorbing metamaterials for automotive crashworthiness.
4. Computational Engineering, HPC & Physics-Informed AI
Serving as the cross-cutting engine of CEELab, we leverage High-Performance Computing (HPC), massive parallelism, and hybrid computing architectures to tackle computationally prohibitive problems. By fusing mechanistic physical laws with machine learning—specifically Physics-Informed Neural Networks (PINNs)—we build predictive models and real-time digital twins for complex energy and thermo-fluid systems.
Join Us in Shaping the Future of Energy
Whether you are a prospective student passionate about computational science and clean energy, or an academic/industrial partner seeking innovative R&D solutions, CEELab offers a dynamic, collaborative environment to turn bold scientific ideas into high-impact technologies. Explore our projects and connect with us at bau.luongminh@hust.edu.vn.