My research focuses on process intensification via modular reactor and separation system design to enable electrified, decarbonized chemical manufacturing. I leverage process simulation, data analysis, and mathematical modeling—using Python, MATLAB, Pyomo, Aspen Plus, and GAMS—to build models that optimize process design, guide dynamic operation, and minimize economic costs.
Research Interests
According to the U.S. Energy Information Administration (EIA), renewable electricity is projected to become the largest primary energy source globally by 2050, surpassing petroleum, natural gas, and coal. Solar photovoltaic (PV) is expected to lead as the largest individual electricity source. To facilitate the liquid fuel production with renewable energy, I am interested in designing modular reactor and membrane-integrated modular separation process powered with renewable energy.
While optimization methods have long provided critical insights into process design in my previous work, I see physics-informed machine learning as a complementary tool for intensifying both reaction and separation operations—and for accelerating scale-up from laboratory to industrial scale. Ultimately, my goal is to select and apply the most appropriate computational and data-driven techniques to generate actionable insights, optimize performance, and intensify chemical processes for a low-carbon future.
Below, I introduce the projects which I have submitted and published (ongoing work is not included). (1) I benchmarked ethane–ethylene membrane separation technologies by comparing heat-pump enhanced cryogenic distillation without external refrigeration against multi-stage membrane cascade design, establishing performance targets for membrane permeance and selectivity. (2) To achieve the electrification of ethane cracking process, we developed a linear programming model for the energy storage system to enable continuous and steady operation of chemical plants powered by intermittent solar and wind electricity, considering battery storage, hydrogen storage, electrolyzer, renewable curtailment, and grid connection (published in Chemical Engineering Journal, Vol. 505, Feb. 2025). 3) Building on these insights regarding the substantial energy storage burdens, we realize the importance of modular reactor and separation processes design, which can adjust its demand to the fluctuations in renewable power. We have designed a load‐following reactor to integrate intermittent renewable energy into chemical production processes which significantly reduce the battery requirement. This significantly reduces the capital cost in decarbonized liquid‐fuel production and accelerate the renewable power plant deployment in the future.