Water electrolyzers are electrochemical devices that use renewable electricity to split water into its elemental components such as hydrogen and oxygen. Hydrogen is a common chemical feedstock in major chemical industries and is also a potential energy carrier for automotive and long-term energy storage applications. In this project, we will be designing and building a test bench for water electrolyzer and its various components.

This project aims at studying the impact of distributed architecture on control of an interacting system. Specifically, distributed model predictive controller is used for controlling levels in a quadruple tank system. The work will be primarily experimental but may also require validation using simulations. The work would require background in advanced process control. Pre-requisites: CL 701, CL 686.

(Experimental + Computational)

This project aims at pursuing sustainable design of an integrated biogas-fuel cellcarbon capture system to generate renewable power. The work is an extension of our previous work ( https://aiche.onlinelibrary.wiley.com/doi/abs/10.1002/aic.70118 ) by including anaerobic digestor, gas clean up and carbon capture steps into the design envelope. The work would require background in mathema9cal op9miza9on. Pre-requisites: CL 701, CL 603.

(Computational)

Sodium-ion batteries are emerging as a promising low-cost alternative to lithium-ion batteries, but their performance strongly depends on material and transport properties that are not directly measurable from standard tests. This project focuses on developing a physics-based computer model of a sodium-ion cell that can realistically predict voltage, capacity, and rate performance under different operating conditions.

Commercial lithium-ion batteries only show us the total voltage, hiding what is actually happening inside each electrode during charging, discharging, and aging. This project aims to develop and use a very thin, minimally invasive "micro-sensor" that can be safely placed inside a real commercial battery to separately monitor the behavior of the anode and cathode without dismantling the cell.

Molecular simulations analyze how organic molecules self-assemble into protective thin films on metal substrates to block corrosive agents like oxygen and chloride ions. By calculating adsorption energies and molecular interactions, these studies predict the stability and coverage of the inhibitor layer. This atomic-scale modeling allows researchers to design eco-friendly "green" inhibitors by optimizing the molecular orientation and binding strength to ensure long-term surface passivation in diverse industrial environments.

Molecular simulations investigate the fundamental physics of nanoparticle wetting by calculating atomic-level adhesion energies and contact angles at the interface of particles, liquids, and substrates. These studies are essential for engineering self-cleaning coatings and high-efficiency heat exchangers, as they reveal how surface nanostructures govern the transition between the Wenzel and Cassie-Baxter states.

Molecular simulations investigate the fundamental physics of nanoparticle wetting by calculating atomic-level adhesion energies and contact angles at the interface of particles, liquids, and substrates. These studies are essential for engineering self-cleaning coatings and high-efficiency heat exchangers, as they reveal how surface nanostructures govern the transition between the Wenzel and Cassie-Baxter states.

Molecular simulations provide an atomic-level view of the oil-water interface, revealing how surfactants and ions reduce interfacial tension to mobilize trapped crude. By modeling these nanoscopic interactions, researchers can optimize Enhanced Oil Recovery (EOR) strategies by predicting how chemical formulations will behave under specific reservoir pressures and temperatures. This computational insight allows for the design of more efficient displacement fluids, bridging the gap between theoretical chemistry and field-scale production.

Our group works on building computational models for self-organization in biological systems across scales with a vision of writing down the design principles of functional biomaterials. We use multiple tools of engineering and applied physics as the problem in hand needs. The specific problem will be decided based on the mutual interest of the student and the PI. Some example problems are: 

i) Developing a mechanical model of a tissue to engineer it's deformation based on chemical pattern.