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.

Consider a chemical reactor like a PFR. In the usual, forward problem, taught in CRE courses, you are given the input flow rate and reactant concentration, along with kinetic reaction-rate information, and asked to predict the output concentration or conversion. But suppose, instead, that the conversion is measured experimentally and you are asked to use a model to estimate the input flow rate or input concentration. This is an inverse problem. Such problems arise when using specialized research reactors to determine chemical kinetics information.

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. 

Objective is to determine the critical condition for meandering instability of air flow in a granular bed.

Objective is to quantify the segregation behaviour of cohesive and non-cohesive powders during vertical flow under different air-flow conditions.