The project aims at developing a comprehensive model, currently lacking in the literature, for simultaneous electroporation and electrodeformation in vesicles and excitable (such as Neurons and Cardiomyotcytes) and non-excitable nucleate and anucleate cells, relevant in electroporation for cancer treatment.  On the other spectrum of soft matter, the code will also be extended to droplet electrohydrodynamics relevant in crude oil refining. The simulatino platform will be in-house Boundary Integral code, as well as COMSOL Multiphysics and other open source softwares.

We have already developed a working prototype for killing and removal of
E. coli from water. It is based on our synthesized nanocomposite, made
of Ag-Cu nanoparticle impregnated on granular activated carbon and
packed into a filter column, which is driven by gravity-head of the water

We have already developed in our lab. an autonomous device for
real-time, water quality monitoring by both physical and chemical
sensors (some of the sensors being developed by us), with years of
earllier work in our lab. by a multidisciplinary team of Chemical, Mechanical and Electrical Engg. students. 

Electrocatalysis is central to decarbonising the chemical industry, from carbon dioxide reduction to green hydrogen production. Most computational tools in this area were developed for aqueous systems, but the field is now moving towards non-aqueous electrolytes such as ionic liquids and organic carbonates, which offer new reaction pathways and stability windows. Our group has recently implemented an implicit solvent model which interfaces with a density functional theory code.

Water electrolysis using renewable electricity to produce hydrogen is an option for the decarbonization of the major industrial processes and the energy sector. Renewable hydrogen is a flexible molecule to store energy. However, the electrochemical methods to split water are highly energy consuming leading to high Levelized Cost of Hydrogen (LCOH). To bring the LCOH down and accelerate the commercialization of renewable hydrogen, we need to look at alternate pathways for electrochemical hydrogen production.

The vanadium redox flow battery (VRFB) is regarded as one of the most promising candidates for future large-scale energy storage owing to its numerous advantages, including flexible and scalable energy capacity, long cycle life (up to 25 years), high safety and environmental friendliness (no fire risk), and the possibility of low-cost recycling of active materials. However, VRFBs still suffer from intrinsic limitations associated with the vanadium electrolyte, such as low solubility and poor thermal stability.

With the rapid deployment of renewable energy and battery energy storage systems (BESS), reliable battery diagnostics are essential for ensuring safety, performance, and long service life. This PhD project will develop next-generation diagnostic and prognostic tools by combining physics-based electrochemical models with machine learning for accurate estimation of battery state, health, and degradation.

Reliable battery operation at low temperatures is critical for defense, drones (UAVs), aerospace, electric mobility, and grid-scale energy storage. This PhD project aims to develop high-performance sodium-ion batteries for cold-climate operation through a combination of experimental research and physics-based electrochemical modeling. The research will focus on understanding ion transport, reaction kinetics, and degradation using advanced electrochemical characterization (e.g., EIS and cycling) and computational modeling.

Study of phase change solvents for CO2 adsorption