Research
Approach
Our group employs a range of computer-based modelling methods to understand and design materials for different energy, environment and biomedical applications.
These include:
Quantum-mechanical methods (such as density functional theory and time-dependent density functional theory)
Atomistic methods (such as molecular dynamics)
Machine-learning methods
Projects
- Catalysis
Our core work revolves around designing efficient photocatalysts (specifically, plasmonic photocatalysts). These catalysts are made up of metallic nanostructures in conjunction with semiconductors generally. Because they are strong absorbers of light, there is interest in using these catalysts to utilize sunlight to directly carry out chemical reactions. Currently, these are still poorly understood and the reaction efficiencies are low. We are trying to address these issues using quantum-mechanical approaches along with experimental work carried out in collaboration with Dr. Mahesh Suryawanshi's and Prof. Rose Amal's group at UNSW.
2. Batteries
With interest to explore battery technologies beyond Li-ion, we are closely working with Dr. Dipan Kundu at UNSW to design practically relevant Zn-ion batteries. These are expected to be safe, low cost and easy to manufacture along with other positive attributes. However, there are issues related to anode stability that prevent these from becoming a commercial reality. We are employing a mix of quantum-mechanical and machine-learning methods to address these issues to support experimental work being carried out in Dr. Kundu's group.
3. Antimicrobial polymers
Increasing microbial resistance has prompted the research community to design novel antimicrobial materials. In this regard, we are trying to design novel antimicrobial polymers in collaboration with Prof. Cyrille Boyer's group at UNSW. We are employing machine-learning methods to analyse existing experimental datasets and to discover potent antimicrobial polymers using the developed models/understanding.