We seek to delve into the mechanistic intricacies of 3d-metal catalyzed reactions involving non-innocent ligands. By employing advanced multi-configurational ab initio methods, such as CASSCF/NEVPT2, we aim to address the challenges in spin-state energetics prediction of  species with multi-reference characteristics, which are often inadequately captured by traditional DFT approaches. Our research strives to provide a deeper understanding of metal-ligand cooperativity and the fundamental reactivity paradigms in these complex catalytic systems, ultimately contributing to more accurate predictions and understanding of reaction mechanisms. 

Traditional methods for converting methane to formaldehyde typically involve an indirect, multi-step process using metal-based catalysts, which is cost intensive. Recently, there has been growing interest in boron-based catalysts, such as boron oxide and hexagonal boron nitride, for facilitating a direct conversion of methane to formaldehyde. Our research aims to utilize density functional theory (DFT) and relevant descriptors to gain a deeper understanding of the role of electron-deficient boron-based catalysts in transforming methane into formaldehyde (HCHO). Through this investigation, we seek to uncover the underlying mechanisms and various actives sites involved in the reaction.

Our research leverages the power of Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations to identify and design optimal electrolytes for next-generation batteries. By applying advanced DFT techniques, we predict and refine the electronic properties of potential electrolytes to ensure their performance. We also work towards unravelling the complexities of the electrode-electrolyte interface, providing crucial insights that influence overall battery efficiency and longevity. Prediction of promising electrode materials is another crucial aspect of our research.

Our research focuses on the computational investigation of transition metal-catalyzed hydrofunctionalization of alkenes, aiming to understand reaction mechanisms at the molecular level. By utilizing density functional theory (DFT) and non-covalent interaction (NCI) analyses, we explore key orbital interactions and catalytic efficiencies. This work provides insights into catalyst design for selective and sustainable transformations. Through these studies, we aim to contribute to the development of novel catalytic systems.

We aim to gather deep understanding in how the corrosive atoms interact with the various corrosion inhibitors, including various types of metal oxides and organic inhibitors. This information is then used to design effective inhibitors to further enhance the corrosion inhibition. We also focus on altering the composition of the base metal itself to enhance its corrosion resistance.