Research Interests

My research interest is based on theoretical and computational chemistry. I devoted my research career in different areas of chemistry, viz., non-covalent interactions, optical properties, magnetic properties, aromaticity, thermochemistry, chemical kinetics, photochemistry, and molecular dynamics.

Throughout these years, I engaged myself in the following fields.

1. Linear and Nonlinear Response Properties of various molecules and small cluster materials, photoswitches.

2. Magnetic Properties of diradicals and dehydrogenated DNA base pairs.

3. Weak Interactions in benzene dimer, CH/π interacting systems and rare gas-CO₂ complexes.

4. Explicit role of electron correlations in small carbon clusters and carbenes.

5. Relativistic Effect in atomic gold chain.

6. Aromaticity in six-membered and four-membered heteroatomic systems.

7. Stability of systems.

8. Range-Separated Density Functional Theory (RSH-DFT) along with the application of Random Phase Approximation (RPA) technique: In this project, I was involved in benchmarking the performance of the RSH technique along with the RPA approach in various categories of weak-interacting systems. I was also involved in a project which deals with the estimation of Resta Localization Index, a field which is quite popular among physicists and slowly gaining importance within the chemistry community. Our group is involved in the development of the RSH-DFT approach and the scheme that we follow is implemented in the developing version of MOLPRO.

9. Variational Transition State Theory for Combustion Mechanisms of Biofuels: In this project, we calculated chemical reaction rates that will be useful for developing mechanisms for oxygenated fuels that are being considered as transportation fuels and on improving the methods available for obtaining such results. We worked on improving ways to obtain and represent potential energy surfaces for rate constant calculations. A typical strategy would be to validate a theoretical model chemistry (e.g., an affordable multi-coefficient correlation method or a combination of a particular density functional with a particular basis set) against the most accurate affordable benchmark-quality wave function method or high-level multi-coefficient correlation method. We also determined whether specific reaction parameters need to be adjusted, and on this basis choose or develop a method on which to base the dynamics for a particular reaction. We then calculated the rate constant by a combination of direct dynamics and multi-configuration Shepard interpolation using variational transition state theory. An example of a reaction we will work on is the gas-phase hydrogen abstraction reaction of hydroperoxyl radical with n-butanol. The overarching goal of this research program is "The development of a validated, predictive, multi-scale combustion modeling capability to optimize the design and operation of evolving fuels in advanced engines for transportation applications." In identifying this goal, it is recognized that drastic changes in the fuel constituents and operational characteristics of energy conversion devices are needed over the next few decades as the world transitions away from petroleum-derived transportation fuels. Conventional empirical approaches to developing new engines and certifying new fuels have only led to incremental improvements, and as such they cannot meet these enormous challenges in a timely, cost-effective manner. Achieving the required high rate of innovation will require computer-aided design, as is currently used to design the aerodynamically efficient wings of airplanes and the molecules in ozone-friendly refrigerants. The diversity of alternative fuels, including biomass-derived fuels, and the corresponding variation in their physical and chemical properties, coupled with simultaneous changes in energy conversion device design/control strategies needed to improve efficiency and reduce emissions, pose immense technical challenges. These challenges are particularly daunting since energy conversion efficiencies and exhaust emissions are governed by coupled chemical and transport processes at multiple length scales ranging from electron excitation to molecular rearrangements to nanoscale particulate formation to turbulent fuel/air mixing. Fortunately, recent advances in quantum chemistry, chemical kinetics, reactive flow simulation, high-performance computing, and experimental diagnostics suggest that first-principles-based predictive tools for optimum integration of energy conversion/control methodologies and new fuel compositions are possible.

10. Nanodusty plasmas and silane chemistry: I was involved in the project of nanodusty plasmas. Plasmas that contain dispersed particulates—“dusty plasmas”—are ubiquitous in the universe and important in industry. Dusty plasmas involve many fascinating phenomena that are not found in either neutral aerosols or in plasmas that do not contain particulates. Silane has been the most studied nucleating chemical system in plasmas. Silane plasmas are of special interest because they are prone to gas-phase nucleation, and they are widely used to grow microcrystalline silicon for electronics and amorphous hydrogenated silicon for photovoltaics, as well as, more recently, silicon nanocrystals that show promise for photovoltaics and photonics. Mass spectrometry studies demonstrated that silicon hydride anion clusters can grow to large sizes (several tens of Si atoms) in silane plasmas, while neutral and cation clusters are limited to smaller sizes. Our focus is on plasmas containing very small particles, less than 100 nm in diameter because particulates of this size are a major source of contamination of wafers in semiconductor processing. These contaminant particulates include nanoparticles generated by gas-phase nucleation in the chemically reacting plasmas used for thin film deposition and etching. As microelectronics feature sizes have shifted deeper into the nanoscale regime, the need to avoid contaminant nanoparticles has become more critical, and a practical goal of our work is to understand the mechanisms (nanoparticle nucleation, growth, charging, and transport in plasmas) for such particle formation and growth so that these contaminants can be avoided. In one of our works in this project, a recently proposed multistructural statistical thermodynamic method is used to show the importance of multiple structures and torsional anharmonicity in determining the thermodynamic properties of silicon hydride clusters, which are important both in plasmas and in thermally driven systems. The calculations are performed using all of the conformational structures of each molecule or radical by employing the multi-structural quasiharmonic approximation (MS-QH) and also by including torsional potential anharmonicity (MS-T). Our results indicate that the entropic effect on the thermochemistry of these clusters is huge and are dominated by multistructural effects. The entropic effect of multiple structures is also expected to be important for other kinds of chain molecules, and its effect on nucleation kinetics is expected to be large. This results in a publication in J. Am. Chem. Soc. in 2014. The second work in this project published in Phys. Chem. Chem. Phys. highlights some reaction mechanisms of early steps in the growth of nanodusty particles.

11. Computational Drug and Gene Delivery: In recent years, paramount interests have grown upon various ways to deliver drugs and genes inside the body. The term “drug and gene delivery” refers to the approaches, formulations, technologies, and systems for transporting a pharmaceutical compound in the body as needed to safely achieve the therapeutic effect. It is possible to design new therapies by controlling the precise level and location of a given drug, which in turn, reduces the side effects as well as lowering their doses. From computational point of view, it is highly desirable to estimate the binding and dynamics between drugs and their carriers in order to better understand their mechanism of action. The present project aims to achieve this feat. We have a particular interest in studying interaction of drugs that inhibit the growth of cancer cells with several carriers such as proteins, dendrimers, etc. In this project, we will also study the mechanism of formation of multifunctional tadpoles, nanorods and nanoworms. We started our project by studying the physical mechanism underlying the interactions of anticancer drugs with dendrimers. Peptide dendrimers are macromolecules with the structure composed of branches and a core formed by amino acids linked via peptide/amide bonds, with potential applications in cancer therapy and drug delivery. The dendrimers studied here were synthesized and used to understand the solubility, permeability and deposition of anticancer drugs through the skin. Our computational results demonstrate that the dendrimers we used here have potential applications in cancer therapy and drug delivery. In the next part of the project, we will explore mechanisms of the interactions of more complex anti-cancer drugs like tegafur, methotrexate, etc. and proteins like lysozyme, si-RNA, etc. with peptide dendrimers and other polymers of interest. In this regard, we already started to estimate the bindings and dynamics of egg-white lysozyme and poly (ethylene glycol) methyl ether acrylate-b-poly(carboxyethyl acrylate) (PEGMEA-b-PCEA). Experimentally it has been shown that the interaction of lysozyme with PEGMEA forms polyion complex micelles, which were designed as cancer therapeutic carriers for protein drugs. Later on, in our project, we will explore the mechanism for the binding of si-RNA with PEGMEA-b-PCEA. We are also interested in the simulation of multifunctional tadpoles. These are intriguing class of structures with wide range of applications. In order to create such tadpoles, we need to understand the self-assembling of other nano-objects such as nanospheres, nanorods, nanoworms, nanovesicles, etc. In this part, our approach will be to simulate different nano-objects and then try to understand the self-assembling process adopting computational strategies.

12. Photoredox catalyst specificity for selective polymerization: In this project, we are trying to focus our attention in explaining the extreme specificity of photoredox catalysts, pheophorbide a (PheoA) towards dithiobenzoate under red light and zinc tetraphenylporphine (ZnTPP) towards trithiocarbonates under green light irradiation. The photoredox catalyst, PheoA has this unique specificity to a single RAFT agent, CPADB, compared to other such agents and we are using quantum mechanics as the prime investigating tool. This remarkable selectivity is actually exploited for preparing controlled polymer architectures.

13. Gas Phase Reaction Kinetics: In this project, I will be performing electronic structure calculations of radical – molecule and radical – radical reactions and use different reaction rate theories, viz. Transition-State theory, Master Equations simulations to calculate rection rate coefficient over wide temperature and pressure conditions and compare results with experimental observations performed in the group.

14. Mechanism and kinetic studies of the autoxidation of anthropogenic voltaic organic compounds (AVOCs): Volatile organic compounds (VOCs) are organic chemicals with high vapor pressure at room temperature. They are of paramount interest due to their role in the formation of secondary organic aerosols. In this project, we are interested in anthropogenic VOCs (AVOCs) for which although we have preliminary experimental results that reveals that they can autoxidize, however, detailed mechanism of the process remains a mystery. To unravel this, we will be performing computational investigation along with complimentary mass-spectrometric analyses. AVOCs form peroxy radical, RO2, which undergoes autoxidation process thereby enabling the formation of aerosol precursor. These reactions are extremely fast and can occur at sub-second atomic scales. For electronic structure calculations, we used DFT and coupled cluster approaches implemented in GAUSSIAN, ORCA, and MOLPRO. For the kinetics, we will be using master-equation solver like MESMER and MULTIWELL to estimate the rate constants.