Pradeep Kumar Pal supervised by Prof. Deva Priyakumar U received  his doctorate in  Computational Natural Sciences (CNS). Here’s a  summary of his research work on Computational Study of Gold Nanoclusters, their Catalytic Activity and other Catalytic Processes:

Computational methods have profoundly impacted the field of chemistry by providing essential tools to model and study complex chemical systems and processes. These methods make use of advanced algorithms, mathematical models, and implemented on high-performance computing to simulate the behavior of molecules, reactions, and materials at various scales, from atomistic to macroscopic levels. Computational techniques have become essential in modern chemical research by bridging the gap between theoretical chemistry and experimental observations. One of the major applications of computational methods is to predict the properties and behavior of chemical systems. Quantum chemical calculations, such as Density Functional Theory (DFT) and ab-initio methods, aid scientists to analyze electronic structures, molecular geometries, and reaction mechanisms with high accuracy. These analysis are important for understanding fundamental chemical reactions like bond formation, energy transfer and catalysis, which are often critical to observe experimentally. Additionally, molecular dynamics (MD) simulations enable researchers to explore the time-dependent behavior of molecules, providing comprehensive information about molecular interactions, diffusion, and conformational changes. This is vital in biochemistry, where MD simulations have helped to demonstrate protein folding, membrane dynamics and drug binding. Computational methods have also played a key role in material science, where they are used to design and optimize new material with desired properties, like polymers, catalysts and nano materials. By predicting the performance of a materials before chemical synthesis, such methods save time and resources in their development process. The role of computational chemistry in drug discovery is indispensable. It enables virtual screening of huge chemical spaces, by predicting the molecular interactions with biological targets, and optimization of drug candidates. This facilitates the identification of potential therapeutics and reduces the cost of experimental validation. Techniques like quantum mechanics/molecular mechanics (QM/MM) combine the detailed accuracy of quantum mechanics with the cost efficiency of molecular mechanics, allowing the study of large biomolecules like enzymes with accuracy and computational feasibility. The amalgamation of machine learning (ML) into computational chemistry has improved the predictive capabilities by analyzing large datasets to identify patterns and relationships in chemical properties. This synergy has allowed faster predictions in drug discovery and material sciences. Computational chemistry and its methods have revolutionized chemistry by providing efficient, accurate and cost effective approaches to model chemical systems and processes. They have improved our understanding of molecular behavior, and facilitated the design of new materials and drugs. This work demonstrated in this thesis proposal focuses on the application of the various computational methods to the understanding of molecular properties of newly synthesized molecules and various metal clusters, and modeling various types of catalysis reactions. The use of gold nanoclusters (AuNC) in complex reactions involving large substrates and supporting agents is an active field of interest and molecular study of the catalytic role or AuNC in many reactions is still unexplored. The thesis proposal lays key focus on the discussion of pure and copper doped 13 atom AuNC and prediction of their key molecular properties. It discusses the structure property relationship of the entire range of AumCun clusters where m+n = 13. The work also demonstrates the comparative catalytic activity of pure and doped Cu and Au rich 13 atom clusters in the aerobic oxidation of benzyl alcohol to benzaldehyde. The work then transitions to the study of various types of catalytic reactions such as photocatalysis of the cycloaddition of CO2 and epoxide by Zn-salen derivatives, kinetic vs thermodynamic controlled asymmetric Henry reaction in the synthesis of β-nitroalcohols catalysed by Baliospermum montanum, synthesis of Aryl ketones by activating toluene, and activation of esters to undergo annulative π-extension lactonization (APEX-LAC). 

October 2025