Research Experiences
Development of coordination-based models (Physics-based model)
In this area of research, we have extended the development of coordination based known as α-scheme model for catalysis and/or material science. The developed model is highly useful to understand catalysis and screen active catalysts for various useful reactions. The major developments are in classification of hydrocarbons and correlation among various metals at a specific coordination environment. The classification of hydrocarbons and correlation among various metals can be used to predict the adsorbate binding energies on-the-fly very accurately. These developments are based on the coordination number, bond order and surface site stability.
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Understanding of catalyst deactivation processes (Sintering)
In collaboration, we have investigated the fundamental of autocatalysts in vehicle exhaust which needs to be active as well as stable under harsh reaction environment. The commonly used autocatalysts are platinum group elements and hence highly expensive. We need to reduce catalyst deactivation or find an alternate cheap catalysts for the reaction. The loss of catalytic activity is due to particle growth. Hence, to prevent deactivation we need to first understand the reason behind the deactivation processes. We have collaborated with various experimental groups and investigated the reason behind the catalyst deactivation processes and possible ways to mitigate.
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Machine learning aided heterogeneous catalysis (CO2RR and HER)
We have screened a huge number of heterogeneous catalysts for selective hydrogenation of CO2 to methanol and hydrogen evolution reaction (HER) using machine learning. In these studies we have considered microstructure-based approaches as an input feature and predicted various adsorbate binding energies which are relevant for selective product formation. We have considered pure metal-based systems to high entropy alloys of various metals. Various stability as well as reactivity related parameters were included during screening of active and selective catalysts using machine learning-based approaches.
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Heterogeneous CO2 reduction reactions (Modeling of catalysts)
We have modeled various efficient and stable heterogeneous catalysts for CO2 reduction to useful products such as carbon monoxide, methanol, methane, ethylene, ethanol, dimethyl ether and so on. The parent structure of the model catalysts are Cu. The modeling of Cu-based nanoparticles were studied in detail and investigated the mechanism as well as suggested the further ways to improve the catalytic activity as well as stability. In all the cases, we have compared our results with earlier reports and explained using atomistic insights. It is noteworthy to mention that the surface facets, doping, additives, synergistic effects are responsible for selective product formations.
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Catalytic up upgradation of ethanol to butanol (Fuel additive)
Butanol can be used directly as a fuel additive and hence catalytic upgrdation of ethanol to butanol is a highly desirable reaction. In this context, we have investigated mechanism and modeled efficient catalysts for the catalytic conversion of ethanol to butanol. The considered catalysts are Mn(I)-based homogeneous catalysts and Cu(111) surface with Li promoter in the subsurface layer. The mechanism of the reaction can be divided into three section such as dehydrogenation of ethanol to acetaldehyde, aldol condensation of acetaldehyde to crotonaldehyde and crotonaldehyde hydrogenation to butanol.
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N-H functionality (Revised Noyori type mechanism)
CO2 reduction reaction is highly complex due to its multistep multiproduct nature. The major problem related to CO2 reduction reactions is activation of CO2. We have investigated the detailed mechanistic investigation of various CO2 reduction reactions and explained the reason behind the catalytic activity. In molecular catalysis we have reported the effect of N-H functionality in the ligand sphere which don't participate in the reaction it only assist the reaction via stabilization of the formate intermediate. The calculated reaction free energy profile diagram support our hypothesis and it is important to mention the importance of non covalent interaction in catalysis.
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Electrochemical molecular catalysis (Redox ligand with Mn)
CO can used as a fundamental building block for the formation of various useful products. Hence, the formation of CO2 to CO can give a useful possibilities to be investigated in detail. We have investigated, electrochemical synthesis of CO from CO2 using homogeneous catalysts. In one case, we have investigated the role of function group attached with the ligand sphere whereas in another study we have investigated the half-sandwich based catalysts and effect of solvents. The studies show the promising approaches for the electrochemical synthesis of CO from CO2 by altering ligand sphere, solvent and type of functional attached with the ligand.
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Mechanistic insights in molecular catalysis (Carbon neutrality)
Identifying the most plausible mechanism for any reaction is highly valuable to gain insights into the rate determining step and possible ways to increase rate of the reaction and find out the efficient catalysts. In this context, we majorly studies various CO2 hydrogenation reactions using earth abundant metal-based catalysts and compared their results with active metal-based catalysts. The reported results show the importance of hydride transfer and heterolytic H2 cleavage in case of hydrogenation reactions. In most cases, heterolytic H2 cleavage is the rate determining step. The possible ways to improve catalytic activity is ligand sphere interaction.
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Nitrogen reduction reaction (Electrochemical)
We have modeled various Fe-based catalysts for nitrogen reduction reaction (NRR) to ammonia computationally. The model catalysts are various surface and nanoparticles. In all the cases various mechanistic pathways have been considered such as associative and dissociative pathways. The calculated energies of the potential determine steps show that the modeled catalysts are efficient for ammonia production. In all the cases, activation of N2 is the most difficult step due to strong bond between two nitrogen atom in N2 molecule. However, the future direction of this direction will be the reducing the rate of competitive HER compared to NRR.
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2D layered hybrid perovskites (Solar cell)
2D layered hybrid perovskites have attracted huge attention due to their electronic structures and properties. In this context, we have studied various 2D layered hybrid perovskites and investigated the effect of spacer cations. The spacer cations can influence significantly in the optoelectronic properties by effecting structural and electronic properties of the material and is a useful approach to model efficient 2D layered hybrid perovskites. Sometime the spacer cation contribute in the band structure significantly and dominate other inorganic atoms which is an interesting observation from our end.
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Machine learning in molecular catalysis (CO2 to HCOOH)
Discovery of earth abundant molecular metal-catalysts can be highly valuable. In search of this, we have selected Mn(I)-based molecular catalysts for CO2 hydrogenation by varing the ligand sphere. In case of molecular catalysts ligand sphere can play the vital role in deterring the catalytic activity by their steric, inductive and electronegative effects. The ligand encoded input features have been used in ML and screened huge number of Mn(I) catalysts for CO2 to HCOOH where hydride transfer and heterolytic H2 cleavage are the two important steps. The study select a range of active catalysts where energy for hydride transfer as well as heterolytic H2 cleavage is optimal.
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Collaboration work with experimentalists
Along with our computational investigations we have actively collaborated with experimentalists to validate our hypothesis or explain the experimentally observed outcomes using computational insights. My collaborative works span from sensing of various materials to catalysis. In one case it is sensing of volatile organic contaminants. Others are degradation of harmful mercury from the environment, mechanistic insights of C-H bond activation and dehydrogenation reactions. Lastly, I have collaboration in the field of molecular organic frameworks to understand their properties.
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Teaching Experiences
Quantum chemistry
Graduate Student Instructor
Indian Institute of Technology Indore
2018-2019
Chemistry practical
Graduate Student Instructor
Indian Institute of Technology Indore
2017-1018
Freelance tutor
Teaching school and college students
Doubt solving
2012-2017