Computational Design of Novel Catalysts for Sustainable Fuels
Computational Design of Novel Catalysts for Sustainable Fuels
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Research Areas
Research Areas
Catalytic Conversion of CO2 to Value-added Chemicals
Catalytic Conversion of CO2 to Value-added Chemicals
Converting CO2 into fuels or value-added products offers the dual benefit of reducing emissions and producing storable chemicals like methane, methanol, and formic acid. However, this process is complex, requiring catalysts to overcome significant kinetic barriers. Our project focuses on designing and optimizing catalysts through a combination of Density Functional Theory (DFT), Microkinetic Modeling (MKM), and Machine Learning (ML). We aim to develop detailed MKM models to analyze reaction kinetics, pathways, and rate-limiting steps, while leveraging ML to simulate and predict catalyst performance and reaction outcomes. This integrated approach seeks to enhance the efficiency of CO2 conversion into valuable C1 products like methane, syngas, and methanol, or C2 products like ethanol, offering significant environmental and industrial benefits.
Hydrogen Generation via Methane Pyrolysis in Molten Media
Hydrogen Generation via Methane Pyrolysis in Molten Media
Hydrogen has the potential to play an important cross-cutting role in a future low-carbon economy in India. Despite this promise, the conventional hydrogen production methods (electrolysis, methane reforming reaction) are either expensive (electrolysis) or produces CO/CO2 (reforming reaction). Interestingly, methane pyrolysis (CH4(g)→C(s)+2H2(g)) has the potential to generate CO2-free hydrogen from natural gas. We study the feasibility of methane activation and the resulting hydrogen generation by simulating the interactions between methane and different molten salts.
Greenhouse Gas Capture using Biochar
Greenhouse Gas Capture using Biochar
Biochar, a carbon-rich material from organic waste pyrolysis, is recognized by the IPCC as a scalable CO2 removal technology. With its high surface area, biochar adsorbs greenhouse gases (GHGs), influenced by properties like porosity and functional groups. However, the mechanisms behind GHG adsorption remain unclear. This study combines experimental and computational methods to investigate GHG (CO2, CH4, N2O) adsorption on biochar. It examines biochar from various feedstocks (e.g., crop waste, tree trimmings) produced under different conditions (e.g., temperatures, treatments like activation, doping) and uses DFT calculations to uncover molecular-level adsorption mechanisms. The findings aim to clarify structure-property relationships and support sustainable GHG mitigation technologies.
Collaborations
Collaborations
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