Computer simulations and multiscale modeling of nanoscale transport and phase transitions
Related Oral Presentation
Abstract ID: 715020
Title: Mechanistic Investigation of Semiquinone-Functionalized Å-Scale Graphene Nanopores for Carbon Capture Applications
Technical Skills
Computer Languages: MATLAB, Python, FORTRAN, Bash Scripting
Tools: GROMACS, Quantum ESPRESSO, Gaussian, Visual Molecular Dynamics, Avogadro, XCrySDen, PETREL
Skills: Statistical analysis, Optimization, Molecular Dynamics and Monte Carlo Simulations, First-principles electronic-structure calculations, Materials modeling, Data visualization, Fundamentals of Machine Learning, OOPS
Selected Awards
Research Experience
Indian Institute of Science (IISc), Bangalore (2019 – 2025) – Department of Chemical Engineering
Advisor: Prof. K. Ganapathy Ayappa.
Computational nanoscience and membrane-based separations. Developed molecular simulation frameworks and theoretical models to evaluate the performance of functionalized nanoporous graphene for water purification and bioethanol production. Demonstrated more than 25-fold enhancement in water evaporation flux from nanoporous graphene, with applications in energy-efficient seawater desalination. Led collaborative projects with EPFL, Switzerland, validating simulation results through large-scale experiments.
École Polytechnique Fédérale de Lausanne (EPFL), Switzerland (2020 – 2025) – Laboratory of Advanced Separations (collaboration)
Collaborator: Prof. Kumar Varoon Agrawal.
Nanoporous membranes for gas separations and model development. Collaborated with EPFL, Switzerland on various independent projects focused on gas separation using nanoporous graphene membranes. Conducted DFT calculations, molecular simulations, and free energy calculations to uncover selective transport mechanisms. Demonstrated >100 selectivity for CO₂/N₂, CO₂/O₂, and NH₃/N₂ separations, supported by experimental validation. Developed transition-state-theory-based and machine learning models to predict the permeation of O₂, CO₂, NH₃, N₂, and CH₄ molecules through functionalized graphene pores.
Indian Institute of Technology (IIT), Hyderabad (2016 – 2018) – Department of Chemical Engineering
Advisor: Prof. Saptarshi Majumdar.
Molecular simulations and soft matter systems. Investigated the physicochemical properties of gelatin as a biomaterial for drug delivery applications. Performed molecular dynamics simulations to examine gelatin stability in diverse solvent systems and ionic environments. Analysed hydrogen bonding and conformational dynamics under varying pH conditions and salt concentrations. Validated simulation results through comparison with experimental data obtained from small-angle X-ray scattering (SAXS).
ABSTRACT
Amid the broad array of separation technologies employed in chemical industries, liquid and gas mixture separations stand out due to their pivotal roles in addressing global resource scarcity, mitigating climate change and promoting sustainable energy solutions. Although conventional membrane-based techniques are widely used, they are often energy-intensive and heavily dependent on membrane material properties. This has led to growing interest in novel alternatives such as two-dimensional (2D) materials, which offer exceptional permeability and tunable selectivity owing to their atomic-scale thickness and chemical versatility.
In this study, we employ molecular dynamics simulations to investigate spontaneous evaporation through nanoporous graphene, a promising separation platform characterized by its atomic thinness, mechanical robustness, and chemical tunability. Advances in synthesis techniques now allow precise control over the pore size and functionalization of graphene membranes, making them ideal candidates for high-performance separations.
Our simulations reveal substantial enhancement in water evaporation flux through nanoporous graphene compared to evaporation across a bare liquid-vapor interface. This enhancement intensifies with decreasing pore size and is particularly pronounced for small, oxygen-functionalized nanopores, where flux enhancements exceeding 25-fold were observed. These findings, validated experimentally, represent some of the highest evaporation flux enhancements reported to date [1]. Extending this work, we investigated water evaporation from various salt solutions (LiCl, NaCl, and KCl). We found that cation-π interactions significantly modulate ion accumulation near the nanopore, with KCl solutions exhibiting the highest flux, followed by NaCl and LiCl. This ion-dependent behaviour diminishes at lower concentrations. Notably, hydroxyl-functionalized pores yielded 7–11-fold higher evaporation fluxes compared to the bare interface, with a 10.8-fold enhancement observed for 0.6 M NaCl - a composition similar to seawater. We further demonstrated that functionalized nanopores accelerate water-water hydrogen bond dynamics and reduce interfacial surface tension, thereby lowering the free energy barrier for evaporation without significantly disrupting ion hydration structures [2].
Motivated by these results, we explored the use of nanoporous graphene for ethanol-water separation. For mixtures containing 25-75 mol% ethanol, hydrogen-terminated nanopores achieved separation factors exceeding 100. This remarkable selectivity arises from the preferential adsorption of ethanol molecules at the pore interface, which excludes water and enhances ethanol flux. In the context of bioethanol production, evaporation fluxes through these nanopores surpassed those of conventional pervaporation membranes by over two orders of magnitude. Furthermore, for azeotropic ethanol–water mixtures, the membranes demonstrated both high flux (~107 g m⁻² h⁻¹) and exceptional separation performance, highlighting their potential for energy-efficient bioethanol recovery [3].
Beyond liquid-phase separations, we also evaluated nanoporous graphene for industrial gas mixture separations. Our simulations showed that oxygen-functionalized nanopores can achieve selectivities exceeding 100 for challenging separations such as CO₂/N₂, CO₂/O₂, and NH₃/N₂ - results that were further validated through collaborative experimental efforts. To complement these studies, we developed predictive models based on transition state theory and machine learning algorithms to estimate gas permeation rates across functionalized pores, enabling accelerated screening of pore chemistries and structures [4, 5].
Overall, these findings underscore the transformative potential of nanoporous graphene as a versatile membrane platform for both evaporation-based and gas-phase separations. While challenges remain in large-scale synthesis and process integration, our multiscale modeling and experimental validation efforts suggest that graphene nanopores hold great promise for next-generation, energy-efficient separation technologies.
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