(6ap) Computational Design of Crystalline Materials Toward Storage and Efficient Use of Energy

One of the greatest challenges that mankind is facing is to continue the development of technologies that improve our quality of life without depleting our energy resources.  At the center of addressing this challenge is the need to discover novel materials that allow us to develop processes and systems that make efficient use of energy.  The advent of nanotechnology has given us unprecedented access to the atomistic structure of matter and enabled the rational design of materials by precisely controlling their nanostructure.  My primary research interest is to use quantum and classical mechanics molecular simulations to (help) design the materials that will play pivotal roles in overcoming the bottlenecks related to energy consumption and/or storage in emerging technologies in areas as diverse as transportation, the chemical industry, and biomedicine. The goal is to capitalize on the link between properties/performance and nanoscale features.

This poster will provide an overview of my computational research work for the design of materials towards energy storage and/or efficient use of energy.  During my doctoral work, I sought to design a catalyst/support system that could selectively produce single-walled carbon nanotubes (SWCNTs) of the same chirality.  SWCNTs are tubular crystalline materials with outstanding chirality-dependent properties.  Therefore, chiral-selective nanotube synthesis is eagerly pursued to avoid energy-intensive separations methods to obtain the desired chirality for applications such as biomedical imaging and photovoltaics.  I investigated the nanotube growth mechanism to elucidate and discover ways that chirality could be controlled during synthesis, using reactive molecular dynamics (RMD) and density functional theory (DFT) methods.  I investigated the feasibility and relevant conditions under which one could take advantage of the catalyst nanoparticle structure to act as a template to the nascent nanotube, and thus provided useful synthesis guidelines to experts in nanotube synthesis.

During my first postdoctoral project, I sought to design metal-organic frameworks (MOFs) that could be used in vehicular tanks to store fuels such as natural gas and hydrogen in high enough quantities to allow practical driving ranges.  These gaseous fuels have specific energy contents (MJ/kg) superior to gasoline, but significantly lower energy density (MJ/L) at standard conditions, and thus their use currently requires energy-intensive compression.  However, natural gas and hydrogen represent promising cleaner alternatives to reduce dependence on oil, so their adsorption on porous materials is being actively explored.  MOFs are novel, remarkable, crystalline materials whose nanopore structure can be finely tuned by appropriate selection of essentially limitless possible combinations of inorganic “nodes” and organic “linkers.”  I used a variety of strategies for generating “crystal structures” and Monte Carlo simulations to calculate their adsorption properties. The goal was to establish performance limits (through data mining) for this class of materials and identify the best materials within these boundaries.  Through close collaboration with synthetic chemists, some of the best MOFs identified via simulation have been synthesized, and their promising adsorption characteristics have been experimentally confirmed.

My current postdoctoral research focuses on the computational component of a collaborative project with experts in synthetic chemistry and catalysis.  We aim to design hybrid MOF/nanoparticle catalysts for regioselective oxidation and/or hydrogenation toward the synthesis of commodity chemicals.  Designing highly selective catalysts can result in “greener” reactions by reducing the need for post-reaction separation processes, which typically account for the bulk of the energy cost of operating a chemical plant.  Mimicking the working mechanism of enzymes, the nanopores of the MOF component are expected to provide control on how the molecule “attacks” the surface of the nanoparticle component.  In this research, I integrate insights obtained from classical molecular dynamics (MD) about the dynamics of the reactants inside MOF nanopores with insights from DFT calculations about the reaction energetics for the transformation of reactants into products on the catalyst surface.  These calculations stand out from other DFT calculations in the literature in that the reactants are exposed to steric constraints using a novel faux-pore approach. 

Building on my expertise in materials science, catalysis, computational methods, and data mining, I plan to mainly focus my academic career on the computational design and discovery of materials and catalytic systems that will either enable us to reduce energy consumption through highly active and selective catalysts (likely drawing inspiration from nature’s enzymes), or directly use the required energy to convert reactants to products from abundant renewable sources such as in metal-oxide photocatalysts.

Doctoral Advisor:  Professor Perla B. Balbuena, Texas A&M University, College Station TX

Postdoctoral Advisor: Professor Randall Q. Snurr, Northwestern University, Evanston IL