Jihan Kim

In silico screening of carbon-capture materials

One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO(2) from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies.

Mapping of Functional Groups in Metal-Organic Frameworks

Mapping Molecular Linkers In metal-organic framework compounds, inorganic centers (metal atoms or clusters) are linked by bidentate organic groups. Normally, the same group is used throughout the structure, but recently, synthesis with linkers bearing different functional groups has produced well-defined materials. Kong et al. (p. 882, published online 25 July) combined solid-state nuclear magnetic resonance and molecular simulations to map the distributions of linkers in these materials as random, well-mixed, or clustered. Solid-state nuclear magnetic resonance and simulations map the distribution of linking groups in metal-organic frameworks. We determined the heterogeneous mesoscale spatial apportionment of functional groups in a series of multivariate metal-organic frameworks (MTV-MOF-5) containing BDC (1,4-benzenedicarboxylate) linkers with different functional groups—B (BDC-NH2), E (BDC-NO2), F [(BDC-(CH3)2], H [BDC-(OC3H5)2], and I [BDC-(OC7H7)2]—using solid-state nuclear magnetic resonance measurements combined with molecular simulations. Our analysis reveals that these methods discern between random (EF), alternating (EI and EHI), and various cluster (BF) forms of functional group apportionments. This combined synthetic, characterization, and computational approach predicts the adsorptive properties of crystalline MTV-MOF systems. This methodology, developed in the context of ordered frameworks, is a first step in resolving the more general problem of spatial disorder in other ordered materials, including mesoporous materials, functionalized polymers, and defect distributions within crystalline solids.

The materials genome in action: Identifying the performance limits for methane storage

Analogous to the way the Human Genome Project advanced an array of biological sciences by mapping the human genome, the Materials Genome Initiative aims to enhance our understanding of the fundamentals of materials science by providing the information we need to accelerate the development of new materials. This approach is particularly applicable to recently developed classes of nanoporous materials, such as metal–organic frameworks (MOFs), which are synthesized from a limited set of molecular building blocks that can be combined to generate a very large number of different structures. In this Perspective, we illustrate how a materials genome approach can be used to search for high-performance adsorbent materials to store natural gas in a vehicular fuel tank. Drawing upon recent reports of large databases of existing and predicted nanoporous materials generated in silico, we have collected and compared on a consistent basis the methane uptake in over 650 000 materials based on the results of molecular simulation. The data that we have collected provide candidate structures for synthesis, reveal relationships between structural characteristics and performance, and suggest that it may be difficult to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage.

Understanding CO2 Dynamics in Metal–Organic Frameworks with Open Metal Sites

Hopping along: Metal-organic frameworks such as Mg-MOF-74 possess open metal sites that interact strongly with CO2. Molecular simulations reveal detailed CO2 dynamics (hops between metal sites and localized fluctuations), which can be used to accurately explain the experimentally measured 13C NMR chemical shift anisotropy pattern. Copyright

Predicting Large CO2 Adsorption in Aluminosilicate Zeolites for Postcombustion Carbon Dioxide Capture

Large-scale simulations of aluminosilicate zeolites were conducted to identify structures that possess large CO(2) uptake for postcombustion carbon dioxide capture. In this study, we discovered that the aluminosilicate zeolite structures with the highest CO(2) uptake values have an idealized silica lattice with a large free volume and a framework topology that maximizes the regions with nearest-neighbor framework atom distances from 3 to 4.5 Å. These predictors extend well to different Si:Al ratios and for both Na(+) and Ca(2+) cations, demonstrating their universal applicability in identifying the best-performing aluminosilicate zeolite structures.

Highly Enhanced Gas Adsorption Properties in Vertically Aligned MoS2 Layers

In this work, we demonstrate that gas adsorption is significantly higher in edge sites of vertically aligned MoS2 compared to that of the conventional basal plane exposed MoS2 films. To compare the effect of the alignment of MoS2 on the gas adsorption properties, we synthesized three distinct MoS2 films with different alignment directions ((1) horizontally aligned MoS2 (basal plane exposed), (2) mixture of horizontally aligned MoS2 and vertically aligned layers (basal and edge exposed), and (3) vertically aligned MoS2 (edge exposed)) by using rapid sulfurization method of CVD process. Vertically aligned MoS2 film shows about 5-fold enhanced sensitivity to NO2 gas molecules compared to horizontally aligned MoS2 film. Vertically aligned MoS2 has superior resistance variation compared to horizontally aligned MoS2 even with same surface area exposed to identical concentration of gas molecules. We found that electrical response to target gas molecules correlates directly with the density of the exposed edge sites of MoS2 due to high adsorption of gas molecules onto edge sites of vertically aligned MoS2. Density functional theory (DFT) calculations corroborate the experimental results as stronger NO2 binding energies are computed for multiple configurations near the edge sites of MoS2, which verifies that electrical response to target gas molecules (NO2) correlates directly with the density of the exposed edge sites of MoS2 due to high adsorption of gas molecules onto edge sites of vertically aligned MoS2. We believe that this observation extends to other 2D TMD materials as well as MoS2 and can be applied to significantly enhance the gas sensor performance in these materials.

Superior Chemical Sensing Performance of Black Phosphorus: Comparison with MoS2 and Graphene.

Superior chemical sensing performance of black phosphorus (BP) is demonstrated by comparison with MoS2 and graphene. Dynamic sensing measurements of multichannel detection show that BP displays highly sensitive, selective, and fast-responsive NO2 sensing performance compared to the other representative 2D sensing materials.

Large-scale Screening of Zeolite Structures for CO2 Membrane Separations

We have conducted large-scale screening of zeolite materials for CO2/CH4 and CO2/N2 membrane separation applications using the free energy landscape of the guest molecules inside these porous materials. We show how advanced molecular simulations can be integrated with the design of a simple separation process to arrive at a metric to rank performance of over 87,000 different zeolite structures, including the known IZA zeolite structures. Our novel, efficient algorithm using graphics processing units can accurately characterize both the adsorption and diffusion properties of a given structure in just a few seconds and accordingly find a set of optimal structures for different desired purity of separated gases from a large database of porous materials in reasonable wall time. Our analysis reveals that the optimal structures for separations usually consist of channels with adsorption sites spread relatively uniformly across the entire channel such that they feature well-balanced CO2 adsorption and diffusion properties. Our screening also shows that the top structures in the predicted zeolite database outperform the best known zeolite by a factor of 4-7. Finally, we have identified a completely different optimal set of zeolite structures that are suitable for an inverse process, in which the CO2 is retained while CH4 or N2 is passed through a membrane.

New materials for methane capture from dilute and medium-concentration sources

Methane (CH4) is an important greenhouse gas, second only to CO2, and is emitted into the atmosphere at different concentrations from a variety of sources. However, unlike CO2, which has a quadrupole moment and can be captured both physically and chemically in a variety of solvents and porous solids, methane is completely non-polar and interacts very weakly with most materials. Thus, methane capture poses a challenge that can only be addressed through extensive material screening and ingenious molecular-level designs. Here we report systematic in silico studies on the methane capture effectiveness of two different materials systems, that is, liquid solvents (including ionic liquids) and nanoporous zeolites. Although none of the liquid solvents appears effective as methane sorbents, systematic screening of over 87,000 zeolite structures led to the discovery of a handful of candidates that have sufficient methane sorption capacity as well as appropriate CH4/CO2 and/or CH4/N2 selectivity to be technologically promising.

Large-Scale Computational Screening of Zeolites for Ethane/Ethene Separation

Large-scale computational screening of thirty thousand zeolite structures was conducted to find optimal structures for separation of ethane/ethene mixtures. Efficient grand canonical Monte Carlo (GCMC) simulations were performed with graphics processing units (GPUs) to obtain pure component adsorption isotherms for both ethane and ethene. We have utilized the ideal adsorbed solution theory (IAST) to obtain the mixture isotherms, which were used to evaluate the performance of each zeolite structure based on its working capacity and selectivity. In our analysis, we have determined that specific arrangements of zeolite framework atoms create sites for the preferential adsorption of ethane over ethene. The majority of optimum separation materials can be identified by utilizing this knowledge and screening structures for the presence of this feature will enable the efficient selection of promising candidate materials for ethane/ethene separation prior to performing molecular simulations.