164 research outputs found
Addressing Challenges of Identifying Geometrically Diverse Sets of Crystalline Porous Materials
No full textLSMOMartin, Richard Luis Smit, Berend Haranczyk, Maciej9th International Conference on Chemical Structures (ICCS)Jun 05-09, 2011Noordwijkerhout, NETHERLAND
Adsorption and diffusion in zeolites: the pitfall of isotypic crystal structures
No full textLSMOZimmermann, Nils E. R. Haranczyk, Maciej Sharma, Manju Liu, Bei Smit, Berend Keil, Frerich J
Chemical Hieroglyphs: Abstract Depiction of Complex Void Space Topology of Nanoporous Materials
No full textIn general, most porous materials are so complex that structural information cannot be easily observed with 3D visualization tools. To address this problem, we have developed a special abstract 2D representation to depict all important topological features and geometrical parameters. Our approach involves reducing these structures based on symmetry and perceived building blocks to a compressed, graph representation that allows for quick structure analysis, classification, and comparison. © 2010 American Chemical Society.LSMOTheisen, Kevin Smit, Berend Haranczyk, MaciejU.S. Department of Energy [DE-ACO2-05CH11231]; DOE Office of Basic Energy Sciences ; Office of Advanced Scientific Computing Research [CSNEW918]; U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences [DE-SC0001015]We would like to thank Prof. Vladislav Blatov and Prof. Davide Proserpio for provision of the zeolite structures contained in IZA database in a format suitable for the TOPOS package as well as their invaluable help regarding its use. M.H. is a 2008 Seaborg Fellow at Lawrence Berkeley National Laboratory. This research was supported in part (to M.H.) by the U.S. Department of Energy under contract DE-ACO2-05CH11231. This work was also supported in part (to M.H.) jointly by DOE Office of Basic Energy Sciences and the Office of Advanced Scientific Computing Research through SciDAC project #CSNEW918 entitled "Knowledge guided screening tools for identification of porous materials for CO2 separations". K.T. and B.S. were supported as part of the Center for Gas Separations Relevant to Clean Energy Technologies, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0001015
Computational identification of organic porous molecular crystals
No full textMost nanoporous solids, such as metal-organic frameworks and zeolites, are composed of extended three-dimensional covalent or coordination bond networks. Nevertheless, an increasing number of porous molecular crystals have been reported that display surface areas and separation efficiencies rivaling those of conventional porous materials. In this investigation, a geometry-based analysis and molecular simulations were used to screen over 150000 organic molecular crystal structures, resulting in the identification of 481 potential organic porous molecular crystals, a testament to the rarity of these materials. Subsequently, we have computed the surface area and pore dimensions of these structures. This computer-generated database has been used to uncover a number of trends and properties that had not previously been quantified due to the limited number of reported porous molecular crystals. Finally, we have used machine learning to show that the van der Waals surface area and other related descriptors of molecular size are the molecular properties best able to predict a crystal's propensity to form structural voids, which are strong indicators of permanent porosity. We posit that the identified database is a promising resource for discovering candidate structures for gas-separation applications and providing general design guidelines for the production of new porous crystals.Jack D. Evans, David M. Huang, Maciej Haranczyk, Aaron W. Thornton, Christopher J. Sumby and Christian J. Doona
Methane storage capabilities of diamond analogues
No full textMethane can be an alternative fuel for vehicular usage provided that new porous materials are developed for its efficient adsorption-based storage. Herein, we search for materials for this application within the family of diamond analogues. We used density functional theory to investigate structures in which tetrahedral C atoms of diamond are separated by -CC- or -BN- groups, as well as ones involving substitution of tetrahedral C atoms with Si and Ge atoms. The adsorptive and diffusive properties of methane are studied using classical molecular simulations. Our results suggest that the all-carbon structure has the highest volumetric methane uptake of 280 VSTP/V at p = 35 bar and T = 298 K. However, it suffers from limited methane diffusion. Alternatively, the considered Si and Ge-containing analogies have fast diffusive properties but their adsorption is lower, ca. 172-179 VSTP/V, at the same conditions. © 2013 the Owner Societies.LSM
Zeolite screening for the separation of gas mixtures containing SO2, CO2 and CO
No full textWe used a combination of experiments and molecular simulations to investigate at the molecular level the effects of zeolite structure on the adsorption and diffusion of sulfur dioxide, carbon dioxide and carbon monoxide as well as separation processes of their mixtures. Our study involved different zeolite topologies and revealed numerous structure–property trends depending on the temperature and pressure conditions. Sulfur dioxide, which has the strongest interactions with zeolites due to its size and polarity, showed the largest adsorption across investigated temperatures and pressures. Our results indicate that structures with channel-type pore topology and low pore volume are the most promising for selective adsorption of sulfur dioxide over carbon dioxide and carbon monoxide under room conditions, while structures with higher pore volume exhibit better storage capacity at higher pressure. Our results emphasize the need for considering both adsorption and diffusion processes in the selection of the optimal structure for a given separation process. Our findings help to identify the best materials for effective separation processes under realistic operating conditions.This work was supported by the Spanish “Ministerio de Ciencia
e Innovación” (CTQ2010-16077/BQU), and the European
Research Council through an ERC Starting Grant (ERC-StG’11
RASPA-project). A. Martín-Calvo thanks the Spanish
“Ministerio de Educación” for her predoctoral fellowship. M.
Haranczyk was supported by the Nanoporous Materials
Genome Center for the U.S. Department of Energy, Office of
Basic Energy Sciences, Division of Chemical Sciences,
Geosciences and Biosciences under Award DE-FG02-
12ER1636.Peer reviewe
Computationally-guided synthetic control over pore size in isostructural porous organic cages
No full textThe physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal-organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of cage molecule, CC3, in a systematic way by introducing methyl groups into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure–energy landscape of a CC15-R binary co-crystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy–structure–function maps
Comparison of similarity coefficients for clustering and compound selection
No full textRecent studies into the use of a selection of similarity coefficients, when applied to searches of chemical databases represented by binary fingerprints, have shown considerable variation in their retrieval performance and in the sets of compounds being retrieved. The main factor influencing performance is the density distribution of the bitstrings for the active class, a feature which is closely related to molecular size. If this is the case when these coefficients are applied to similarity searches, then we would expect considerable variation in performance when applied to dissimilarity methods, namely clustering and compound selection. Here we report on several studies which have been undertaken to investigate the relative performance of 13 association and correlation coefficients, which have been shown to exhibit complementary performance in similarity searches, when applied to hierarchical and nonhierarchical clustering methods and to a compound selection methodology. Results suggest that the correlation coefficients perform consistently well for clustering and compound selection, as does the Baroni-Urbani/Buser association coefficient. Surprisingly, these often outperform the Tanimoto coefficient, while the Simple Match (effectively the complement of the Squared Euclidean Distance) performs very poorly
Combinatorial-computational-chemoinformatics (C<sup>3</sup>) approach to finding and analyzing low-energy tautomers
No full textFinding the most stable tautomer or a set of lowenergy tautomers of molecules is critical in many aspects of molecular modelling or virtual screening experiments. Enumeration of low-energy tautomers of neutral molecules in the gas-phase or typical solvents can be performed by applying available organic chemistry knowledge. This kind of enumeration is implemented in a number of software packages and it is relatively reliable. However, in esoteric cases such as charged molecules in uncommon, non-aqueous solvents there is simply not enough available knowledge to make reliable predictions of low energy tautomers. Over the last few years we have been developing an approach to address the latter problem and we successfully applied it to discover the most stable anionic tautomers of nucleic acid bases that might be involved in the process of DNA damage by low-energy electrons and in charge transfer through DNA. The approach involves three steps: (1) combinatorial generation of a library of tautomers, (2) energy-based screening of the library using electronic structure methods, and (3) analysis of the information generated in step (2). In steps 1-3 we employ combinatorial, computational and chemoinformatics techniques, respectively. Therefore, this hybrid approach is named " Combinatorial* Computational*Chemoinformatics", or just abbreviated as C3 (or C-cube) approach. This article summarizes our developments and most interesting methodological aspects of the C3 approach. It can serve as an example how to identify the most stable tautomers of molecular systems for which common chemical knowledge had not been sufficient to make definite predictions. © The Author(s) 2010.</p
Comparison of nonbinary similarity coefficients for similarity searching, clustering and compound selection
No full textSeveral recent studies have compared the relative performance of a selection of similarity coefficients when applied to chemical databases represented by binary fingerprints. Considerable variation in performance, when used for (dis)similarity-based techniques, such as similarity searching, database clustering, and dissimilarity-based compound selection, has been reported, the reasons for which are closely related to molecular size. For many of these similarity coefficients, an alternative form can be derived which is applicable to sets of nonbinary data, such as calculated or measured physicochemical properties, or counts of substructural fragments. Here we report on several studies which have been undertaken to investigate the relative performance of twelve coefficients when applied to nonbinary data using such (dis)similarity-based techniques. Results suggest that no single coefficient is appropriate for all methodologies investigated and that the size bias detected with binary data is not as apparent when the data and, hence, coefficient are nonbinary in nature
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