Dataset Information

Bottom-up Formation of Carbon-Based Structures with Multilevel Hierarchy from MOF-Guest Polyhedra.

ABSTRACT: Three-dimensional carbon-based structures have proven useful for tailoring material properties in structural mechanical and energy storage applications. One approach to obtain them has been by carbonization of selected metal-organic frameworks (MOFs) with catalytic metals, but this is not applicable to most common MOF structures. Here, we present a strategy to transform common MOFs, by guest inclusions and high-temperature MOF-guest interactions, into complex carbon-based, diatom-like, hierarchical structures (named for the morphological similarities with the naturally existing diatomaceous species). As an example, we introduce metal salt guests into HKUST-1-type MOFs to generate a family of carbon-based nano-diatoms with two to four levels of structural hierarchy. We report control of the morphology by simple changes in the chemistry of the MOF and guest, with implications for the formation mechanisms. We demonstrate that one of these structures has unique advantages as a fast-charging lithium-ion battery anode. The tunability of composition should enable further studies of reaction mechanisms and result in the growth of a myriad of unprecedented carbon-based structures from the enormous variety of currently available MOF-guest candidates.

SUBMITTER: Wang T

PROVIDER: S-EPMC5991782 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Bottom-up Formation of Carbon-Based Structures with Multilevel Hierarchy from MOF-Guest Polyhedra.

Wang Tiesheng T Kim Hyun-Kyung HK Liu Yingjun Y Li Weiwei W Griffiths James T JT Wu Yue Y Laha Sourav S Fong Kara D KD Podjaski Filip F Yun Chao C Kumar R Vasant RV Lotsch Bettina V BV Cheetham Anthony K AK Smoukov Stoyan K SK

Journal of the American Chemical Society 20180503 19

Three-dimensional carbon-based structures have proven useful for tailoring material properties in structural mechanical and energy storage applications. One approach to obtain them has been by carbonization of selected metal-organic frameworks (MOFs) with catalytic metals, but this is not applicable to most common MOF structures. Here, we present a strategy to transform common MOFs, by guest inclusions and high-temperature MOF-guest interactions, into complex carbon-based, diatom-like, hierarchi ...[more]

PMID: 29685030

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Project description:Deciphering complete networks of interactions between proteins is the key to comprehend cellular regulatory mechanisms. A significant effort has been devoted to expanding the coverage of the proteome-wide interaction space at molecular level. Although a growing body of research shows that protein docking can, in principle, be used to predict biologically relevant interactions, the accuracy of the across-proteome identification of interacting partners and the selection of near-native complex structures still need to be improved.In this study, we developed a new method to discover and model protein interactions employing an exhaustive all-to-all docking strategy. This approach integrates molecular modeling, structural bioinformatics, machine learning, and functional annotation filters in order to provide interaction data for the bottom-up assembly of protein interaction networks. Encouragingly, the success rates for dimer modeling is 57.5 and 48.7% when experimental and computer-generated monomer structures are employed, respectively. Further, our protocol correctly identifies 81% of protein-protein interactions at the expense of only 19% false positive rate. As a proof of concept, 61,913 protein-protein interactions were confidently predicted and modeled for the proteome of E. coli. Finally, we validated our method against the human immune disease pathway.Protein docking supported by evolutionary restraints and machine learning can be used to reliably identify and model biologically relevant protein assemblies at the proteome scale. Moreover, the accuracy of the identification of protein-protein interactions is improved by considering only those protein pairs co-localized in the same cellular compartment and involved in the same biological process. The modeling protocol described in this communication can be applied to detect protein-protein interactions in other organisms and pathways as well as to construct dimer structures and estimate the confidence of protein interactions experimentally identified with high-throughput techniques.

Dataset Information

Bottom-up Formation of Carbon-Based Structures with Multilevel Hierarchy from MOF-Guest Polyhedra.

Publications

Bottom-up Formation of Carbon-Based Structures with Multilevel Hierarchy from MOF-Guest Polyhedra.

Similar Datasets

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