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Gerbrand Ceder - One of the best experts on this subject based on the ideXlab platform.
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similarity of precursors in solid state synthesis as text mined from scientific literature
Chemistry of Materials, 2020Co-Authors: Wenhao Sun, Haoyan Huo, Olga Kononova, Ziqin Rong, Vahe Tshitoyan, Tiago Botari, Gerbrand CederAbstract:Author(s): He, T; Sun, W; Huo, H; Kononova, O; Rong, Z; Tshitoyan, V; Botari, T; Ceder, G | Abstract: Copyright © 2020 American Chemical Society. Collecting and analyzing the vast amount of information available in the Solid-State Chemistry literature may accelerate our understanding of materials synthesis. However, one major problem is the difficulty of identifying which materials from a synthesis paragraph are precursors or are target materials. In this study, we developed a two-step chemical named entity recognition model to identify precursors and targets, based on information from the context around material entities. Using the extracted data, we conducted a meta-analysis to study the similarities and differences between precursors in the context of Solid-State synthesis. To quantify precursor similarity, we built a substitution model to calculate the viability of substituting one precursor with another while retaining the target. From a hierarchical clustering of the precursors, we demonstrate that the "chemical similarity"of precursors can be extracted from text data. Quantifying the similarity of precursors helps provide a foundation for suggesting candidate reactants in a predictive synthesis model.
Zhenmeng Peng - One of the best experts on this subject based on the ideXlab platform.
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size dependent oxygen reduction property of octahedral pt ni nanoparticle electrocatalysts
Journal of Materials Chemistry, 2014Co-Authors: Changlin Zhang, Sang Youp Hwang, Zhenmeng PengAbstract:The size effect on the electrocatalytic property of octahedral Pt–Ni alloy nanoparticles in the oxygen reduction reaction (ORR) was studied by making particles with different sizes and conducting electrochemical measurements. Octahedral Pt–Ni nanoparticles on carbon support (Pt–Ni/C) were produced using a facile and surfactant-free Solid-State Chemistry method. Two groups of octahedral Pt–Ni/C, including Pt3Ni/C and Pt1.5Ni/C, with particle size ranging from around 4 to 8 nm were prepared. Both the ORR activity and the stability of the two group catalysts were studied, which exhibited varying dependence over the particle size. The different relationships between the Pt–Ni size and the ORR property were investigated and attributed to alterations in the particle electronic/geometric structure and the Ni leaching behaviour.
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solid state Chemistry enabled scalable production of octahedral pt ni alloy electrocatalyst for oxygen reduction reaction
Journal of the American Chemical Society, 2014Co-Authors: Changlin Zhang, Alexis Trout, Sang Youp Hwang, Zhenmeng PengAbstract:Although octahedral Pt–Ni alloy nanoparticles possess an excelling property in oxygen reduction reaction (ORR) and are of great potential as an electrocatalyst for polymer electrolyte membrane fuel cells (PEMFCs), mass production of the materials at low cost remains a big challenge. By combining the advantages of both Solid-State Chemistry and wet synthetic Chemistry, we developed one scalable, surfactant-free, and cost-effective method for producing octahedral Pt–Ni alloy nanoparticles on carbon support. The octahedral Pt–Ni samples were prepared with different compositions and studied for the ORR property. They exhibit a much improved reaction activity compared to the commercial catalyst. The experiments demonstrate an innovative strategy for preparing shaped metal nanoparticles and make significant progress in the ORR catalyst research.
Wenhao Sun - One of the best experts on this subject based on the ideXlab platform.
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similarity of precursors in solid state synthesis as text mined from scientific literature
Chemistry of Materials, 2020Co-Authors: Wenhao Sun, Haoyan Huo, Olga Kononova, Ziqin Rong, Vahe Tshitoyan, Tiago Botari, Gerbrand CederAbstract:Author(s): He, T; Sun, W; Huo, H; Kononova, O; Rong, Z; Tshitoyan, V; Botari, T; Ceder, G | Abstract: Copyright © 2020 American Chemical Society. Collecting and analyzing the vast amount of information available in the Solid-State Chemistry literature may accelerate our understanding of materials synthesis. However, one major problem is the difficulty of identifying which materials from a synthesis paragraph are precursors or are target materials. In this study, we developed a two-step chemical named entity recognition model to identify precursors and targets, based on information from the context around material entities. Using the extracted data, we conducted a meta-analysis to study the similarities and differences between precursors in the context of Solid-State synthesis. To quantify precursor similarity, we built a substitution model to calculate the viability of substituting one precursor with another while retaining the target. From a hierarchical clustering of the precursors, we demonstrate that the "chemical similarity"of precursors can be extracted from text data. Quantifying the similarity of precursors helps provide a foundation for suggesting candidate reactants in a predictive synthesis model.
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a map of the inorganic ternary metal nitrides
Nature Materials, 2019Co-Authors: Wenhao Sun, Elisabetta Arca, Sage R. Bauers, Bethany Matthews, Bernardo Orvañanos, Bor-rong Chen, Laura T. Schelhas, Christopher J Bartel, Michael F. Toney, William TumasAbstract:Exploratory synthesis in new chemical spaces is the essence of Solid-State Chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging. Nitrides represent one such space, where stringent synthesis constraints have limited the exploration of this important class of functional materials. Here, we employ a suite of computational materials discovery and informatics tools to construct a large stability map of the inorganic ternary metal nitrides. Our map clusters the ternary nitrides into chemical families with distinct stability and metastability, and highlights hundreds of promising new ternary nitride spaces for experimental investigation-from which we experimentally realized seven new Zn- and Mg-based ternary nitrides. By extracting the mixed metallicity, ionicity and covalency of Solid-State bonding from the density functional theory (DFT)-computed electron density, we reveal the complex interplay between Chemistry, composition and electronic structure in governing large-scale stability trends in ternary nitride materials.
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a map of the inorganic ternary metal nitrides
arXiv: Materials Science, 2018Co-Authors: Wenhao Sun, Elisabetta Arca, Sage R. Bauers, Bethany Matthews, Bernardo Orvañanos, Bor-rong Chen, Laura T. Schelhas, Christopher J Bartel, Michael F. Toney, William TumasAbstract:Exploratory synthesis in novel chemical spaces is the essence of Solid-State Chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging. Nitrides represent one such space, where stringent synthesis constraints have limited the exploration of this important class of functional materials. Here, we employ a suite of computational materials discovery and informatics tools to construct a large stability map of the inorganic ternary metal nitrides. Our map clusters the ternary nitrides into chemical families with distinct stability and metastability, and highlights hundreds of promising new ternary nitride spaces for experimental investigation--from which we experimentally realized 7 new Zn- and Mg-based ternary nitrides. By extracting the mixed metallicity, ionicity, and covalency of Solid-State bonding from the DFT-computed electron density, we reveal the complex interplay between Chemistry, composition, and electronic structure in governing large-scale stability trends in ternary nitride materials.
Fabrizio Cavani - One of the best experts on this subject based on the ideXlab platform.
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Mixed-oxide catalysts with spinel structure for the valorization of biomass: the chemical-loop reforming of bioethanol.
Catalysts, 2018Co-Authors: Olena Vozniuk, Jean-marc M. Millet, Stefania Albonetti, Nathalie Tanchoux, Tommaso Tabanelli, Francesco Di Renzo, Fabrizio CavaniAbstract:This short review reports on spinel-type mixed oxides as catalysts for the transformation of biomass-derived building blocks into chemicals and fuel additives. After an overview of the various methods reported in the literature for the synthesis of mixed oxides with spinel structure, the use of this class of materials for the chemical-loop reforming of bioalcohols is reviewed in detail. This reaction is aimed at the production of H2 with intrinsic separation of C-containing products, but also is a very versatile tool for investigating the Solid-State Chemistry of spinels.
Martin Jansen - One of the best experts on this subject based on the ideXlab platform.
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structure prediction in solid state Chemistry as an approach to rational synthesis planning
Reference Module in Chemistry Molecular Sciences and Chemical Engineering#R##N#Comprehensive Inorganic Chemistry II (Second Edition)#R##N#From Element, 2013Co-Authors: J. C. Schön, Martin JansenAbstract:Traditionally, Solid-State Chemistry has followed the inductive paradigm, where experimental synthesis and observations provide information about the possible compounds in a chemical system and phenomenological and semi-phenomenological models are employed to rationalize a compound's existence (or ‘nonexistence’). Over the past 20 years, a new methodology has been developing, the aim of which is the prediction of chemical compounds without any recourse to experimental information, followed by their synthesis. The founding stone of this deductive approach to the rational planning of Solid-State syntheses is the global study of the energy landscape of the chemical system under consideration. In this chapter, we present an introduction to the concept of energy landscapes in the context of structure predictions and its implications for synthesis planning. The latter step gives access to calculate phase diagrams without resorting to any prior experimental information. Particularly noteworthy, the approach developed allows the derivation of extended phase diagrams that include metastable compounds in a systematic fashion.
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structure prediction and energy landscape exploration in the zinc oxide system
Processing and Application of Ceramics, 2011Co-Authors: Dejan Zagorac, J. C. Schön, Vladimirovich Ilya Pentin, Martin JansenAbstract:The rational planning of syntheses, i.e. the search for new crystalline compounds followed by their synthesis is a central topic of solid state Chemistry. In order to gain new insights in the ZnO system, we have performed global explorations of the energy landscape using simulated annealing with an empirical potential, both at standard and elevated pressure (up to 100 GPa). Besides the well-known structure types (wurtzite, sphalerite and rock-salt), many new interesting modifications were found in different regions of the energy landscape, e.g. the “5-5” type, the NiAs type, and the β-BeO type. Furthermore, we observed many distorted variations of these main types, in particular new structures built-up from various combinations of structure elements of these types, exhibiting a variety of stacking orders.
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A concept for synthesis planning in Solid-State Chemistry.
Angewandte Chemie (International ed. in English), 2002Co-Authors: Martin JansenAbstract:There is a widely-held belief that the preparation of new Solid-State compounds based on rational design is not possible. Herein, we present a concept that points the way towards a rational design of syntheses in Solid-State Chemistry. The foundation of our approach is the representation of the whole material world, that is, the known and not-yet-known compounds, on an energy landscape, which gives information about the free energies of these compounds. From this it follows that all chemical compounds capable of existence are present on this landscape. Thus the chemical synthesis always corresponds to the discovery of compounds, not their creation. Consequently, the first step in planning a synthesis can and must be to identify a synthesizable compound. Up to now, materials capable of existence are discovered in the course of an experimental exploration of the energy landscape; however, an a priori identification of a synthesis goal requires an exploration using theoretical methods. In contrast to those computational approaches currently employed for structure determination for fixed composition and already known unit cells, our aims clash with such restrictions and full global optimizations have to be performed on the landscape. Although for reasons of computational feasibility the accuracy of the energy calculations is not yet as high as one would wish, our approach proves to be surprisingly robust. One always finds the already known compounds of a given chemical system, and, in addition, further plausible structure candidates are discovered. The second step of a rational planning of syntheses is the design of feasible synthesis routes. Modeling such routes requires highly accurate computations for realistic thermodynamic conditions, however this is usually beyond our current capabilities. Thus, we have not seriously pursued such a deductive approach; instead we have attempted, to reproduce the “computational annealing” employed during our structure predictions in the experiment. Educts, generated by vapor deposition methods, that are disperse on an atomic level are found to react with surprisingly low activation energies to give highly crystallized products. However, even this technique does not yet provide the possibility to selectively synthesize a specific solid compound. For this final step, modeling and experimental control of nucleation processes will be the key ingredient. Only when viewed superficially, our goal of a “rational design” of Solid-State syntheses and the “high-throughput” syntheses are in contradiction. But an exhaustive exploration of the unimaginably large combinatorial diversity of Chemistry remains beyond our capabilities, even with an exceedingly high throughput. The future of Solid-State synthesis will be found in a union of these two conceptual approaches.