The role of computational results databases in accelerating the discovery of catalysts

Bo, Carles; Maseras, Feliu; López, Núria

doi:10.1038/s41929-018-0176-4

Cited by 66 publications

(67 citation statements)

References 26 publications

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“…In the regime of data-driven catalysis research, it is important that data can be accessed efficiently and selectively so that meaningful subsets can be leveraged to make new computational insights into catalyst design. Therefore, development of advanced approaches for storing and accessing relevant data, such as the establishment of curated open access databases is critical 3 . Ensuring that data is findable, accessible, inter-operational, and reusable, in correspondence with the FAIR guiding principles for data management 4 , is an important step towards making data machine as well as human readable.…”

Section: Introductionmentioning

confidence: 99%

Catalysis-Hub.org, an open electronic structure database for surface reactions

et al. 2019

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We present a new open repository for chemical reactions on catalytic surfaces, available at https://www.catalysis-hub.org . The featured database for surface reactions contains more than 100,000 chemisorption and reaction energies obtained from electronic structure calculations, and is continuously being updated with new datasets. In addition to providing quantum-mechanical results for a broad range of reactions and surfaces from different publications, the database features a systematic, large-scale study of chemical adsorption and hydrogenation on bimetallic alloy surfaces. The database contains reaction specific information, such as the surface composition and reaction energy for each reaction, as well as the surface geometries and calculational parameters, essential for data reproducibility. By providing direct access via the web-interface as well as a Python API, we seek to accelerate the discovery of catalytic materials for sustainable energy applications by enabling researchers to efficiently use the data as a basis for new calculations and model generation.

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Section: Introductionmentioning

confidence: 99%

Catalysis-Hub.org, an open electronic structure database for surface reactions

et al. 2019

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“…Approximately 30% of the total use of supercomputers at the European level is dedicated to different types of density functional theory (DFT) approximations, and the amount of data generated is truly staggering. [ 10 ] Databases of experimental results are highly promising to accelerate catalysis research. Yet, several problems remain, and consensus on issues such as metadata, usability, and healing is key to transform the current excitement into an attractive technology.…”

Section: Pomzites: Pom‐based Frameworkmentioning

confidence: 99%

“…Yet, several problems remain, and consensus on issues such as metadata, usability, and healing is key to transform the current excitement into an attractive technology. [ 10 ] Material discovery and design efforts ideally involve a close coupling between material prediction, synthesis, and characterization. We need to speed up and lower the cost of the discovery of materials that are able to adapt to the needs of a much more demanding technology.…”

Section: Pomzites: Pom‐based Frameworkmentioning

confidence: 99%

POMzites: A roadmap for inverse design in metal oxide chemistry

Vilà‐Nadal

2020

Int J of Quantum Chemistry

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Computationally exploring the space generated by the self‐assembly of known molecular metal oxides and the ability to predict new architectures is a challenging task. As a proof of concept, here, we propose narrowing it down to a new family of all‐inorganic porous materials named POMzites. Structures with new topologies, but aiming for pure inorganic systems, will be targeted initially. POMzites are composed of ring‐shaped tungsten oxide building blocks connected with transition metal linkers forming zero to three dimensional frameworks. Despite POMzites and zeolites having similar structures, the library of POMzites is an order of magnitude smaller than that of zeolites (14 POMzites vs 213 zeolites). The idea proposed in this perspective article is to accelerate the discovery of new POMzite porous frameworks materials using inverse design approaches.

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“…Only lately, the relevance of keeping these data in the form of databases has been acknowledged. [ 4 ] Most of the systems, however, have emerged in materials science in projects such as the Materials Project, [ 5,6 ] NoMaD, [ 7 ] Materials Cloud, [ 8 ] and Computational Materials Repository. [ 9 ] Data are mostly unlinked to the corresponding works, and thus, the traceability (who, when, what) and fairness (findable, accessible, interoperable, reusable) are lost.…”

Section: Introductionmentioning

confidence: 99%

Turning chemistry into information for heterogeneous catalysis

Pablo‐García

Álvarez‐Moreno

López

2020

Int J of Quantum Chemistry

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The growing generation of data and their wide availability has led to the development of tools to produce, analyze, and store this information. Computational chemistry studies, especially catalytic applications, often yield a vast amount of chemical information that can be analyzed and stored using these tools. In this manuscript, we present a framework that automatically performs a fully automated procedure consisting of the transfer of an adsorbate from a known metal slab to a new metal slab with similar packing. Our method generates the new geometry and also performs the required calculations and analysis to finally upload the processed data to an online database (ioChem-BD). Two different implementations have been built, one to relocate minimum energy point structures and the second to transfer transition states. Our framework shows good performance for the minimum point location and a decent performance for the transition state identification. Most of the failures occurred during the transition state searches and needed additional steps to fully complete the process. Further improvements of our framework are required to increase the performance of both implementations. These results point to the avoidhuman path as a feasible solution for studies on very large systems that require a significant amount of human resources and, in consequence, are prone to human errors.

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The role of computational results databases in accelerating the discovery of catalysts

Cited by 66 publications

References 26 publications

Catalysis-Hub.org, an open electronic structure database for surface reactions

Catalysis-Hub.org, an open electronic structure database for surface reactions

POMzites: A roadmap for inverse design in metal oxide chemistry

Turning chemistry into information for heterogeneous catalysis

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