Keyword

materials database

Description: An organized collection of materials data used to store, search, analyze, and compare material properties in science and engineering.

Primary topic: Machine Learning in Materials Science (35%)

Wikidata ID: wiki/Q2560532

OpenAlex ID: keywords/materials-database

Recent advances and applications of machine learning in solid-state materials science

2019 · Jonathan Schmidt, Mário R. G. Marques, et al. · npj Computational Materials · 2,622

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Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

2013 · James E. Saal, Scott Kirklin, et al. · JOM · 2,529

The high-throughput highway to computational materials design

2013 · Stefano Curtarolo, Gus L. W. Hart, et al. · Nature Materials · 2,042

Algorithms and tools for high-throughput geometry-based analysis of crystalline porous materials

2011 · Thomas F. Willems, Chris H. Rycroft, et al. · Microporous and Mesoporous Materials · 1,931

The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals

2018 · Sten Haastrup, Mikkel Strange, et al. · 2D Materials · 1,228

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Recent advances and applications of deep learning methods in materials science

2022 · Kamal Choudhary, Brian DeCost, et al. · npj Computational Materials · 1,166

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AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations

2012 · Stefano Curtarolo, Wahyu Setyawan, et al. · Computational Materials Science · 1,123

Unsupervised word embeddings capture latent knowledge from materials science literature

2019 · Vahe Tshitoyan, John Dagdelen, et al. · Nature · 1,117

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Matminer: An open source toolkit for materials data mining

2018 · Logan Ward, Alexander Dunn, et al. · Computational Materials Science · 1,076

Charting the complete elastic properties of inorganic crystalline compounds

2015 · Maarten de Jong, Wei Chen, et al. · Scientific Data · 1,007

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Data‐Driven Materials Science: Status, Challenges, and Perspectives

2019 · Lauri Himanen, Amber Geurts, et al. · Advanced Science · 804

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Refractiveindex.info database of optical constants

2024 · Mikhail N. Polyanskiy · Scientific Data · 737

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Biomimetic materials research: what can we really learn from nature's structural materials?

2007 · Peter Fratzl · Journal of The Royal Society Interface · 617

Mapping the world of complex concentrated alloys

2017 · Stéphane Gorsse, Daniel B. Miracle, et al. · Acta Materialia · 436

Compendium of Material Composition Data for Radiation Transport Modeling

2011 · USDOE National Nuclear Security Administration (NNSA), Nuclear Criticality Safety Program (NCSP), Ronald McConn, et al. · 431

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Combinatorial and High‐Throughput Materials Science

2007 · Wilhelm F. Maier, Klaus Stöwe, et al. · Angewandte Chemie International Edition · 401

Computation-Accelerated Design of Materials and Interfaces for All-Solid-State Lithium-Ion Batteries

2018 · Adelaide M. Nolan, Yizhou Zhu, et al. · Joule · 398

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2DMatPedia, an open computational database of two-dimensional materials from top-down and bottom-up approaches

2019 · Jun Zhou, Lei Shen, et al. · Scientific Data · 379

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Toward a Common Framework and Database of Materials for Soft Robotics

2020 · Luc Marechal, Pascale Balland, et al. · Soft Robotics · 344

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The 2019 materials by design roadmap

2018 · Kirstin Alberi, Marco Buongiorno Nardelli, et al. · Journal of Physics D Applied Physics · 322

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A database to enable discovery and design of piezoelectric materials

2015 · Maarten de Jong, Wei Chen, et al. · Scientific Data · 311

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Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

2014 · Olexandr Isayev, Denis Fourches, et al. · Chemistry of Materials · 300

Deep materials informatics: Applications of deep learning in materials science

2019 · Ankit Agrawal, Alok Choudhary · MRS Communications · 296

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Materials Data Science: Current Status and Future Outlook

2015 · Surya R. Kalidindi, Marc De Graef · Annual Review of Materials Research · 294

Performance-Based Screening of Porous Materials for Carbon Capture

2021 · H. Farmahini, Amir, Krishnamurthy, Shreenath, et al. · Research Explorer (The University of Manchester) · 278

Works count: 3,546

Citation count: 46,190