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2018

490

Matminer: An open source toolkit for materials data mining

Computational Materials Science (3.1 ★★★), 152, 60-69. Cite Citations

Logan Ward (67, 3.9K)Yinan Li (36, 794)Qi Wang (10, 1.3K)

2023

A database of molecular properties integrated in the Materials Project

Digital Discovery (5.7 ★★★), 2, 1862-1882. Cite Citations

Evan Walter Clark Spotte-smith (29, 392)Samuel M Blau (17, 414)Patrick Huck (10, 387)

2018

Automated generation and ensemble-learned matching of X-ray absorption spectra

Npj Computational Materials (9.1 ★★★), 4, . Cite Citations

Chi Chen (64, 7.4K)Fernando D Vila (58, 2.6K)Hanmei Tang (16, 1.4K)

2023

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling

Nature Machine Intelligence (15.2 ★★★), 5, 1031-1041. Cite Citations

Peichen Zhong (13, 285)Kyujung Jun (15, 243)Christopher J Bartel (54, 3.7K)

2017

271

Topology-Scaling Identification of Layered Solids and Stable Exfoliated 2D Materials

Physical Review Letters (8.0 ★★★), 118, 106101. Cite Citations

Michael Ashton (11, 1.0K)Susan B Sinnott (260, 13.4K)Richard G Hennig (176, 14.9K)

2017

169

Data Mining for New Two- and One-Dimensional Weakly Bonded Solids and Lattice-Commensurate Heterostructures

Nano Letters (9.5 ★★★), 17, 1915-1923. Cite Citations

Gowoon Cheon (11, 803)Austin D Sendek (23, 2.4K)Yuan Chen (5, 232)

2024

matbench-genmetrics: A Python library for benchmarking crystal structure generative models using time-based splits of Materials Project structures

Journal of Open Source Software (4.8 ★★★), 9, 5618. Cite Citations

Sterling G Baird (16, 133)Hasan M Sayeed (4, 13)Joseph H Montoya (57, 8.2K)

2018

161

Computational Screening of 2D Materials and Rational Design of Heterojunctions for Water Splitting Photocatalysts

Small Methods (9.6 ★★★), 2, 1700359. Cite Citations

Juliana Alvares-teodoro (192, 2.8K)Xu Zhang (41, 4.6K)Xudong Zhao (34, 3.9K)

2018

The Materials Project: Accelerating Materials Design Through Theory-Driven Data and Tools

Shyue Ping Ong (185, 25.1K)Anubhav Jain (153, 19.5K)Shyam Dwaraknath (40, 1.9K)

2019

211

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

Scientific Data (5.4 ★★★), 6, 86. Cite Citations

Jun Zhou (77, 3.7K)Lei Shen (128, 5.2K)Kristin A Persson (271, 29.4K)

2020

132

A critical examination of compound stability predictions from machine-learned formation energies

Npj Computational Materials (9.1 ★★★), 6, . Cite Citations

Alexander Dunn (11, 1.6K)Anubhav Jain (153, 19.5K)Christopher J Bartel (54, 3.7K)

2017

106

Computational prediction of new auxetic materials

Nature Communications (13.2 ★★★), 8, 323. Cite Citations

Kristin A Persson (271, 29.4K)

2020

Structure-Based Synthesizability Prediction of Crystals Using Partially Supervised Learning

Journal of the American Chemical Society (14.6 ★★★), 142, 18836-18843. Cite Citations

Geun Ho Gu (29, 1.4K)Juhwan Noh (19, 1.3K)Yousung Jung (231, 25.3K)

2015

A Community Contribution Framework for Sharing Materials Data with Materials Project

Anubhav Jain (153, 19.5K)Dan Gunter (31, 3.5K)Donny Winston (19, 1.8K)

2015

329

Crystal structure representations for machine learning models of formation energies

International Journal of Quantum Chemistry (2.1 ★★★), 115, 1094-1101. Cite Citations

Rickard Armiento (66, 3.4K)Alexander Lindmaa (2, 681)O Anatole Von Lilienfeld (126, 12.8K)

2016

201

Understanding thermoelectric properties from high-throughput calculations: trends, insights, and comparisons with experiment

Journal of Materials Chemistry C (5.6 ★★★), 4, 4414-4426. Cite Citations

Paola Rogliani (612, 21.3K)Bryce Meredig (30, 5.2K)G Jeffrey Snyder (555, 64.7K)

2018

112

Active learning for accelerated design of layered materials

Npj Computational Materials (9.1 ★★★), 4, . Cite Citations

Aiichiro Nakano (285, 7.7K)David J Singh (409, 50.8K)Kristin A Persson (271, 29.4K)

2019

114

Machine Learning the Voltage of Electrode Materials in Metal-Ion Batteries

ACS Applied Materials & Interfaces (8.3 ★★★), 11, 18494-18503. Cite Citations

Jesse Eickholt (29, 1.3K)Marco Fornari (104, 3.4K)Veronica Barone (42, 3.2K)

2019

Candidate Inorganic Photovoltaic Materials from Electronic Structure-Based Optical Absorption and Charge Transport Proxies

Chemistry of Materials (7.1 ★★★), 31, 1561-1574. Cite Citations

Douglas H Fabini (28, 2.0K)Ram Seshadri (453, 25.8K)

2021

Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration

ACS Nano (15.3 ★★★), 15, 3971-3995. Cite Citations

Jiwon Yeom (7, 140)Gun Park (11, 162)Hyeonmuk Kang (5, 95)

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Similar Keywords

21-40 of (312 documents found)

Matminer: An open source toolkit for materials data mining

A database of molecular properties integrated in the Materials Project

Automated generation and ensemble-learned matching of X-ray absorption spectra

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling

Topology-Scaling Identification of Layered Solids and Stable Exfoliated 2D Materials

Data Mining for New Two- and One-Dimensional Weakly Bonded Solids and Lattice-Commensurate Heterostructures

matbench-genmetrics: A Python library for benchmarking crystal structure generative models using time-based splits of Materials Project structures

Computational Screening of 2D Materials and Rational Design of Heterojunctions for Water Splitting Photocatalysts

The Materials Project: Accelerating Materials Design Through Theory-Driven Data and Tools

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

A critical examination of compound stability predictions from machine-learned formation energies

Computational prediction of new auxetic materials

Structure-Based Synthesizability Prediction of Crystals Using Partially Supervised Learning

A Community Contribution Framework for Sharing Materials Data with Materials Project

Crystal structure representations for machine learning models of formation energies

Understanding thermoelectric properties from high-throughput calculations: trends, insights, and comparisons with experiment

Active learning for accelerated design of layered materials

Machine Learning the Voltage of Electrode Materials in Metal-Ion Batteries

Candidate Inorganic Photovoltaic Materials from Electronic Structure-Based Optical Absorption and Charge Transport Proxies

Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration