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A fundamental challenge in materials science pertains to elucidating the relationship between stoichiometry, stability, structure, and property.
The Analytical Expression Of The Results Of The Theory Of Space-groups
Ralph Walter Graystone Wyckoff · 1922
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The origin dependence of wyckoff site description of a crystal structure
LL Boyle and JE Lawrenson · 1973
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Crystallographic databases
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Estimating the mean and variance of the target probability distribution
David A Nix and Andreas S Weigend · 1994
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Projector augmented-wave method
Peter E Blöchl · 1994
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A numerical study on learning curves in stochastic multilayer feedforward networks
K-R Müller, Michael Finke, Noboru Murata, Klaus Schulten, and Shun-ichi Amari · 1996
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Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set
Georg Kresse and Jürgen Furthmüller · 1996
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Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
Georg Kresse and Jürgen Furthmüller · 1996
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Generalized gradient approximation made simple
John P Perdew, Kieron Burke, and Matthias Ernzerhof · 1996
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Identification of cathode materials for lithium batteries guided by first-principles calculations
Gerbrand Ceder, Y-M Chiang, DR Sadoway, MK Aydinol, Y-I Jang, and Biying Huang · 1998
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From ultrasoft pseudopotentials to the projector augmented-wave method
Georg Kresse and Daniel Joubert · 1999
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The inorganic crystal structure database (ICSD)—present and future
Mariette Hellenbrandt · 2004
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A discussion of measures of enrichment in virtual screening: Comparing the information content of descriptors with increasing levels of sophistication
Andreas Bender and Robert C Glen · 2005
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Benchmarking sets for molecular docking
Niu Huang, Brian K Shoichet, and John J Irwin · 2006
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Bilbao crystallographic server: I. databases and crystallographic computing programs
Mois Ilia Aroyo, Juan Manuel Perez-Mato, Cesar Capillas, Eli Kroumova, Svetoslav Ivantchev, Gotzon Madariaga, Asen Kirov, and Hans Wondratschek · 2006
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Data mined ionic substitutions for the discovery of new compounds
Geoffroy Hautier, Chris Fischer, Virginie Ehrlacher, Anubhav Jain, and Gerbrand Ceder · 2011
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Ab initio random structure searching
Chris J Pickard and RJ Needs · 2011
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Assessing the thermoelectric properties of sintered compounds via high-throughput ab-initio calculations
Shidong Wang, Zhao Wang, Wahyu Setyawan, Natalio Mingo, and Stefano Curtarolo · 2011
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Formation enthalpies by mixing GGA and GGA+U calculations
Anubhav Jain, Geoffroy Hautier, Shyue Ping Ong, Charles J Moore, Christopher C Fischer, Kristin A Persson, and Gerbrand Ceder · 2011
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Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17
Lars Ruddigkeit, Ruud Van Deursen, Lorenz C Blum, and Jean-Louis Reymond · 2012
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Correcting density functional theory for accurate predictions of compound enthalpies of formation: Fitted elemental-phase reference energies
Vladan Stevanović, Stephan Lany, Xiuwen Zhang, and Alex Zunger · 2012
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CALYPSO: A method for crystal structure prediction
Yanchao Wang, Jian Lv, Li Zhu, and Yanming Ma · 2012
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Commentary: The materials project: A materials genome approach to accelerating materials innovation
Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, and Others · 2013
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Combinatorial screening for new materials in unconstrained composition space with machine learning
Bryce Meredig, Ankit Agrawal, Scott Kirklin, James E Saal, JW Doak, Alan Thompson, Kunpeng Zhang, Alok Choudhary, and Christopher Wolverton · 2014
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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The chemical space project
Jean-Louis Reymond · 2015
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The open quantum materials database (oqmd): Assessing the accuracy of dft formation energies
Scott Kirklin, James E Saal, Bryce Meredig, Alex Thompson, Jeff W Doak, Muratahan Aykol, Stephan Rühl, and Chris Wolverton · 2015
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Crystal structure representations for machine learning models of formation energies
Felix Faber, Alexander Lindmaa, O Anatole Von Lilienfeld, and Rickard Armiento · 2015
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SchNet–a deep learning architecture for molecules and materials
Kristof T Schütt, Huziel E Sauceda, P-J Kindermans, Alexandre Tkatchenko, and K-R Müller · 2018
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Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties
Tian Xie and Jeffrey C Grossman · 2018
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Alchemical and structural distribution based representation for universal quantum machine learning
Felix A Faber, Anders S Christensen, Bing Huang, and O Anatole Von Lilienfeld · 2018
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Spglib: A software library for crystal symmetry search
Atsushi Togo and Isao Tanaka · 2018
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AFLOW-SYM: Platform for the complete, automatic and self-consistent symmetry analysis of crystals
David Hicks, Corey Oses, Eric Gossett, Geena Gomez, Richard H Taylor, Cormac Toher, Michael J Mehl, Ohad Levy, and Stefano Curtarolo · 2018
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Shyue Ping Ong, Shreyas Cholia, Anubhav Jain, Miriam Brafman, Dan Gunter, Gerbrand Ceder, and Kristin A Persson · 2015
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Computational screening of all stoichiometric inorganic materials
Daniel W Davies, Keith T Butler, Adam J Jackson, Andrew Morris, Jarvist M Frost, Jonathan M Skelton, and Aron Walsh · 2016
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A general-purpose machine learning framework for predicting properties of inorganic materials
Logan Ward, Ankit Agrawal, Alok Choudhary, and Christopher Wolverton · 2016
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Machine learning energies of 2 million elpasolite ( A B C 2 D 6 ) ({ABC}_{2}{D}_{6}) crystals
Felix A Faber, Alexander Lindmaa, O Anatole Von Lilienfeld, and Rickard Armiento · 2016
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Computational predictions of energy materials using density functional theory
Anubhav Jain, Yongwoo Shin, and Kristin A Persson · 2016
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The optimal one dimensional periodic table: A modified pettifor chemical scale from data mining
Henning Glawe, Antonio Sanna, EKU Gross, and Miguel AL Marques · 2016
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Machine-learning-assisted materials discovery using failed experiments
Paul Raccuglia, Katherine C Elbert, Philip DF Adler, Casey Falk, Malia B Wenny, Aurelio Mollo, Matthias Zeller, Sorelle A Friedler, Joshua Schrier, and Alexander J Norquist · 2016
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Applications of machine learning in drug discovery and development
Jessica Vamathevan, Dominic Clark, Paul Czodrowski, Ian Dunham, Edgardo Ferran, George Lee, Bin Li, Anant Madabhushi, Parantu Shah, Michaela Spitzer, and Others · 2019
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Graph networks as a universal machine learning framework for molecules and crystals
Chi Chen, Weike Ye, Yunxing Zuo, Chen Zheng, and Shyue Ping Ong · 2019
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Coordination corrected ab initio formation enthalpies
Rico Friedrich, Demet Usanmaz, Corey Oses, Andrew Supka, Marco Fornari, Marco Buongiorno Nardelli, Cormac Toher, and Stefano Curtarolo · 2019
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Recent advances and applications of machine learning in solid-state materials science
Jonathan Schmidt, Mário RG Marques, Silvana Botti, and Miguel AL Marques · 2019
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Unsupervised word embeddings capture latent knowledge from materials science literature
Vahe Tshitoyan, John Dagdelen, Leigh Weston, Alexander Dunn, Ziqin Rong, Olga Kononova, Kristin A Persson, Gerbrand Ceder, and Anubhav Jain · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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The aflow library of crystallographic prototypes: Part 2
David Hicks, Michael J Mehl, Eric Gossett, Cormac Toher, Ohad Levy, Robert M Hanson, Gus Hart, and Stefano Curtarolo · 2019
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Predicting materials properties without crystal structure: Deep representation learning from stoichiometry
Rhys EA Goodall and Alpha A Lee · 2020
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Screening stable and metastable ABO3 perovskites using machine learning and the materials project
Haiying Liu, Jiucheng Cheng, Hongzhou Dong, Jianguang Feng, Beili Pang, Ziya Tian, Shuai Ma, Fengjin Xia, Chunkai Zhang, and Lifeng Dong · 2020
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Developing an improved crystal graph convolutional neural network framework for accelerated materials discovery
Cheol Woo Park and Chris Wolverton · 2020
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Computational search for new W-Mo-B compounds
Alexander G Kvashnin, Christian Tantardini, Hayk A Zakaryan, Yulia A Kvashnina, and Artem R Oganov · 2020
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Database-Driven High-Throughput Calculations And Machine Learning Models For Materials Design
Rickard Armiento · 2020
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Compositionally restricted attention-based network for materials property predictions
Anthony Yu-Tung Wang, Steven K Kauwe, Ryan J Murdock, and Taylor D Sparks · 2021
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Predicting stable crystalline compounds using chemical similarity
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A framework for quantifying uncertainty in DFT energy corrections, May 2021
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Promises and perils of computational materials databases
MK Horton, S Dwaraknath, and KA Persson · 2021
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Ab initio random structure searching for battery cathode materials
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First-principles search of hot superconductivity in la-xh ternary hydrides
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