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High-throughput screening has become one of the major strategies for the discovery of novel functional materials.
Searching potential energy surfaces by simulated annealing
LT Wille · 1986
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Crystallographic databases
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Global optimization by basin-hopping and the lowest energy structures of lennard-jones clusters containing up to 110 atoms
David J Wales and Jonathan PK Doye · 1997
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Symmetry-general least-squares extraction of elastic data for strained materials from ab initio calculations of stress
Yvon Le Page and Paul Saxe · 2002
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Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems
Stefan Goedecker · 2004
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Uspex—evolutionary crystal structure prediction
Colin W Glass, Artem R Oganov, and Nikolaus Hansen · 2006
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Reducing the dimensionality of data with neural networks
Geoffrey E Hinton and Ruslan R Salakhutdinov · 2006
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
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Crystal structure prediction via particle-swarm optimization
Yanchao Wang, Jian Lv, Li Zhu, and Yanming Ma · 2010
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High-throughput screening: speeding up porous materials discovery
Philipp Wollmann, Matthias Leistner, Ulrich Stoeck, Ronny Grünker, Kristina Gedrich, Nicole Klein, Oliver Throl, Wulf Grählert, Irena Senkovska, Frieder Dreisbach, et al · 2011
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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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Crystal structure prediction using the uspex code
AR Oganov, Andriy Lyakhov, Mario Valle, and Gilles Frapper · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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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, et al · 2013
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Materials design and discovery with high-throughput density functional theory: the open quantum materials database (oqmd)
James E Saal, Scott Kirklin, Muratahan Aykol, Bryce Meredig, and Christopher Wolverton · 2013
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Python materials genomics (pymatgen): A robust, open-source python library for materials analysis
Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy Hautier, Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent L Chevrier, Kristin A Persson, and Gerbrand Ceder · 2013
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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Evidence for a large phononic band gap leading to slow hot carrier thermalisation
S Chung, S Shrestha, X Wen, Y Feng, N Gupta, H Xia, P Yu, J Tang, and G Conibeer · 2014
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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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First principles phonon calculations in materials science
A Togo and I Tanaka · 2015
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Tutorial on variational autoencoders
Carl Doersch · 2016
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Electron–phonon coupling in hybrid lead halide perovskites
Adam D Wright, Carla Verdi, Rebecca L Milot, Giles E Eperon, Miguel A Pérez-Osorio, Henry J Snaith, Feliciano Giustino, Michael B Johnston, and Laura M Herz · 2016
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Holistic computational structure screening of more than 12000 candidates for solid lithium-ion conductor materials
Austin D Sendek, Qian Yang, Ekin D Cubuk, Karel-Alexander N Duerloo, Yi Cui, and Evan J Reed · 2017
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Strong electron–phonon interaction retarding phonon transport in superconducting hydrogen sulfide at high pressures
Jia-Yue Yang and Ming Hu · 2018
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Structure prediction drives materials discovery
Artem R Oganov, Chris J Pickard, Qiang Zhu, and Richard J Needs · 2019
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Inverse design of solid-state materials via a continuous representation
Juhwan Noh, Jaehoon Kim, Helge S Stein, Benjamin Sanchez-Lengeling, John M Gregoire, Alan Aspuru-Guzik, and Yousung Jung · 2019
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Ultrafast hot carrier dynamics of zrte 5 {\mathrm{zrte}}_{5} from time-resolved optical reflectivity
Xiu Zhang, Hai-Ying Song, X. C. Nie, Shi-Bing Liu, Yang Wang, Cong-Ying Jiang, Shi-Zhong Zhao, Genfu Chen, Jian-Qiao Meng, Yu-Xia Duan, and H. Y. Liu · 2019
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An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery
Murat Cihan Sorkun, Séverin Astruc, JM Vianney A Koelman, and Süleyman Er · 2020
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Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Cited alongside, same era.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
Cited alongside, same era.
Aelas: Automatic elastic property derivations via high-throughput first-principles computation
S.H. Zhang and R.F. Zhang · 2017
Cited alongside, same era.
Band structure diagram paths based on crystallography
Yoyo Hinuma, Giovanni Pizzi, Yu Kumagai, Fumiyasu Oba, and Isao Tanaka · 2017
Cited alongside, same era.
Anomalously temperature-dependent thermal conductivity of monolayer gan with large deviations from the traditional 1/t law
Guangzhao Qin, Zhenzhen Qin, Huimin Wang, and Ming Hu · 2017
Cited alongside, same era.
Machine-learning-accelerated high-throughput materials screening: Discovery of novel quaternary heusler compounds
Kyoungdoc Kim, Logan Ward, Jiangang He, Amar Krishna, Ankit Agrawal, and C Wolverton · 2018
Cited alongside, same era.
Tailoring the cation lattice for chloride lithium-ion conductors
Yunsheng Liu, Shuo Wang, Adelaide M Nolan, Chen Ling, and Yifei Mo · 2020
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Generative adversarial networks (gan) based efficient sampling of chemical composition space for inverse design of inorganic materials
Yabo Dan, Yong Zhao, Xiang Li, Shaobo Li, Ming Hu, and Jianjun Hu · 2020
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Ccdcgan: Inverse design of crystal structures
Teng Long, Nuno M Fortunato, Ingo Opahle, Yixuan Zhang, Ilias Samathrakis, Chen Shen, Oliver Gutfleisch, and Hongbin Zhang · 2020
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Inverse design of crystals using generalized invertible crystallographic representation
Zekun Ren, Juhwan Noh, Siyu Tian, Felipe Oviedo, Guangzong Xing, Qiaohao Liang, Armin Aberle, Yi Liu, Qianxiao Li, Senthilnath Jayavelu, et al · 2020
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Generative adversarial networks for crystal structure prediction
Sungwon Kim, Juhwan Noh, Geun Ho Gu, Alán Aspuru-Guzik, and Yousung Jung · 2020
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A charge-density-based general cation insertion algorithm for generating new li-ion cathode materials
Jimmy-Xuan Shen, Matthew Horton, and Kristin A Persson · 2020
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Computational discovery of new 2d materials using deep learning generative models
Yuqi Song, Edirisuriya M Dilanga Siriwardane, Yong Zhao, and Jianjun Hu · 2020
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Machine-enabled inverse design of inorganic solid materials: promises and challenges
Juhwan Noh, Geun Ho Gu, Sungwon Kim, and Yousung Jung · 2020
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3-d inorganic crystal structure generation and property prediction via representation learning
Callum Court, Batuhan Yildirim, Apoorv Jain, and Jacqueline M Cole · 2020
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Machine-learning-assisted search for functional materials over extended chemical space
Vadim Korolev, Artem Mitrofanov, Artem Eliseev, and Valery Tkachenko · 2020
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Mlatticeabc: generic lattice constant prediction of crystal materials using machine learning
Yuxin Li, Wenhui Yang, Rongzhi Dong, and Jianjun Hu · 2020
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Hot carrier dynamics in nitrogen – rich hafnium nitride thin film
B. Thapa, M. Dubajic, M. P. Nielsen, R. Patterson, G. Conibeer, and S. Shrestha · 2020
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Strong electron-phonon coupling induced anomalous phonon transport in ultrahigh temperature ceramics zrb2 and tib2
Jia-Yue Yang, Wenjie Zhang, Chengying Xu, Jun Liu, Linhua Liu, and Ming Hu · 2020
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