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Two dimensional (2D) materials have emerged as promising functional materials with many applications such as semiconductors and photovoltaics because of their unique optoelectronic properties.
ab initio
G. Kresse and J. Hafner · 1993
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ab initio
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Efficiency of ab initio total energy calculations for metals and semiconductors using a plane-wave basis set
J. Furthmüller G. Kresse · 1996
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Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
G. Kresse and J. Furthmüller · 1996
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Generalized gradient approximation made simple
John P. Perdew, Kieron Burke, and Matthias Ernzerhof · 1996
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Generative adversarial nets
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Computational methods for 2d materials: discovery, property characterization, and application design
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High-throughput identification and characterization of two-dimensional materials using density functional theory
Kamal Choudhary, Irina Kalish, Ryan Beams, and Francesca Tavazza · 2017
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Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds
Nicolas Mounet, Marco Gibertini, Philippe Schwaller, Davide Campi, Andrius Merkys, Antimo Marrazzo, Thibault Sohier, Ivano Eligio Castelli, Andrea Cepellotti, Giovanni Pizzi, et al · 2018
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The computational 2d materials database: high-throughput modeling and discovery of atomically thin crystals
Sten Haastrup, Mikkel Strange, Mohnish Pandey, Thorsten Deilmann, Per S Schmidt, Nicki F Hinsche, Morten N Gjerding, Daniele Torelli, Peter M Larsen, Anders C Riis-Jensen, et al · 2018
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Inverse design in search of materials with target functionalities
Alex Zunger · 2018
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A machine learning approach for engineering bulk metallic glass alloys
Logan Ward, Stephanie C O’Keeffe, Joseph Stevick, Glenton R Jelbert, Muratahan Aykol, and Chris Wolverton · 2018
Discovering two-dimensional topological insulators from high-throughput computations
Thomas Olsen, Erik Andersen, Takuya Okugawa, Daniele Torelli, Thorsten Deilmann, and Kristian S Thygesen · 2019
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Smart inverse design of graphene-based photonic metamaterials by an adaptive artificial neural network
Yingshi Chen, Jinfeng Zhu, Yinong Xie, Naixing Feng, and Qing Huo Liu · 2019
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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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Rhys EA Goodall and Alpha A Lee · 2019
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2d materials for spintronic devices
Ethan C Ahn · 2020
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Matminer: An open source toolkit for materials data mining
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Recent advances in the functional 2d photonic and optoelectronic devices
Xiaoting Wang, Yu Cui, Tao Li, Ming Lei, Jingbo Li, and Zhongming Wei · 2019
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Magnetic 2d materials and heterostructures
M Gibertini, M Koperski, AF Morpurgo, and KS Novoselov · 2019
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Graphene and two-dimensional materials for silicon technology
Deji Akinwande, Cedric Huyghebaert, Ching-Hua Wang, Martha I Serna, Stijn Goossens, Lain-Jong Li, H-S Philip Wong, and Frank HL Koppens · 2019
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High-throughput computational screening of layered and two-dimensional materials
Xu Zhang, An Chen, and Zhen Zhou · 2019
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2dmatpedia, an open computational database of two-dimensional materials from top-down and bottom-up approaches
Jun Zhou, Lei Shen, Miguel Dias Costa, Kristin A Persson, Shyue Ping Ong, Patrick Huck, Yunhao Lu, Xiaoyang Ma, Yiming Chen, Hanmei Tang, et al · 2019
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Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David A Winkler, Joe Shapter, and Michael J Ford · 2019
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High-throughput identifications of exfoliable two-dimensional materials with active basal planes for hydrogen evolution
Tong Yang, Jun Zhou, Ting Ting Song, Lei Shen, Yuan Ping Feng, and Ming Yang · 2020
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Coupling a crystal graph multilayer descriptor to active learning for rapid discovery of 2d ferromagnetic semiconductors/half-metals/metals
Shuaihua Lu, Qionghua Zhou, Yilv Guo, Yehui Zhang, Yilei Wu, and Jinlan Wang · 2020
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High-throughput discovery of high curie point two-dimensional ferromagnetic materials
Arnab Kabiraj, Mayank Kumar, and Santanu Mahapatra · 2020
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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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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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Cryspnet: Crystal structure predictions via neural network
Haotong Liang, Valentin Stanev, A Gilad Kusne, and Ichiro Takeuchi · 2020
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The earth mover’s distance as a metric for the space of inorganic compositions
Cameron Hargreaves, Matthew Dyer, Michael Gaultois, Vitaliy Kurlin, and Matthew J Rosseinsky · 2020
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