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Crystal structure prediction is one of the major unsolved problems in materials science.
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He, K.; Zhang, X.; Ren, S.; Sun, J. Identity mappings in deep residual networks. European conference on computer vision. 2016; pp 630–645
Podryabinkin, E. V.; Tikhonov, E. V.; Shapeev, A. V.; Oganov, A. R. Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning. Physical Review B 2019
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Dan, Y.; Zhao, Y.; Li, X.; Li, S.; Hu, M.; Hu, J. Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials. npj Computational Materials 2020
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Jang, J.; Gu, G. H.; Noh, J.; Kim, J.; Jung, Y. Structure-Based Synthesizability Prediction of Crystals Using Partially Supervised Learning. Journal of the American Chemical Society 2020
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Zhang, L.; Wang, Y.; Lv, J.; Ma, Y. Materials discovery at high pressures. Nature Reviews Materials 2017
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Zhu, Z.; Wu, P.; Wu, S.; Xu, L.; Xu, Y.; Zhao, X.; Wang, C.-Z.; Ho, K.-M. An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs. The Journal of Physical Chemistry C 2017
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Krizhevsky, A.; Sutskever, I.; Hinton, G. E. Imagenet classification with deep convolutional neural networks. Communications of the ACM 2017
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Xie, T.; Grossman, J. C. Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties. Physical review letters 2018
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Curtis, F.; Li, X.; Rose, T.; Vazquez-Mayagoitia, A.; Bhattacharya, S.; Ghiringhelli, L. M.; Marom, N. GAtor: a first-principles genetic algorithm for molecular crystal structure prediction. Journal of chemical theory and computation 2018
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Ryan, K.; Lengyel, J.; Shatruk, M. Crystal structure prediction via deep learning. Journal of the American Chemical Society 2018
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Frey, N. C.; Wang, J.; Vega Bellido, G. I.; Anasori, B.; Gogotsi, Y.; Shenoy, V. B. Prediction of synthesis of 2D metal carbides and nitrides (MXenes) and their precursors with positive and unlabeled machine learning. ACS nano 2019
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Shen, J.-X.; Horton, M.; Persson, K. A. A charge-density-based general cation insertion algorithm for generating new Li-ion cathode materials. npj Computational Materials 2020
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He, J.; Yao, Z.; Hegde, V. I.; Naghavi, S. S.; Shen, J.; Bushick, K. M.; Wolverton, C. Computational Discovery of Stable Heteroanionic Oxychalcogenides ABXO (A, B= Metals; X= S, Se, and Te) and Their Potential Applications. Chemistry of Materials 2020
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Wang, Y.; Lv, J.; Li, Q.; Wang, H.; Ma, Y. CALYPSO method for structure prediction and its applications to materials discovery. Handbook of Materials Modeling: Applications: Current and Emerging Materials 2020
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Pretti, E.; Shen, V. K.; Mittal, J.; Mahynski, N. A. Symmetry-Based Crystal Structure Enumeration in Two Dimensions. The Journal of Physical Chemistry A 2020
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others,, et al. Improved protein structure prediction using potentials from deep learning. Nature 2020
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2023
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Wang, Y.; Lv, J.; Zhu, L.; Ma, Y. CALYPSO: A method for crystal structure prediction. Computer Physics Communications 2012
2070
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