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Powder X-ray diffraction (pXRD) experiments are a cornerstone for materials structure characterization.
Rietveld refinement guidelines
L. B. McCusker, R. B. Von Dreele, D. E. Cox, D. Louër, and P. Scardi · 1999
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Powder diffraction indexing as a pattern recognition problem: A new approach for unit cell determination based on an artificial neural network
S. Habershon, E. Cheung, K. Harris, and R. Johnston · 2004
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X-Ray Diffraction Crystallography
Yoshio Waseda, Eiichiro Matsubara, and Kozo Shinoda · 2011
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1. The power of databases: The RRUFF project
Barbara Lafuente, R. T. Downs, H. Yang, and N. Stone · 2015
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Highlights in Mineralogical Crystallography
Thomas Armbruster and Rosa Micaela Danisi, editors · 2015
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
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Principal component analysis: a review and recent developments
Ian T. Jolliffe and Jorge Cadima · 2015
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Image style transfer using convolutional neural networks
Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge · 2016
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Classification of crystal structure using a convolutional neural network
W. Park, Jiyong Chung, Jaeyoung Jung, Keemin Sohn, S. Singh, M. Pyo, N. Shin, and K. Sohn · 2017
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Evolution of opto-electronic properties during film formation of complex semiconductors
M. D. Heinemann, R. Mainz, F. Österle, H. Rodriguez-Alvarez, D. Greiner, C. A. Kaufmann, and T. Unold · 2017
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Method of artificial intelligence algorithm to improve the automation level of rietveld refinement
Zhenjie Feng, Q. Hou, Y. Zheng, W. Ren, Junyi Ge, Tao Li, Cheng Cheng, Wencong Lu, S. Cao, Jincang Zhang, and Tong-Yi Zhang · 2018
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Fast and interpretable classification of small x-ray diffraction datasets using data augmentation and deep neural networks
Felipe Oviedo, Zekun Ren, Shijing Sun, C. Settens, Zhe Liu, N. T. P. Hartono, Savitha Ramasamy, Brian L. DeCost, S. Tian, Giuseppe Romano, A. Gilad Kusne, and T. Buonassisi · 2018
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Neural network based classification of crystal symmetries from x-ray diffraction patterns
Pascal M. Vecsei, Kenny Choo, Johan Chang, and T. Neupert · 2018
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PAULING FILE - towards a holistic view
Pierre Villars, Karin Cenzual, Roman Gladyshevskii, and Shuichi Iwata · 2018
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Sharing powder diffraction raw data: challenges and benefits
M. Aranda · 2018
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An open experimental database for exploring inorganic materials
Andriy Zakutayev, Nick Wunder, Marcus Schwarting, John D. Perkins, Robert White, Kristin Munch, William Tumas, and Caleb Phillips · 2018
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Surfactant-free synthesis of monodisperse cobalt oxide nanoparticles of tunable size and oxidation state developed by factorial design
Moritz Wolf, Nico Fischer, and Michael Claeys · 2018
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Single-crystal Cu(In,Ga)Se2solar cells grown on GaAs substrates
Jiro Nishinaga, Takehiko Nagai, Takeyoshi Sugaya, Hajime Shibata, and Shigeru Niki · 2018
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High-throughput experiments facilitate materials innovation: A review
Yihao Liu, Ziheng Hu, Zhiguang Suo, Lianzhe Hu, Lingyan Feng, Xiuqing Gong, Yi Liu, and Jincang Zhang · 2019
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Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods
A. Ludwig · 2019
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Rietveld Refinement: Practical Powder Diffraction Pattern Analysis using TOPAS
Robert E. Dinnebier, Andreas Leineweber, and John S. O. Evans · 2019
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Deep materials informatics: Applications of deep learning in materials science
Ankit Agrawal and A. Choudhary · 2019
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The powder diffraction file: a quality materials characterization database
S. Gates-Rector and T. Blanton · 2019
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Synthesis, characterisation and water–gas shift activity of nano-particulate mixed-metal (Al, Ti) cobalt oxides
Moritz Wolf, Stephen J. Roberts, Wijnand Marquart, Ezra J. Olivier, Niels T. J. Luchters, Emma K. Gibson, C. Richard A. Catlow, Jan. H. Neethling, Nico Fischer, and Michael Claeys · 2019
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Revealing the dynamics of hybrid metal halide perovskite formation via multimodal in situ probes
Tze-Bin Song, Zhenghao Yuan, Megumi Mori, Faizan Motiwala, Gideon Segev, Eloïse Masquelier, Camelia V. Stan, Jonathan L. Slack, Nobumichi Tamura, and Carolin M. Sutter-Fella · 2019
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Self-driving laboratory for accelerated discovery of thin-film materials
B. P. MacLeod, F. G. L. Parlane, T. D. Morrissey, F. Häse, L. M. Roch, K. E. Dettelbach, R. Moreira, L. P. E. Yunker, M. B. Rooney, J. R. Deeth, V. Lai, G. J. Ng, H. Situ, R. H. Zhang, M. S. Elliott, T. H. Haley, D. J. Dvorak, A. Aspuru-Guzik, J. E. Hein, and C. P. Berlinguette · 2020
Cited alongside, same era.
Automated crystal structure analysis based on blackbox optimisation
Yoshihiko Ozaki, Yuta Suzuki, T. Hawai, Kotaro Saito, Masaki Onishi, and K. Ono · 2020
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Rapid identification of x-ray diffraction patterns based on very limited data by interpretable convolutional neural networks
Hong Wang, Yunchao Xie, Dawei Li, Heng Deng, Yun-Zhi Zhao, Ming Xin, and Jian Lin · 2020
Cited alongside, same era.
Crystal symmetry classification from powder x-ray diffraction patterns using a convolutional neural network
A. N. Zaloga, V. V. Stanovov, O. E. Bezrukova, P. S. Dubinin, and I. S. Yakimov · 2020
Cited alongside, same era.
Symmetry prediction and knowledge discovery from x-ray diffraction patterns using an interpretable machine learning approach
Simxrd-4m: Big simulated x-ray diffraction data and crystal symmetry classification benchmark
Bin Cao, Yang Liu, Zinan Zheng, Ruifeng Tan, Jia Li, and Tong-yi Zhang · 2024
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Raw diffraction data and reproducibility
Loes M. J. Kroon-Batenburg, Matthew P. Lightfoot, Natalie T. Johnson, and John R. Helliwell · 2024
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Accelerating materials discovery: Automated identification of prospects from x-ray diffraction data in fast screening experiments
Jan Schuetzke, Simon Schweidler, Friedrich R. Muenke, Andre Orth, Anurag D. Khandelwal, Ben Breitung, Jasmin Aghassi-Hagmann, and Markus Reischl · 2024
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Pearson’s crystal data product description
ASM International · 2024
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Mpds access link
P. Villars · 2024
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Yuta Suzuki, H. Hino, T. Hawai, Kotaro Saito, M. Kotsugi, and K. Ono · 2020
Cited alongside, same era.
A comprehensive survey on transfer learning
Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, and Qing He · 2020
Cited alongside, same era.
Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification
Khawla Seddiki, Philippe Saudemont, Frédéric Precioso, Nina Ogrinc, Maxence Wisztorski, Michel Salzet, Isabelle Fournier, and Arnaud Droit · 2020
Cited alongside, same era.
Fifty years of rietveld refinement: Methodology and guidelines in superconductors and functional magnetic nanoadsorbents
Diego Alberto Flores Cano, Anais Roxana Chino Quispe, Renzo Rueda Vellasmin, Joao Andre Ocampo Anticona, J. González, and J. A. Ramos Guivar · 2021
Cited alongside, same era.
Automating crystal-structure phase mapping by combining deep learning with constraint reasoning
Di Chen, Yiwei Bai, Sebastian Ament, Wenting Zhao, Dan Guevarra, Lan Zhou, Bart Selman, R. Bruce van Dover, John M. Gregoire, and Carla P. Gomes · 2021
Cited alongside, same era.
A deep convolutional neural network for real-time full profile analysis of big powder diffraction data
H. Dong, K. Butler, D. Matras, S. W. T. Price, Y. Odarchenko, Rahul Khatry, Andrew Thompson, V. Middelkoop, S. Jacques, A. Beale, and A. Vamvakeros · 2021
Cited alongside, same era.
Automated prediction of lattice parameters from x-ray powder diffraction patterns
Sathya R. Chitturi, Daniel Ratner, Richard C. Walroth, Vivek Thampy, Evan J. Reed, Mike Dunne, Christopher J. Tassone, and Kevin H. Stone · 2021
Cited alongside, same era.
A deep crystal structure identification system for x-ray diffraction patterns
Abhik Chakraborty and Raksha Sharma · 2021
Cited alongside, same era.
Crystal Impact · 2024
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Pdf5 product description
ICDD · 2024
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Rruff access link
University of Arizona Department of Geosciences · 2024
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Crystallography open database
COD maintainers · 2024
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Icsd access link
FIZ Karlsruhe · 2024
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Cambridge structural database access link
Cambridge Crystallographic Data Centre · 2024
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Materials project database website access link
Materials Project · 2024
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Crystallographic and crystallochemical database website access link
Russian Academy of Sciences Institute of Experimental Mineralogy · 2024
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Bilbao incommensurate crystal structure database access link
University of the Basque Country · 2024
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Mineralogy database access link
David Barthelmy · 2024
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Iucr raw data letters access link
International Union of Crystallography (IUCr) · 2024
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Crystal lattice-structures access link
U.S. Naval Research Laboratory · 2024
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Athena mineral database access link
Pierre Perroud · 2024
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Protein data bank access link
Research Collaboratory for Structural Bioinformatics · 2024
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Advancing high-throughput combinatorial aging studies of hybrid perovskite thin films via precise automated characterization methods and machine learning assisted analysis
Alexander Wieczorek, Austin G. Kuba, Jan Sommerhäuser, Luis Nicklaus Caceres, Christian M. Wolff, and Sebastian Siol · 2024
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Pdf5+ license
ICDD · 2025
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High-throughput experimental database statistics
National Renewable Energy Laborator · 2025
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A deep-learning technique for phase identification in multiphase inorganic compounds using synthetic xrd powder patterns
Jin-Woong Lee, Woon Bae Park, Jin Hee Lee, Satendra Pal Singh, and Kee-Sun Sohn · 2041
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Automated classification of big x-ray diffraction data using deep learning models
Jerardo E. Salgado, Samuel Lerman, Zhaotong Du, Chenliang Xu, and Niaz Abdolrahim · 2057
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