Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Cited by (1,039)

Items 301–400 of 1,039

1. Xenon Gas Separation and Storage Using Metal-Organic Frameworks
   Debasis Banerjee, Cory M. Simon, Sameh K. Elsaidi · 2018 · Chem
2. Discovery of high-entropy ceramics via machine learning
   Kevin Kaufmann, Daniel Maryanovsky, William M. Mellor · 2020 · npj Computational Materials
3. Phase transformation strengthening of high-temperature superalloys
   Timothy M. Smith, Bryan David Esser, Nikolas Antolin et al. · 2016 · Nature Communications
4. Computationally guided discovery of thermoelectric materials
   Prashun Gorai, Vladan Stevanović, Eric S. Toberer · 2017 · Nature Reviews Materials
5. Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning
   Prasanna V. Balachandran, Benjamin A. Kowalski, Alp Sehirlioglu, Turab Lookman · 2018 · Nature Communications
6. Unified representation of molecules and crystals for machine learning
   Haoyan Huo, Matthias Rupp · 2022 · Machine Learning Science and Technology
7. Advances in half-Heusler alloys for thermoelectric power generation
   Robert J. Quinn, Jan‐Willem G. Bos · 2021 · Materials Advances
8. What Are the Best Materials To Separate a Xenon/Krypton Mixture?
   Cory M. Simon, Rocío Mercado, Sondre K. Schnell, Berend Smit, Maciej Harańczyk · 2015 · Chemistry of Materials
9. Performance-Based Screening of Porous Materials for Carbon Capture
   Farmahini, Amir H., Krishnamurthy, Shreenath, Friedrich, Daniel, Brandani, Stefano, Sarkisov, Lev · 2021 · Chemical Reviews
10. Heusler alloys: Past, properties, new alloys, and prospects
    Sheron Stephany Tavares, Kesong Yang, Marc André Meyers · 2022 · Progress in Materials Science
11. Optimization of thermoelectric efficiency in SnTe: the case for the light band
    Min Zhou, Zachary M. Gibbs, Heng Wang, Yemao Han, Caini Xin, Laifeng Li, Gerald Jeffrey Snyder · 2014 · Physical Chemistry Chemical Physics
12. Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry
    Christopher J. Bartel, Samantha L. Millican, Ann M. Deml, John R. Rumptz, William Tumas, Alan W. Weimer, Stephan Lany, Vladan Stevanović, Charles B. Musgrave, Aaron M. Holder · 2018 · Nature Communications
13. A critical examination of compound stability predictions from machine-learned formation energies
    Bartel, Christopher J., Trewartha, Amalie, Wang, Qi, Dunn, Alexander, Jain, Anubhav, Ceder, Gerbrand · 2020 · npj Computational Materials
14. Interrelationships among Grain Size, Surface Composition, Air Stability, and Interfacial Resistance of Al-Substituted Li 7 La 3 Zr 2 O 12 Solid Electrolytes
    Lei Cheng, Chenghao Wu, Angélique Jarry et al. · 2015 · ACS Applied Materials & Interfaces
15. Direct Synthesis of Intermetallic Platinum–Alloy Nanoparticles Highly Loaded on Carbon Supports for Efficient Electrocatalysis
    Tae Yong Yoo, Ji Mun Yoo, Arun Kumar Sinha, Megalamane Siddaramappa Bootharaju, Euiyeon Jung, Hyeon Seok Lee, Byoung‐Hoon Lee, Jiheon Kim, Wytse Hooch Antink, Yong Min Kim et al. · 2020 · Journal of the American Chemical Society
16. Chemical Speciation, Plant Uptake, and Toxicity of Heavy Metals in Agricultural Soils
    Minori Uchimiya, Desmond I. Bannon, Hiromi Nakanishi, Murray B. McBride, Marc Adrian Williams, Toshihiro Yoshihara · 2020 · Journal of Agricultural and Food Chemistry
17. Expanding Frontiers of Ultraviolet Nonlinear Optical Materials with Fluorophosphates
    Bingbing Zhang, Guopeng Han, Ying Wang · 2018 · Chemistry of Materials
18. Advancements in MXene-Polymer composites for various biomedical applications
    Suchi Mercy George, Balasubramanian Kandasubramanian · 2019 · Ceramics International
19. Generative Adversarial Networks for Crystal Structure Prediction
    Sungwon Kim, Juhwan Noh, Geun Ho Gu, Alán Aspuru‐Guzik, Yousung Jung · 2020 · ACS Central Science
20. Rechargeable Alkali-Ion Battery Materials: Theory and Computation
    Anton Van der Ven, Zhi Deng, Swastika Banerjee, Shyue Ping Ong · 2020 · Chemical Reviews
21. High-throughput screening of inorganic compounds for the discovery of novel dielectric and optical materials
    Ioannis Petousis, David Mrdjenovich, Eric Ballouz, Miao Liu, Donny Winston, Wei Chen, Tanja Graf, Thomas D. Schladt, Kristin Aslaug Persson, Fritz B. Prinz · 2017 · Scientific Data
22. Advancing photoreforming of organics: highlights on photocatalyst and system designs for selective oxidation reactions
    Cui Ying Toe, Constantine Tsounis, Jiajun Zhang, Hassan Masood, Denny Gunawan, Jason Anthony Scott, Rose Amal · 2021 · Energy & Environmental Science
23. Deep neural networks for accurate predictions of crystal stability
    Weike Ye, Chi Chen, Zhenbin Wang, Iek-Heng Chu, Shyue Ping Ong · 2018 · Nature Communications
24. Compositionally restricted attention-based network for materials property predictions
    Anthony Wang, Steven K. Kauwe, Ryan Murdock, Taylor D. Sparks · 2021 · npj Computational Materials
25. Text-mined dataset of inorganic materials synthesis recipes
    Olga Kononova, Haoyan Huo, Tanjin He, Ziqin Rong, Tiago Botari, Wenhao Q. Sun, Vahe Tshitoyan, Gerbrand Ceder · 2019 · Scientific Data
26. Understanding thermoelectric properties from high-throughput calculations: trends, insights, and comparisons with experiment
    Wei Chen, Jan‐Hendrik Pöhls, Geoffroy Hautier, Danny Broberg, Saurabh Bajaj, Umut Aydemir, Zachary M. Gibbs, Hong Zhu, Mark Asta, Gerald Jeffrey Snyder et al. · 2016 · Journal of Materials Chemistry C
27. Role of Na+ Interstitials and Dopants in Enhancing the Na+ Conductivity of the Cubic Na3PS4 Superionic Conductor
    Zhuoying Zhu, Iek‐Heng Chu, Zhi Deng, Shyue Ping Ong · 2015 · Chemistry of Materials
28. Machine learned features from density of states for accurate adsorption energy prediction
    Victor Fung, Guoxiang Hu, Panchapakesan Ganesh, Bobby G. Sumpter · 2021 · Nature Communications
29. Machine learning approaches for the prediction of materials properties
    Siwar Chibani, François‐Xavier Coudert · 2020 · APL Materials
30. Predicting the thermodynamic stability of perovskite oxides using machine learning models
    Wei Li, Ryan M. Jacobs, Dane D. Morgan · 2018 · Computational Materials Science
31. The Aluminum-Ion Battery: A Sustainable and Seminal Concept?
    Tilmann Leisegang, Falk Meutzner, Matthias Zschornak · 2019 · Frontiers in Chemistry
32. Strategies Based on Nitride Materials Chemistry to Stabilize Li Metal Anode
    Yizhou Zhu, Xingfeng He, Yifei Mo · 2017 · Advanced Science
33. Unveiling the Stable Nature of the Solid Electrolyte Interphase between Lithium Metal and LiPON via Cryogenic Electron Microscopy
    Diyi Cheng, Thomas A. Wynn, Xuefeng Wang, Shen Wang, Minghao Zhang, Ryosuke Shimizu, Shuang Bai, Han Nguyen, Chengcheng Fang, Min-cheol Kim et al. · 2020 · Joule
34. Deep acceptors and their diffusion in Ga2O3
    Hartwin Peelaers, John L. Lyons, Joel Basile Varley · 2019 · APL Materials
35. A High Performing Zn‐Ion Battery Cathode Enabled by In Situ Transformation of V 2 O 5 Atomic Layers
    Yanying Lu, Tianyu Zhu, Wessel van den Bergh, Morgan Stefik, Kevin Huang · 2020 · Angewandte Chemie International Edition
36. Electronic-structure methods for materials design
    Nicola Marzari, Andrea Ferretti, Chris M. Wolverton · 2021 · Nature Materials
37. Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage
    Aaron W. Thornton, Cory M. Simon, Jihan Kim, Ohmin Kwon, Kathryn S. Deeg, Kristina Konstas, Steven J. Pas, Matthew R. Hill, David Alan Winkler, Maciej Harańczyk et al. · 2017 · Chemistry of Materials
38. Manganese oxidation as the origin of the anomalous capacity of Mn-containing Li-excess cathode materials
    Maxwell D. Radin, Julija Vinckevičiu̅tė, Ram Seshadri · 2019 · Nature Energy
39. Non-Abelian band topology in noninteracting metals
    Quansheng Wu, Alexey A. Soluyanov, Tomáš Bzdušek · 2019 · Science
40. A guide to comprehensive phosphor discovery for solid-state lighting
    Shruti Hariyani, Małgorzata Sójka, Anant Setlur · 2023 · Nature Reviews Materials
41. Tuning mobility and stability of lithium ion conductors based on lattice dynamics
    Sokseiha Muy, John Christopher Bachman, Livia Giordano et al. · 2018 · Energy & Environmental Science
42. Materials Design Principles for Air‐Stable Lithium/Sodium Solid Electrolytes
    Yizhou Zhu, Yifei Mo · 2020 · Angewandte Chemie International Edition
43. Computational characterization and prediction of metal–organic framework properties
    François‐Xavier Coudert, Alain H. Fuchs · 2015 · Coordination Chemistry Reviews
44. Autonomous Discovery in the Chemical Sciences Part II: Outlook
    Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen · 2019 · Angewandte Chemie International Edition
45. Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm
    Dunn, A, Wang, Q, Alex M. Ganose, Daniel Dopp, Anubhav Jain · 2020 · eScholarship (California Digital Library)
46. Convolutional Neural Network of Atomic Surface Structures To Predict Binding Energies for High-Throughput Screening of Catalysts
    Seoin Back, Junwoong Yoon, Nianhan Tian, Wen Zhong, Kevin Tran, Zachary W. Ulissi · 2019 · The Journal of Physical Chemistry Letters
47. Doping Lanthanide Ions in Colloidal Semiconductor Nanocrystals for Brighter Photoluminescence
    Riccardo Marin, Daniel Jaque · 2020 · Chemical Reviews
48. New opportunities for materials informatics: Resources and data mining techniques for uncovering hidden relationships
    Jain, Anubhav, Hautier, Geoffroy, Ong, Shyue Ping, Persson, Kristin · 2016 · Journal of Materials Research
49. Extracting Knowledge from Data through Catalysis Informatics
    Andrew James Medford, M. Ross Kunz, Sarah M. Ewing, Tammie L. Borders, Rebecca Fushimi · 2018 · ACS Catalysis
50. Cellular Auxetic Structures for Mechanical Metamaterials: A Review
    Parth U. Kelkar, Hyun Soo Kim, Kyung‐Hoon Cho, Joon Young Kwak, Chong‐Yun Kang, Hyun‐Cheol Song · 2020 · Sensors
51. Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation
    Rui Fang Ding, Junhong Chen, Yuxin Chen, Jianguo Liu, Yoshio Bando, Xuebin Wang · 2024 · Chemical Society Reviews
52. molSimplify: A toolkit for automating discovery in inorganic chemistry
    Efthymios I. Ioannidis, Terry Z. H. Gani, Heather J. Kulik · 2016 · Journal of Computational Chemistry
53. Reconfigurable perovskite nickelate electronics for artificial intelligence
    Haitian Zhang, Tae Joon Park, A N M Nafiul Islam, Dat Tran, Sukriti Manna, Qi Wang, Sandip Mondal, Haoming Yu, Suvo Banik, Shaobo Cheng et al. · 2022 · Science
54. Vitamin C-Assisted Synthesized Mn–Co Oxides with Improved Oxygen Vacancy Concentration: Boosting Lattice Oxygen Activity for the Air-Oxidation of 5-(Hydroxymethyl)furfural
    Huai Liu, Wenlong Jia, Xin Hua Yu · 2021 · ACS Catalysis
55. Atomistic calculations and materials informatics: A review
    Logan T. Ward, Chris M. Wolverton · 2016 · Current Opinion in Solid State and Materials Science
56. Isolated copper–tin atomic interfaces tuning electrocatalytic CO2 conversion
    Wenhao Ren, Xin Tan, Jiangtao Qu, Se‐Si Li, Jiantao Li, Xin Liu, Simon Peter Ringer, Julie M. Cairney, Kai‐Xue Wang, Sean Campbell Smith et al. · 2021 · Nature Communications
57. Computational chemistry for water-splitting electrocatalysis
    Miao, Licheng, Jia, Wenqi, Cao, Xuejie, Jiao, Lifang · 2024 · Chemical Society Reviews
58. Design of template-stabilized active and earth-abundant oxygen evolution catalysts in acid
    Michael Huynh, Tuncay Özel, Chong Liu, Eric C. Lau, Daniel G. Nocera · 2017 · Chemical Science
59. Materials science with large-scale data and informatics: Unlocking new opportunities
    Joanne Hill, Gregory J. Mulholland, Kristin Aslaug Persson, Ram Seshadri, Chris M. Wolverton, Bryce Meredig · 2016 · MRS Bulletin
60. Design of functional and sustainable polymers assisted by artificial intelligence
    Tran Doan Huan, Rishi Gurnani, Chiho Kim, Ghanshyam Pilania, Ha-Kyung Kwon, Ryan P. Lively, Rampi Ramprasad · 2024 · Nature Reviews Materials
61. First-Principles Density Functional Theory Modeling of Li Binding: Thermodynamics and Redox Properties of Quinone Derivatives for Lithium-Ion Batteries
    Ki Chul Kim, Tianyuan Liu, Seung Woo Lee · 2016 · Journal of the American Chemical Society
62. Two-Dimensional Intrinsic Half-Metals With Large Spin Gaps
    Michael W Ashton, Ðorđe Gluhović, Susan B. Sinnott · 2017 · Nano Letters
63. Wearable, ultrathin and transparent bacterial celluloses/MXene film with Janus structure and excellent mechanical property for electromagnetic interference shielding
    Chang Ma, Wentao Cao, Wei Zhang · 2020 · Chemical Engineering Journal
64. Part I: Theoretical predictions of preferential oxidation in refractory high entropy materials
    Lavina Backman, Joshua Gild, Jian Luo · 2020 · Acta Materialia
65. An ab initio electronic transport database for inorganic materials
    Francesco Ricci, Wei Chen, Umut Aydemir, Gerald Jeffrey Snyder, Gian‐Marco Rignanese, Anubhav Jain, Geoffroy Hautier · 2017 · Scientific Data
66. Computational Studies of Electrode Materials in Sodium‐Ion Batteries
    Qiang Bai, Lufeng Yang, Hailong Chen · 2018 · Advanced Energy Materials
67. Wigner Formulation of Thermal Transport in Solids
    Michele Simoncelli, Nicola Marzari, Francesco Mauri · 2022 · Physical Review X
68. Thermodynamic Stability Landscape of Halide Double Perovskites via High‐Throughput Computing and Machine Learning
    Li, Zhenzhu, Xu, Qichen, Sun, Qingde, Hou, Zhufeng, Yin, Wan‐Jian · 2019 · Advanced Functional Materials
69. Li 3 BO 3 –Li 2 CO 3 : Rationally Designed Buffering Phase for Sulfide All-Solid-State Li-Ion Batteries
    Sung Hoo Jung, Kyungbae Oh, Young Jin Nam · 2018 · Chemistry of Materials
70. How to GIWAXS: Grazing Incidence Wide Angle X‐Ray Scattering Applied to Metal Halide Perovskite Thin Films
    Julian A. Steele, Eduardo Solano, David F. Hardy, Damara G. Dayton, Dylan M. Ladd, Keith P. White, Peng Chen, Jingwei Hou, Haowei Huang, Rafikul Ali Saha et al. · 2023 · Advanced Energy Materials
71. Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals
    Florbela Pereira, Kaixia Xiao, Diogo A. R. S. Latino, Chengcheng Wu, Qingyou Zhang, João Aires‐de‐Sousa · 2016 · Journal of Chemical Information and Modeling
72. Thermodynamics of Phase Selection in MnO2 Framework Structures through Alkali Intercalation and Hydration
    Daniil A. Kitchaev, Stephen T. Dacek, Wenhao Q. Sun · 2017 · Journal of the American Chemical Society
73. Liquid-like thermal conduction in intercalated layered crystalline solids
    B. Li, Hui Wang, Y. Kawakita, Qiang Zhang, Mikhail Feygenson, Hulei Yu, Di Wu, Koji Ohara, Tatsuya Kikuchi, Kaoru Shibata et al. · 2018 · Nature Materials
74. Identifying Pb-free perovskites for solar cells by machine learning
    Jino Im, Sungwon Lee, Tae-Wook Ko, Hyun Woo Kim, YunKyong Hyon, Hyunju Chang · 2019 · npj Computational Materials
75. Machine Learning Approaches for Thermoelectric Materials Research
    Tian Wang, Cheng Zhang, Hichem Snoussi, Gang Zhang · 2019 · Advanced Functional Materials
76. Invited review: Machine learning for materials developments in metals additive manufacturing
    Nathan Scott Johnson, Praveen S. Vulimiri, Albert C. To, Xin-Ya Zhang, Craig Brice, Branden B. Kappes, Aaron P. Stebner · 2020 · Additive manufacturing
77. Mechanistic Origin of the High Performance of Yolk@Shell Bi2S3@N-Doped Carbon Nanowire Electrodes
    Longze Zhao, Hong‐Hui Wu, Chenghao Yang et al. · 2018 · ACS Nano
78. Machine learning in materials genome initiative: A review
    Yingli Liu, Chen Xu Niu, Zhuo Wang, Yong Gan, Yan Hong Zhu, Shuhong Sun, Tao Shen · 2020 · Journal of Material Science and Technology
79. Emerging Chalcogenide Thin Films for Solar Energy Harvesting Devices
    Shreyash Sudhakar Hadke, Menglin Huang, Chao Chen · 2021 · Chemical Reviews
80. Lithium superionic conductors with corner-sharing frameworks
    KyuJung Jun, Yingzhi Sun, Yihan Xiao · 2022 · Nature Materials
81. Scalable Parallel Algorithm for Graph Neural Network Interatomic Potentials in Molecular Dynamics Simulations
    Yutack Park, Jaesun Kim, Seungwoo Hwang, Seungwu Han · 2024 · Journal of Chemical Theory and Computation
82. The Critical Raw Materials in Cutting Tools for Machining Applications: A Review
    A. Rizzo, Saurav Goel, Maria Luisa Grilli · 2020 · Materials
83. Progress and prospects for accelerating materials science with automated and autonomous workflows
    Helge Sören Stein, John M. Gregoire · 2019 · Chemical Science
84. 14 examples of how LLMs can transform materials science and chemistry: A reflection on a large language model hackathon
    Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander, Badhwar, Shruti, Bocarsly, Joshua D., Bran, Andres M., Bringuier, Stefan, Brinson, L. Catherine, Choudhary, Kamal, Circi, Defne et al. · 2023 · Digital Discovery
85. Insights into the Performance Limits of the Li7P3S11 Superionic Conductor: A Combined First-Principles and Experimental Study
    Iek‐Heng Chu, Han Nguyen, Sunny Hy, Yuh‐Chieh Lin, Zhenbin Wang, Zihan Xu, Zhi Deng, Ying Shirley Meng, Shyue Ping Ong · 2016 · ACS Applied Materials & Interfaces
86. Lithium anode interlayer design for all-solid-state lithium-metal batteries
    Zeyi Wang, Jiale Xia, Xiao Yuan Ji · 2024 · Nature Energy
87. Single‐Atom Catalytic Materials for Advanced Battery Systems
    Chao Lü, Ruyue Fang, Xi Chen · 2020 · Advanced Materials
88. Abnormal self-discharge in lithium-ion batteries
    Won Mo Seong, Kyu‐Young Park, Myeong Hwan Lee · 2018 · Energy & Environmental Science
89. Acidic Oxygen Evolution Reaction Activity–Stability Relationships in Ru-Based Pyrochlores
    McKenzie A. Hubert, Anjli M. Patel, Alessandro Gallo, Yunzhi Liu, Eduardo Valle, Micha Ben‐Naim, Joel Sanchez, Dimosthenis Sokaras, Robert Sinclair, Jens K. Nørskov et al. · 2020 · ACS Catalysis
90. Factors Governing Oxygen Vacancy Formation in Oxide Perovskites
    Robert B. Wexler, Gopalakrishnan Sai Gautam, Ellen B. Stechel, Emily A. Carter · 2021 · Journal of the American Chemical Society
91. Adaptive Strategies for Materials Design using Uncertainties
    Prasanna V. Balachandran, Dezhen Xue, James P. Theiler, John Hogden, Turab Lookman · 2016 · Scientific Reports
92. Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules
    Zongrui Pei, Junqi Yin, Jeffrey A. Hawk, David E. Alman, Michael C. Gao · 2020 · npj Computational Materials
93. Revisiting metal fluorides as lithium-ion battery cathodes
    Xiao Hua, Alexander S. Eggeman, Elizabeth Castillo‐Martínez et al. · 2021 · Nature Materials
94. Learning properties of ordered and disordered materials from multi-fidelity data
    Chi Chen, Yunxing Zuo, Weike Ye, Xiangguo Li, Shyue Ping Ong · 2021 · Nature Computational Science
95. Boosting the interfacial superionic conduction of halide solid electrolytes for all-solid-state batteries
    Hiram Kwak, Jae‐Seung Kim, Daseul Han et al. · 2023 · Nature Communications
96. General-purpose machine-learned potential for 16 elemental metals and their alloys
    Keke Song, Rui Zhao, Jiahui Liu, Yanzhou Wang, Eric Lindgren, Yong Wang, Shunda Chen, Ke Wei Xu, Ting Liang, Penghua Ying et al. · 2024 · Nature Communications
97. Crystalline nickel manganese antimonate as a stable water-oxidation catalyst in aqueous 1.0 M H 2 SO 4
    Ivan A. Moreno‐Hernandez, Clara MacFarland, Carlos G. Read, Kimberly M. Papadantonakis, Bruce S. Brunschwig, Nathan S. Lewis · 2017 · Energy & Environmental Science
98. A polymer dataset for accelerated property prediction and design
    Tran Doan Huan, Arun Mannodi‐Kanakkithodi, Chiho Kim, Vinit Sharma, Ghanshyam Pilania, Rampi Ramprasad · 2016 · Scientific Data
99. High-throughput density-functional perturbation theory phonons for inorganic materials
    Guido Petretto, Shyam Dwaraknath, Henrique Pereira Coutada Miranda, Donny Winston, Matteo Giantomassi, Michiel J. van Setten, Xavier Gonze, Kristin Aslaug Persson, Geoffroy Hautier, Gian‐Marco Rignanese · 2018 · Scientific Data
100. A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds
     de Jong, Maarten, Chen, Wei, Notestine, Randy, Persson, Kristin, Ceder, Gerbrand, Jain, Anubhav, Asta, Mark, Gamst, Anthony · 2016 · Scientific Reports