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

Cited by (1,039)

Items 101–200 of 1,039

1. Recent progress of the Computational 2D Materials Database (C2DB)
   Morten Niklas Gjerding, Alireza Taghizadeh, Asbjørn Rasmussen, Sajid Ali, Fabian Bertoldo, Thorsten Deilmann, Nikolaj Rørbæk Knøsgaard, Mads Kruse, Ask Hjorth Larsen, Simone Manti et al. · 2021 · 2D Materials
2. Site-Occupation-Tuned Superionic Li x ScCl 3+ x Halide Solid Electrolytes for All-Solid-State Batteries
   Jianwen Liang, Xiaona Li, Shuo Wang, Keegan R. Adair, Weihan Li, Yang Zhao, Changhong Wang, Yongfeng Hu, Li Zhang, Shangqian Zhao et al. · 2020 · Journal of the American Chemical Society
3. The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design
   Kamal Choudhary, Kevin F. Garrity, Andrew C. E. Reid, Brian DeCost, Adam J. Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, A. Gilad Kusne, Andrea Centrone et al. · 2020 · npj Computational Materials
4. Deep Learning in Chemistry
   Mater, Adam C., Coote, Michelle L. · 2019 · Journal of Chemical Information and Modeling
5. New frontiers for the materials genome initiative
   Juan Pablo, Nicholas E. Jackson, Michael A. Webb, Long‐Qing Chen, Joel E. Moore, Dane D. Morgan, Ryan M. Jacobs, Tresa M. Pollock, Darrell G. Schlom, Eric S. Toberer et al. · 2019 · npj Computational Materials
6. Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery
   Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler, Rachel A. Caruso · 2022 · Chemical Reviews
7. Clarifying the relationship between redox activity and electrochemical stability in solid electrolytes
   Tammo K. Schwietert, Violetta A. Arszelewska, Chao Wang, Chuang Yu, Alexandros Vasileiadis, Niek J. J. de Klerk, Jart Hageman, Thomas Hupfer, Ingo Kerkamm, Yaolin Xu et al. · 2020 · Nature Materials
8. A generative model for inorganic materials design
   Zeni, Claudio, Pinsler, Robert, Zügner, Daniel, Fowler, Andrew, Horton, Matthew, Fu, Xiang, Wang, Zilong, Shysheya, Aliaksandra, Crabbé, Jonathan, Ueda, Shoko et al. · 2025 · Nature
9. Gold-supported cerium-doped NiOx catalysts for water oxidation
   Jia Wei Desmond Ng, Max García Melchor, Michal Bajdich, Pongkarn Chakthranont, Charlotte Kirk, Aleksandra Vojvodić, Thomas Francisco Jaramillo · 2016 · Nature Energy
10. High Entropy Alloy Electrocatalytic Electrode toward Alkaline Glycerol Valorization Coupling with Acidic Hydrogen Production
    Linfeng Fan, Yaxin Ji, Genxiang Wang, Junxiang Chen, Kai Chen, Xi Liu, Zhenhai Wen · 2022 · Journal of the American Chemical Society
11. FireWorks: a dynamic workflow system designed for high‐throughput applications
    Anubhav Jain, Shyue Ping Ong, Wei Chen, Bharat Medasani, Xiaohui Qu, Michael Kocher, Miriam Brafman, Guido Petretto, Gian‐Marco Rignanese, Geoffroy Hautier et al. · 2015 · Concurrency and Computation Practice and Experience
12. A disordered rock salt anode for fast-charging lithium-ion batteries
    Haodong Liu, Zhuoying Zhu, Qizhang Yan, Sicen Yu, Xin He, Yan Chen, Rui Zhang, Lu Ma, Tongchao Liu, Matthew Li et al. · 2020 · Nature
13. The origin of high electrolyte–electrode interfacial resistances in lithium cells containing garnet type solid electrolytes
    Lei Cheng, Ethan J. Crumlin, Wei Chen et al. · 2014 · Physical Chemistry Chemical Physics
14. Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery
    Andrew Rosen, Shaelyn M. Iyer, Debmalya Ray, Zhenpeng Yao, Alán Aspuru‐Guzik, Laura Gagliardi, Justin M. Notestein, Randall Q. Snurr · 2021 · Matter
15. The 2022 Plasma Roadmap: low temperature plasma science and technology
    Igor Adamovich, Sumit Agarwal, Eduardo Ahedo, L. L. Alves, Scott Baalrud, Natalia Yu. Babaeva, Annemie Bogaerts, Anne Bourdon, Peter Bruggeman, Cristina Canal et al. · 2022 · Journal of Physics D Applied Physics
16. Reactive boride infusion stabilizes Ni-rich cathodes for lithium-ion batteries
    Moonsu Yoon, Yanhao Dong, Jaeseong Hwang, Jaekyung Sung, Hyungyeon Cha, Kihong Ahn, Yimeng Huang, Seok Ju Kang, Ju Li, Jaephil Cho · 2021 · Nature Energy
17. Challenges to developing materials for the transport and storage of hydrogen
    Mark D. Allendorf, Vitalie Stavila, Jonathan L. Snider, Matthew David Witman, Mark Bowden, Kriston Brooks, Ba L. Tran, Tom S. Autrey · 2022 · Nature Chemistry
18. Spinel compounds as multivalent battery cathodes: a systematic evaluation based on ab initio calculations
    Miao Liu, Ziqin Rong, Rahul Malik, Pieremanuele Canepa, Anubhav Jain, Gerbrand Ceder, Kristin Aslaug Persson · 2014 · Energy & Environmental Science
19. High temperature solid-lubricating materials: A review
    Shengyu Zhu, Jun Cheng, Zhuhui Qiao · 2018 · Tribology International
20. Machine learning for a sustainable energy future
    Zhenpeng Yao, Yanwei Lum, Andrew K. Johnston, L.M. Mejía-Mendoza, Xin Zhou, Yonggang Wen, Alán Aspuru‐Guzik, Edward Hartley Sargent, Zhi Wei Seh · 2022 · Nature Reviews Materials
21. Stability of electrocatalytic OER: from principle to application
    Li, HuangJingWei, Lin, Yu, Duan, Junyuan, Wen, Qunlei, Liu, Youwen, Zhai, Tianyou · 2024 · Chemical Society Reviews
22. Wide Band Gap Chalcogenide Semiconductors
    Rachel Woods‐Robinson, Yanbing Han, Hanyu Zhang, Tursun Ablekim, Imran Khan, Kristin Aslaug Persson, Andriy Zakutayev · 2020 · Chemical Reviews
23. Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices
    Anthony Wang, Ryan Murdock, Steven K. Kauwe, Anton O. Oliynyk, Aleksander Gurlo, Jakoah Brgoch, Kristin Aslaug Persson, Taylor D. Sparks · 2020 · Chemistry of Materials
24. ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition
    Dipendra Jha, Logan T. Ward, Arindam Paul, Wei‐keng Liao, Alok Choudhary, Chris M. Wolverton, Ankit Agrawal · 2018 · Scientific Reports
25. Precious Metal Free Hydrogen Evolution Catalyst Design and Application
    Anders Agentoft Feidenhans'l, Yagya Narayan Regmi, Chao Wei, Dong Xia, Jakob Kibsgaard, Laurie Ann King · 2024 · Chemical Reviews
26. A Review on Challenges and Successes in Atomic-Scale Design of Catalysts for Electrochemical Synthesis of Hydrogen Peroxide
    Samira Siahrostami, Santiago Jimenez-Villegas, Amir Hassan Bagherzadeh Mostaghimi, Seoin Back, Amir Barati Farimani, Haotian Wang, Kristin Aslaug Persson, Joseph H. Montoya · 2020 · ACS Catalysis
27. Machine learning modeling of superconducting critical temperature
    Valentin Stanev, Corey Oses, A. Gilad Kusne, Efrain Rodriguez, Johnpierre Paglione, Stefano Curtarolo A, Ichiro Takeuchi · 2018 · npj Computational Materials
28. Statistical variances of diffusional properties from ab initio molecular dynamics simulations
    Xingfeng He, Yizhou Zhu, Alexander Rizzolo Epstein, Yifei Mo · 2018 · npj Computational Materials
29. A cost-effective and humidity-tolerant chloride solid electrolyte for lithium batteries
    Kai Wang, Qingyong Ren, Zhenqi Gu et al. · 2021 · Nature Communications
30. CO 2 Capture at Medium to High Temperature Using Solid Oxide-Based Sorbents: Fundamental Aspects, Mechanistic Insights, and Recent Advances
    Matthew T. Dunstan, Felix Donat, Alexander H. Bork, Clare P. Grey, Christoph Rüdiger Müller · 2021 · Chemical Reviews
31. The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles
    Shyue Ping Ong, Shreyas Cholia, Anubhav Jain, Miriam Brafman, Dan Gunter, Gerbrand Ceder, Kristin Aslaug Persson · 2014 · Computational Materials Science
32. Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
    Stephen Wu, Yukiko Kondo, Masa‐aki Kakimoto, Bin Yang, Hironao Yamada, Isao Kuwajima, G. Lambard, Kenta Hongo, Yibin Xu, Junichiro Shiomi et al. · 2019 · npj Computational Materials
33. Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning
    Kim, Edward, Huang, Kevin, Saunders, Adam, McCallum, Andrew, Ceder, Gerbrand, Olivetti, Elsa · 2017 · Chemistry of Materials
34. Ammonia synthesis from N 2 and H 2 O using a lithium cycling electrification strategy at atmospheric pressure
    Joshua M. McEnaney, Aayush R. Singh, Jay A. Schwalbe, Jakob Kibsgaard, John Christopher Lin, Matteo Cargnello, Thomas Francisco Jaramillo, Jens K. Nørskov · 2017 · Energy & Environmental Science
35. Metal–organic framework materials for light-harvesting and energy transfer
    Monica C. So, Gary P. Wiederrecht, Joseph E. Mondloch · 2015 · Chemical Communications
36. High-throughput computational screening of metal–organic frameworks
    Yamil J. Colón, Randall Q. Snurr · 2014 · Chemical Society Reviews
37. Machine learning assisted materials design and discovery for rechargeable batteries
    Yue Liu, Biru Guo, Xinxin Zou, Yajie Li, Siqi Shi · 2020 · Energy storage materials
38. Elastic anisotropy of crystals
    Christopher M. Kube · 2016 · AIP Advances
39. Crystal structure representations for machine learning models of formation energies
    Felix A. Faber, Alexander Lindmaa, O. Anatole von Lilienfeld, Rickard Armiento · 2015 · International Journal of Quantum Chemistry
40. Transition metal-doped Ni-rich layered cathode materials for durable Li-ion batteries
    H. Hohyun Sun, Un‐Hyuck Kim, Jeonghyeon Park · 2021 · Nature Communications
41. Emerging materials intelligence ecosystems propelled by machine learning
    Batra, Rohit, Song, Le, Ramprasad, Rampi · 2020 · Nature Reviews Materials
42. Predicting the Band Gaps of Inorganic Solids by Machine Learning
    Ya Zhuo, Aria Mansouri Tehrani, Jakoah Brgoch · 2018 · The Journal of Physical Chemistry Letters
43. NOMAD: The FAIR concept for big data-driven materials science
    Claudia Draxl, Matthias Scheffler · 2018 · MRS Bulletin
44. Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization
    Atsuto Seko, Atsushi Togo, Hiroyuki Hayashi, Koji Tsuda, Laurent Chaput, Isao Tanaka · 2015 · Physical Review Letters
45. Computational Screening of Cathode Coatings for Solid-State Batteries
    Yihan Xiao, Lincoln J. Miara, Yan Eric Wang, Gerbrand Ceder · 2019 · Joule
46. Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements
    Takamoto, So, Shinagawa, Chikashi, Motoki, Daisuke, Nakago, Kosuke, Li, Wenwen, Kurata, Iori, Watanabe, Taku, Yayama, Yoshihiro, Iriguchi, Hiroki, Asano, Yusuke et al. · 2022 · Nature Communications
47. Machine learning for heterogeneous catalyst design and discovery
    Bryan R. Goldsmith, Jacques A. Esterhuizen, Jin‐Xun Liu, Christopher J. Bartel, Christopher A. Sutton · 2018 · AIChE Journal
48. Combining theory and experiment in lithium–sulfur batteries: Current progress and future perspectives
    Xiang Chen, Tingzheng Hou, Kristin Aslaug Persson, Qiang Zhang · 2018 · Materials Today
49. Holistic computational structure screening of more than 12 000 candidates for solid lithium-ion conductor materials
    Austin D. Sendek, Qian Yang, Ekin D. Cubuk, Karel-Alexander N. Duerloo, Yi Cui, Evan J. Reed · 2016 · Energy & Environmental Science
50. Bisalt ether electrolytes: a pathway towards lithium metal batteries with Ni-rich cathodes
    J. Alvarado, M. Schroeder, T. Pollard, Xuefeng Wang, J. Lee, Ming-Hao Zhang, T. Wynn, Michael S. Ding, O. Borodin, Y. Meng et al. · 2019 · Energy & Environmental Science
51. Design strategies for nonaqueous multivalent-ion and monovalent-ion battery anodes
    Matthew Li, Jun Lu, Xiulei Ji, Yan-Guang Li, Yuyan Shao, Zhong-Wei Chen, Cheng Zhong, K. Amine · 2020 · Nature Reviews Materials
52. Interpretable and Explainable Machine Learning for Materials Science and Chemistry
    Oviedo, Felipe, Ferres, Juan Lavista, Buonassisi, Tonio, Butler, Keith T. · 2022 · Accounts of Materials Research
53. SchNetPack: A Deep Learning Toolbox For Atomistic Systems
    Kristof T. Schütt, Pan Kessel, Michael Gastegger, Kim A. Nicoli, Alexandre Tkatchenko, K. Robert Müller · 2018 · Journal of Chemical Theory and Computation
54. Catalyst or Precatalyst? The Effect of Oxidation on Transition Metal Carbide, Pnictide, and Chalcogenide Oxygen Evolution Catalysts
    Bryan R. Wygant, Kenta Kawashima, Charles Buddie Mullins · 2018 · ACS Energy Letters
55. The Role of Machine Learning in the Understanding and Design of Materials
    Seyed Mohamad Moosavi, Kevin Maik Jablonka, Berend Smit · 2020 · Journal of the American Chemical Society
56. Electrochemical Synthesis of H2O2 by Two-Electron Water Oxidation Reaction
    Xinjian Shi, Seoin Back, Thomas Mark Gill · 2020 · Chem
57. Thermodynamic limit for synthesis of metastable inorganic materials
    Muratahan Aykol, Shyam Dwaraknath, Wenhao Q. Sun, Kristin Aslaug Persson · 2018 · Science Advances
58. A map of the inorganic ternary metal nitrides
    Wenhao Q. Sun, Christopher J. Bartel, Elisabetta Arca, Sage R. Bauers, Bethany E. Matthews, Bernardo Orvañanos, Bor‐Rong Chen, Michael F. Toney, Laura T. Schelhas, William Tumas et al. · 2019 · Nature Materials
59. Interpretable machine learning for knowledge generation in heterogeneous catalysis
    Jacques A. Esterhuizen, Bryan R. Goldsmith, Suljo Linic · 2022 · Nature Catalysis
60. Machine Learning for Electronically Excited States of Molecules
    Julia Westermayr, Philipp Marquetand · 2020 · Chemical Reviews
61. Nature of metal-support interaction for metal catalysts on oxide supports
    Tairan Wang, Jianyu Hu, Runhai Ouyang, Y. Wang, Yi Huang, Sulei Hu, Wei‐Xue Li · 2024 · Science
62. The AFLOW standard for high-throughput materials science calculations
    Camilo E. Calderón, José J. Plata, Cormac Toher, Corey Oses, Ohad Levy, Marco Fornari, Amir Natan, Michael J. Mehl, Gus L. W. Hart, Marco Buongiorno Nardelli et al. · 2015 · Computational Materials Science
63. A reflection on polymer electrolytes for solid-state lithium metal batteries
    Ziyu Song, Fangfang Chen, María Martínez‐Ibáñez · 2023 · Nature Communications
64. Wide Band Gap Chalcogenide Semiconductors.
    Rachel Woods‐Robinson, Yanbing Han, Hanyu Zhang · 2020 · eScholarship (California Digital Library)
65. Stabilizing Pt‐Based Electrocatalysts for Oxygen Reduction Reaction: Fundamental Understanding and Design Strategies
    Jiawei Zhang, Yuliang Yuan, Lei Gao, Gangming Zeng, Mengfan Li, Hongwen Huang · 2021 · Advanced Materials
66. Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries
    Chade Lv, Xin Zhou, Lixiang Zhong, Chunshuang Yan, Madhavi Srinivasan, Zhi Wei Seh, Chuntai Liu, Hongge Pan, Shuzhou Li, Yonggang Wen et al. · 2021 · Advanced Materials
67. P -type transparent conducting oxides
    Kelvin H. L. Zhang, Kai Xi, Mark G. Blamire · 2016 · Journal of Physics Condensed Matter
68. Accelerating the discovery of insensitive high-energy-density materials by a materials genome approach
    Yi Wang, Yuji Liu, Siwei Song, Zhijian Yang, Xiujuan Qi, Kangcai Wang, Yu Liu, Qinghua Zhang, Yong Tian · 2018 · Nature Communications
69. Size effects and active state formation of cobalt oxide nanoparticles during the oxygen evolution reaction
    Felix Thomas Haase, Arno Bergmann, Travis E. Jones, Janis Timoshenko, Antonia Herzog, Hyo Sang Jeon, Clara Rettenmaier, Beatriz Roldán Cuenya · 2022 · Nature Energy
70. Machine Learning Energies of 2 Million Elpasolite ( A B C 2 D 6 ) Crystals
    Felix A. Faber, Alexander Lindmaa, O. Anatole von Lilienfeld, Rickard Armiento · 2016 · Physical Review Letters
71. Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations
    Logan T. Ward, Ruoqian Liu, Amar Krishna, Vinay I. Hegde, Ankit Agrawal, Alok Choudhary, Chris M. Wolverton · 2017 · Physical review. B./Physical review. B
72. Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm
    Dunn, Alexander, Wang, Qi, Ganose, Alex, Dopp, Daniel, Jain, Anubhav · 2020 · npj Computational Materials
73. Thermochemical electronegativities of the elements
    Christian Tantardini, Артем Ромаевич Оганов · 2021 · Nature Communications
74. MAX phases – Past, present, and future
    Martin Dahlqvist, Michel W. Barsoum, Johanna Rosén · 2023 · Materials Today
75. Elastic Properties of Alkali Superionic Conductor Electrolytes from First Principles Calculations
    Zhi Deng, Zhenbin Wang, Iek‐Heng Chu, Jian Luo, Shyue Ping Ong · 2015 · Journal of The Electrochemical Society
76. The role of the solid electrolyte interphase layer in preventing Li dendrite growth in solid-state batteries
    Bingbin Wu, Shanyu Wang, Joshua Andrew Lochala, David Desrochers, Bo Liu, Wenqing Zhang, Jihui Yang, Jie Xiao · 2018 · Energy & Environmental Science
77. Predicting materials properties without crystal structure: deep representation learning from stoichiometry
    Rhys E. A. Goodall, Alpha A. Lee · 2020 · Nature Communications
78. Lithium–Sulfur Battery Cathode Design: Tailoring Metal‐Based Nanostructures for Robust Polysulfide Adsorption and Catalytic Conversion
    Sue‐Faye Ng, Michelle Yu Ling Lau, Wee‐Jun Ong · 2021 · Advanced Materials
79. Inverse design of nanoporous crystalline reticular materials with deep generative models
    Zhenpeng Yao, Benjamín Sánchez-Lengeling, N. Scott Bobbitt, Benjamin J. Bucior, Sai Govind Hari Kumar, Sean P. Collins, Thomas D. Burns, Tom K. Woo, Omar K. Farha, Randall Q. Snurr et al. · 2021 · Nature Machine Intelligence
80. Autonomous experimentation systems for materials development: A community perspective
    Eric A. Stach, Brian DeCost, Aaron Gilad Kusne, Jason R. Hattrick-Simpers, Keith A. Brown, Kristofer G. Reyes, Joshua Schrier, Simon J. L. Billinge, Tonio Buonassisi, Ian T Foster et al. · 2021 · Matter
81. Mesoscopic and multiscale modelling in materials
    Jacob Fish, Gregory J. Wagner, Sinan Keten · 2021 · Nature Materials
82. Materials Cloud, a platform for open computational science
    Leopold Talirz, Snehal Kumbhar, Elsa Passaro, Aliaksandr V. Yakutovich, Valeria Granata, Fernando Gargiulo, Marco Borelli, Martin Uhrin, Sebastiaan P. Huber, Spyros Zoupanos et al. · 2020 · Scientific Data
83. Computation-Accelerated Design of Materials and Interfaces for All-Solid-State Lithium-Ion Batteries
    Adelaide M. Nolan, Yizhou Zhu, Xingfeng He, Qiang Bai, Yifei Mo · 2018 · Joule
84. Mechanical properties and peculiarities of molecular crystals
    Wegood M. Awad, Daniel W. Davies, Daichi Kitagawa, Jad Mahmoud Halabi, Marieh B. Al‐Handawi, Ibrahim Tahir, Fei Tong, Gonzalo Campillo‐Alvarado, Alexander G. Shtukenberg, Tamador Alkhidir et al. · 2023 · Chemical Society Reviews
85. Electrochemical surface passivation of LiCoO2 particles at ultrahigh voltage and its applications in lithium-based batteries
    Jiawei Qian, Lei Liu, Jixiang Yang, Siyuan Li, Xiao Wang, Houlong L. Zhuang, Yingying Lü · 2018 · Nature Communications
86. Compatibility issues between electrodes and electrolytes in solid-state batteries
    Yaosen Tian, Tan Shi, William D. Richards, Juchuan Li, Jae Chul Kim, Shou‐Hang Bo, Gerbrand Ceder · 2017 · Energy & Environmental Science
87. Accelerated Discovery of Large Electrostrains in BaTiO3‐Based Piezoelectrics Using Active Learning
    Ruihao Yuan, Zhen Liu, Prasanna V. Balachandran, Deqing Xue, Yumei Zhou, Xiangdong Ding, Jun Sun, Dezhen Xue, Turab Lookman · 2018 · Advanced Materials
88. Predicting Materials Properties with Little Data Using Shotgun Transfer Learning
    Hironao YAMADA, Chang Liu, Stephen Wu, Yukinori Koyama, Shenghong Ju, Junichiro Shiomi, Junko Morikawa, Ryo Yoshida · 2019 · ACS Central Science
89. High-Performance Transition Metal Phosphide Alloy Catalyst for Oxygen Evolution Reaction
    Kewei Liu, Changlin Zhang, Yuandong Sun, Guanghui Zhang, Xiaochen Shen, Feng Yuan Zou, Haichang Zhang, Zhenwei Wu, Evan C. Wegener, Clinton J. Taubert et al. · 2017 · ACS Nano
90. Efficient generation of generalized Monkhorst-Pack grids through the use of informatics
    Pandu Wisesa, Kyle A. McGill, Tim Mueller · 2016 · Physical review. B./Physical review. B
91. Machine learning in concrete science: applications, challenges, and best practices
    Li, Zhanzhao, Yoon, Jinyoung, Zhang, Rui, Rajabipour, Farshad, Srubar III, Wil V., Dabo, Ismaila, Radlińska, Aleksandra · 2022 · npj Computational Materials
92. Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design
    Teng Zhou, Zhen Song, Kai Sundmacher · 2019 · Engineering
93. The materials genome in action: identifying the performance limits for methane storage
    Cory M. Simon, Jihan Kim, Diego A. Gómez‐Gualdrón, Jeffrey S. Camp, Yongchul G. Chung, Richard Luis Martin, Rocío Mercado, Michael W. Deem, Dan Gunter, Maciej Harańczyk et al. · 2015 · Energy & Environmental Science
94. Progress of Nonprecious‐Metal‐Based Electrocatalysts for Oxygen Evolution in Acidic Media
    Jiajian Gao, Hua Bing Tao, Bin Liu · 2021 · Advanced Materials
95. Inverse Design of Solid-State Materials via a Continuous Representation
    Juhwan Noh, Jaehoon Kim, Helge Sören Stein, Benjamín Sánchez-Lengeling, John M. Gregoire, Alán Aspuru‐Guzik, Yousung Jung · 2019 · Matter
96. Autonomy in materials research: a case study in carbon nanotube growth
    Pavel N. Nikolaev, Daylond J. Hooper, Frederick C. Webber, Rahul S. Rao, Kevin Decker, Michael P. Krein, Jason Poleski, Rick Barto, Benji Maruyama · 2016 · npj Computational Materials
97. 2DMatPedia, an open computational database of two-dimensional materials from top-down and bottom-up approaches
    Jun Zhou, Lei Shen, Miguel Dias Costa, Kristin Aslaug Persson, Shyue Ping Ong, Patrick Huck, Yunhao Lu, Xiaoyang Ma, Yiming Chen, Hanmei Tang et al. · 2019 · Scientific Data
98. The carrier transition from Li atoms to Li vacancies in solid-state lithium alloy anodes
    Yang Lu, Chen‐Zi Zhao, Rui Zhang, Hong Yuan, Li‐Peng Hou, Zhongheng Fu, Xiang Chen, Jia‐Qi Huang, Qiang Zhang · 2021 · Science Advances
99. Lithium Manganese Spinel Cathodes for Lithium‐Ion Batteries
    Yimeng Huang, Yanhao Dong, Sa Li, Jinhyuk Lee, Chao Wang, Zhi Hong Zhu, Weijiang Xue, Yao Li, Ju Li · 2020 · Advanced Energy Materials
100. Ultrathin ferroic HfO2–ZrO2 superlattice gate stack for advanced transistors
     Suraj Cheema, Nirmaan Shanker, Li‐Chen Wang et al. · 2022 · Nature