Planning chemical syntheses with deep neural networks and symbolic AI
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DOI: 10.1038/nature25978
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- Hang Xiao & Rong Li & Xiaoyang Shi & Yan Chen & Liangliang Zhu & Xi Chen & Lei Wang, 2023. "An invertible, invariant crystal representation for inverse design of solid-state materials using generative deep learning," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
- Yuanyuan Jiang & Zongwei Yang & Jiali Guo & Hongzhen Li & Yijing Liu & Yanzhi Guo & Menglong Li & Xuemei Pu, 2021. "Coupling complementary strategy to flexible graph neural network for quick discovery of coformer in diverse co-crystal materials," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
- Nathan J. Szymanski & Pragnay Nevatia & Christopher J. Bartel & Yan Zeng & Gerbrand Ceder, 2023. "Autonomous and dynamic precursor selection for solid-state materials synthesis," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
- Shuangjia Zheng & Tao Zeng & Chengtao Li & Binghong Chen & Connor W. Coley & Yuedong Yang & Ruibo Wu, 2022. "Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
- de Mars, Patrick & O’Sullivan, Aidan, 2021. "Applying reinforcement learning and tree search to the unit commitment problem," Applied Energy, Elsevier, vol. 302(C).
- Debesh Mishra & Biswajit Mohapatra & Abhaya Sanatan Satpathy & Kamalakanta Muduli & Binayak Mishra & Swagatika Mishra & Upma Paliwal, 2024. "The pandemic COVID-19 and associated challenges with implementation of artificial intelligence (AI) in Indian agriculture," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2715-2729, June.
- Marcel Rolf Pfeifer, 2021. "Development of a Smart Manufacturing Execution System Architecture for SMEs: A Czech Case Study," Sustainability, MDPI, vol. 13(18), pages 1-23, September.
- Fernando Martinez-Plumed & Emilia Gomez Gutierrez & Jose Hernandez-Orallo, 2020. "AI Watch Assessing Technology Readiness Levels for Artificial Intelligence," JRC Research Reports JRC122014, Joint Research Centre.
- Naudé, Wim, 2020. "Artificial Intelligence against COVID-19: An Early Review," IZA Discussion Papers 13110, Institute of Labor Economics (IZA).
- Yu Wang & Chao Pang & Yuzhe Wang & Junru Jin & Jingjie Zhang & Xiangxiang Zeng & Ran Su & Quan Zou & Leyi Wei, 2023. "Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
- Weihe Zhong & Ziduo Yang & Calvin Yu-Chian Chen, 2023. "Retrosynthesis prediction using an end-to-end graph generative architecture for molecular graph editing," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
- Umit V. Ucak & Islambek Ashyrmamatov & Junsu Ko & Juyong Lee, 2022. "Retrosynthetic reaction pathway prediction through neural machine translation of atomic environments," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
- Debesh Mishra & Kamalakanta Muduli & Rakesh Raut & Balkrishna Eknath Narkhede & Himanshu Shee & Sujoy Kumar Jana, 2023. "Challenges Facing Artificial Intelligence Adoption during COVID-19 Pandemic: An Investigation into the Agriculture and Agri-Food Supply Chain in India," Sustainability, MDPI, vol. 15(8), pages 1-25, April.
- Yuqiang Han & Xiaoyang Xu & Chang-Yu Hsieh & Keyan Ding & Hongxia Xu & Renjun Xu & Tingjun Hou & Qiang Zhang & Huajun Chen, 2024. "Retrosynthesis prediction with an iterative string editing model," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
- Itai Levin & Mengjie Liu & Christopher A. Voigt & Connor W. Coley, 2022. "Merging enzymatic and synthetic chemistry with computational synthesis planning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
- M. Saqlain & S. Ali & J. Y. Lee, 2023. "A Monte-Carlo tree search algorithm for the flexible job-shop scheduling in manufacturing systems," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 548-571, June.
- Mochen Liao & Kai Lan & Yuan Yao, 2022. "Sustainability implications of artificial intelligence in the chemical industry: A conceptual framework," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 164-182, February.
- Zhao, Jingyuan & Feng, Xuning & Wang, Junbin & Lian, Yubo & Ouyang, Minggao & Burke, Andrew F., 2023. "Battery fault diagnosis and failure prognosis for electric vehicles using spatio-temporal transformer networks," Applied Energy, Elsevier, vol. 352(C).
- Wenhao Gao & Priyanka Raghavan & Connor W. Coley, 2022. "Autonomous platforms for data-driven organic synthesis," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
- Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
- Shingo Harada & Hiroki Takenaka & Tsubasa Ito & Haruki Kanda & Tetsuhiro Nemoto, 2024. "Valence-isomer selective cycloaddition reaction of cycloheptatrienes-norcaradienes," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
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