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RESEARCH PAPER · Nature Computational Science · 2023

The promise and pitfalls of AI for molecular and materials synthesis

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22 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

The promise and pitfalls of AI for molecular and materials synthesisOriginalIntelligent Biomaterialomics: Molecular Design, Manufacturing, and Biomedical Applications51Data-Driven Imputation of Miscibility of Aqueous Solutions via Graph-Regularized Logistic Matrix Factorization6“You’ve got the Body I’ve got the Brains” – Could the current AI-based tools replace the human ingenuity for designing new drug candidates?3Bayesian optimisation for additive screening and yield improvements – beyond one-hot encoding28Should We Teach AI a Better Scientific Method?5Synthesis strategies and cancer therapy applications of PEDOT nanoparticles13Hacking decarbonization with a community-operated CreatorSpace8Optimal thermodynamic conditions to minimize kinetic by-products in aqueous materials synthesis26Transforming research laboratories with connected digital twins19The increasing potential and challenges of digital twins28Navigating phase diagram complexity to guide robotic inorganic materials synthesis82Music generation using hybrid deep neural model0Conductive Core–Shell Nanoparticles: Synthesis and Applications64Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions15A critical reflection on attempts to machine-learn materials synthesis insights from text-mined literature recipes16Human-Guided Metaverse Synthesis for Quantum Dots: Advancing Nanomaterial Research through Augmented Artificial Intelligence2How to accelerate the inorganic materials synthesis: from computational guidelines to data-driven method?9Artificial Intelligence (AI) for More Sustainable Chemistry and a Greener Future8A roadmap toward closed-loop autonomous experimentation for engineered nanomaterials3Data-Driven Synthesis of Covalent Organic Frameworks via Machine Learning with Integrated Success–Failure Data4Accelerating Perovskite Solar Cell Development Through High‐Throughput Technologies: Computational Simulation, Automated Experimentation, and Intelligent Integration0The disorazole family of potent anticancer agents: structures, bioactivity, total synthesis, and heterologous biosynthesis0

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22 direct citing papers saved.

  1. Intelligent Biomaterialomics: Molecular Design, Manufacturing, and Biomedical Applications

    Advanced Materials · 2023-07-25

    Yu Yi, Hong‐Wei An, Hao Wang

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  2. Data-Driven Imputation of Miscibility of Aqueous Solutions via Graph-Regularized Logistic Matrix Factorization

    The Journal of Physical Chemistry B · 2023-09-08

    Diba Behnoudfar, Cory M. Simon, Joshua Schrier

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  3. “You’ve got the Body I’ve got the Brains” – Could the current AI-based tools replace the human ingenuity for designing new drug candidates?

    Bioorganic & Medicinal Chemistry · 2023-09-13

    Edeildo Ferreira da Silva‐Júnior

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  4. Bayesian optimisation for additive screening and yield improvements – beyond one-hot encoding

    Digital Discovery · 2023-11-02

    Bojana Ranković, Ryan‐Rhys Griffiths, Henry B. Moss, Philippe Schwaller

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  5. Should We Teach AI a Better Scientific Method?

    Chemistry of Materials · 2023-12-26

    James Richmond Neilson

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  6. Synthesis strategies and cancer therapy applications of PEDOT nanoparticles

    Materials Advances · 2024-01-01

    Diogo Dias, Leonor Resina, Frederico Castelo Ferreira, Paola Sanjuan‐Alberte, Teresa Esteves

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  7. Hacking decarbonization with a community-operated CreatorSpace

    Chem · 2024-01-26

    Aleksandar Kondinski, Sebastian Mosbach, Jethro Akroyd, Andrew C. Breeson, Yong Ren Tan, Simon D. Rihm, Jiaru Bai, Markus Kraft

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  8. Optimal thermodynamic conditions to minimize kinetic by-products in aqueous materials synthesis

    Nature Synthesis · 2024-01-30

    Zheren Wang, Yingzhi Sun, Kevin Cruse, Yan Zeng, Yuxing Fei, Zexuan Liu, Junyi Shangguan, Young‐Woon Byeon, KyuJung Jun, Tanjin He, Wenhao Q. Sun, Gerbrand Ceder

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  9. Transforming research laboratories with connected digital twins

    Nexus · 2024-02-05

    Simon D. Rihm, Jiaru Bai, Aleksandar Kondinski, Sebastian Mosbach, Jethro Akroyd, Markus Kraft

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  10. The increasing potential and challenges of digital twins

    Nature Computational Science · 2024-03-26

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  11. Navigating phase diagram complexity to guide robotic inorganic materials synthesis

    Nature Synthesis · 2024-04-09

    Jiadong Chen, Samuel R. Cross, Lincoln J. Miara, Jeong‐Ju Cho, Yan Eric Wang, Wenhao Q. Sun

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  12. Music generation using hybrid deep neural model

    Unknown journal · 2024-05-04

    Rajnish Kumar Chaturvedi, Nitin Arvind Shelke

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  13. Conductive Core–Shell Nanoparticles: Synthesis and Applications

    The Journal of Physical Chemistry C · 2024-07-01

    Catarina Franco Jones, Leonor Resina, Frederico Castelo Ferreira, Paola Sanjuan‐Alberte, Teresa Esteves

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  14. Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions

    Chemistry - A European Journal · 2024-07-31

    Han Yu, Mingjing Deng, Ke Liu, Jia Chen, Yuting Wang, Yongsong Xu, Longyang Dian

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  15. A critical reflection on attempts to machine-learn materials synthesis insights from text-mined literature recipes

    Faraday Discussions · 2024-08-13

    Wenhao Q. Sun, Nicholas David

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  16. Human-Guided Metaverse Synthesis for Quantum Dots: Advancing Nanomaterial Research through Augmented Artificial Intelligence

    ACS Applied Materials & Interfaces · 2024-08-13

    Yao Xu, Yuechen Gao, Min Wang, Xi Zhu

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  17. How to accelerate the inorganic materials synthesis: from computational guidelines to data-driven method?

    National Science Review · 2025-02-27

    Yilei Wu, Xiangyang Li, Rong Guo, Rui Xu, Ming‐Gang Ju, Jinlan Wang

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  18. Artificial Intelligence (AI) for More Sustainable Chemistry and a Greener Future

    ACS Sustainable Chemistry & Engineering · 2025-03-07

    Mehran Ghasemlou, Hoang Chinh Nguyen, Sachin Talekar, Frederick Matthew Pfeffer, Colin James Barrow

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  19. A roadmap toward closed-loop autonomous experimentation for engineered nanomaterials

    Nature Chemical Engineering · 2025-10-17

    Nicholas A. Jose, Alexei A. Lapkin

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  20. Data-Driven Synthesis of Covalent Organic Frameworks via Machine Learning with Integrated Success–Failure Data

    JACS Au · 2026-05-20

    Bing Ma, Qianqian Yan, Wei Zhou, Junhao Wu, Lipiao Bao, Xinhui Lu, Xinhui Lu, Jixia Qiu, Yuanyuan Zhu, Xiao Wang, Dong Zhai, Chengcheng Liu, S W Zhang, Wei Deng, Xing Lu, Xing Lu

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  21. Accelerating Perovskite Solar Cell Development Through High‐Throughput Technologies: Computational Simulation, Automated Experimentation, and Intelligent Integration

    Battery energy · 2026-05-28

    Yiming Wang, Ziwei Du, Yuehua Chen, Yicheng Qiu, Dong Yan, Bo Hou

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  22. The disorazole family of potent anticancer agents: structures, bioactivity, total synthesis, and heterologous biosynthesis

    Journal of Advanced Research · 2026-07-01

    Guoan Fu, He Li, Ruijuan Li, Qiang Tu, Piwu Li, Youming Zhang

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