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RESEARCH PAPER · Digital Discovery · 2025

Atlas: a brain for self-driving laboratories

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Atlas: a brain for self-driving laboratoriesOriginalMulti-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations41ExpFlow: a graphical user interface for automated reproducible electrochemistry10Accelerated chemical science with AI86Autonomous chemical research with large language models1012AlabOS: a Python-based reconfigurable workflow management framework for autonomous laboratories33An Affordable Platform for Automated Synthesis and Electrochemical Characterization1Race to the bottom: Bayesian optimisation for chemical problems76Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs75ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories103Self-Driving Laboratories for Chemistry and Materials Science674Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science19An affordable platform for automated synthesis and electrochemical characterization23Machine learning-guided strategies for reaction conditions design and optimization49A revolutionary paradigm in chemistry and materials science research: self-driving laboratories8Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation23Automating care by self-maintainability for full laboratory automation9BayBE: a Bayesian Back End for experimental planning in the low-to-no-data regime24Constrained composite Bayesian optimization for rational synthesis of polymeric particles6Contents list0Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry51Curiosity driven exploration to optimize structure–property learning in microscopy4Does one need to polish electrodes in an eight pattern? Automation provides the answer7Polymer microparticles in an evolving drug delivery landscape: challenges and the role of machine learning10El Agente: An autonomous agent for quantum chemistry54Self-driving laboratories with artificial intelligence: An overview of process systems engineering perspective14Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self‐Driving Lab14Bayesian Optimization for Chemical Synthesis in the Era of Artificial Intelligence: Advances and Applications19Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments10A Data-Driven Workflow for Nanomedicine Optimization Using Active Learning and Automated Experimentation18Pareto-Optimal Experimentation: Human-Guided Multi-Objective Bayesian Optimization in Scanning Probe Microscopy4Hierarchical optimization of perovskite solar cell fabrication via step-by-step machine learning3AI-driven electrocatalysis: reinforcement learning-based control and theoretical modeling of the glycerol oxidation reaction0Can we automate scientific reasoning in closed-loop experiments using large language models?4Closed-loop agentic AI in drug discovery1Closed-loop robotic manipulation of transparent substrates for self-driving laboratories using deep learning micro-error correction0Do Self-Driving Laboratories Accelerate Discovery or Automate Uncertainty, Bias, and Irreproducible Decisions?0Metallurgy-informed Bayesian optimization: rethinking alloy discovery and design0Toward self-driving laboratory 2.0 for chemistry and materials discovery15Transfer learning for reaction optimisation: overview of its applications and limits0Risk Mitigation Strategies for Artificial Intelligence-Enabled Self-Driving Laboratories0Exploring the limitations of kNN noisy feature detection and recovery for self-driving labs0Stepwise multi-target optimization of two-step deposition for wide-bandgap perovskite solar cells0Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories1Self-driving manufacturing labs: A conceptual framework and implementation case studies0Polymer informatics: Integrating data‐driven strategies, advanced machine learning, and automated synthesis for next‐generation polymer design2Foundation Model-Guided Optimization of Chemical Reaction Spaces for Autonomous Experimentation0Redefining synthetic efficiency: Chemical and technological shortcuts1Autonomous laboratories for sustainable nanomaterials discovery0Machine Learning for Synthetic Organic Chemistry: Methods, Applications, and Best Practices0

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  1. Multi-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations

    Digital Discovery · 2023-01-01

    Nickolas Gantzler, Aryan Deshwal, Janardhan Rao Doppa, Cory M. Simon

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  2. ExpFlow: a graphical user interface for automated reproducible electrochemistry

    Digital Discovery · 2023-12-05

    Rebekah Duke, Siamak Mahmoudi, Aman Preet Kaur, Vinayak Bhat, Ian C. Dingle, Nathan C. Stumme, Scott K. Shaw, D. L. Eaton, Asmund Vego, Chad M. Risko

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  3. Accelerated chemical science with AI

    Digital Discovery · 2023-12-06

    Seoin Back, Alán Aspuru‐Guzik, Michele Ceriotti, Ganna Gryn’ova, Bartosz A. Grzybowski, Geun Ho Gu, Jason E. Hein, Kedar Hippalgaonkar, Rodrigo Hormázabal, Yousung Jung, Seonah Kim, Woo Youn Kim, Seyed Mohamad Moosavi, Juhwan Noh, Chang-Young Park, Joshua Schrier, Philippe Schwaller, Koji Tsuda, Tejs Vegge, O. Anatole von Lilienfeld, Aron Walsh

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  4. Autonomous chemical research with large language models

    Nature · 2023-12-20

    Daniil A. Boiko, Robert MacKnight, Ben Kline, Gabe Gomes

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  5. AlabOS: a Python-based reconfigurable workflow management framework for autonomous laboratories

    Digital Discovery · 2024-01-01

    Yuxing Fei, Bernardus Rendy, Rishi E. Kumar, Olympia Dartsi, Hrushikesh P. Sahasrabuddhe, Matthew J. McDermott, Zheren Wang, Nathan J. Szymanski, Lauren N. Walters, David Milsted, Yan Zeng, Anubhav Jain, Gerbrand Ceder

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  6. An Affordable Platform for Automated Synthesis and Electrochemical Characterization

    SSRN Electronic Journal · 2024-01-01

    Sergio Pablo‐García, A. Garcı́a, Gun Deniz Akkoc, Malcolm Sim, Yang Cao, Maxine Somers, Chance Hattrick, Naruki Yoshikawa, Dominik Dworschak, Han Hao, Alán Aspuru‐Guzik

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  7. Race to the bottom: Bayesian optimisation for chemical problems

    Digital Discovery · 2024-01-01

    Yifan Wu, Aron Walsh, Alex M. Ganose

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  8. Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs

    npj Computational Materials · 2024-05-13

    Andre K. Y. Low, Flore Mekki‐Berrada, Abhishek Gupta, Aleksandr Ostudin, Jiaxun Xie, Eléonore Vissol-Gaudin, Yee‐Fun Lim, Qianxiao Li, Yew-Soon Ong, Saif A. Khan, Kedar Hippalgaonkar

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  9. ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories

    Matter · 2024-05-14

    Malcolm Sim, Mohammad Ghazi Vakili, Felix Strieth‐Kalthoff, Han Hao, Riley J. Hickman, Santiago Miret, Sergio Pablo‐García, Alán Aspuru‐Guzik

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  10. Self-Driving Laboratories for Chemistry and Materials Science

    Chemical Reviews · 2024-08-13

    Gary Tom, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo‐García, Ella Miray Rajaonson, Marta Skreta, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc, Felix Strieth‐Kalthoff, Martin T. Seifrid, Alán Aspuru‐Guzik

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  11. Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science

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    Austin Cheng, Cher Tian Ser, Marta Skreta, Andrés Guzmán-Cordero, Luca Thiede, Andreas Burger, Abdulrahman Aldossary, Shi Xuan Leong, Sergio Pablo‐García, Felix Strieth‐Kalthoff, Alán Aspuru‐Guzik

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  12. An affordable platform for automated synthesis and electrochemical characterization

    Device · 2024-10-03

    Sergio Pablo‐García, A. Garcı́a, Gun Deniz Akkoc, Malcolm Sim, Yang Cao, Maxine Somers, Chance Hattrick, Naruki Yoshikawa, Dominik Dworschak, Han Hao, Alán Aspuru‐Guzik

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  13. Machine learning-guided strategies for reaction conditions design and optimization

    Beilstein Journal of Organic Chemistry · 2024-10-04

    Lung-Yi Chen, Yi‐Pei Li

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  14. A revolutionary paradigm in chemistry and materials science research: self-driving laboratories

    Chemical Communications · 2025-01-01

    Jiaxuan Qiu, Liwen Zhu, Zhe Feng, Zhongzhong Luo, Longlu Wang

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  15. Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation

    Digital Discovery · 2025-01-01

    Riley J. Hickman, Gary Tom, Yunheng Zou, Matteo Aldeghi, Alán Aspuru‐Guzik

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  16. Automating care by self-maintainability for full laboratory automation

    Digital Discovery · 2025-01-01

    Koji Ochiai, Yuya Tahara-Arai, Akari Kato, Kazunari Kaizu, Hirokazu Kariyazaki, Makoto Umeno, Koichi Takahashi, Genki N. Kanda, Haruka Ozaki

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  17. BayBE: a Bayesian Back End for experimental planning in the low-to-no-data regime

    Digital Discovery · 2025-01-01

    Martin Fitzner, Adrian Šošić, Alexander Vincent Hopp, Marcel Müller, Rim Rihana, Karin Hrovatin, Fabian Liebig, Mathias Winkel, Wolfgang Halter, Jan Gerit Brandenburg

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  18. Constrained composite Bayesian optimization for rational synthesis of polymeric particles

    Digital Discovery · 2025-01-01

    Fanjin Wang, Maryam Parhizkar, Anthony Henry Harker, Mohan J. Edirisinghe

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  19. Contents list

    Digital Discovery · 2025-01-01

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  20. Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry

    Chemical Society Reviews · 2025-01-01

    Austin M. Mroz, Annabel R. Basford, Friedrich Hastedt, Isuru Shavindra Jayasekera, Irea Mosquera‐Lois, Ruby Sedgwick, Pedro J. Ballester, Joshua D. Bocarsly, Ehecatl Antonio del Rio‐Chanona, Matthew L. Evans, Jarvist Moore Frost, Alex M. Ganose, Rebecca L. Greenaway, King Kuok Hii, Yingzhen Li, Ruth Misener, Aron Walsh, Dandan Zhang, Kim E. Jelfs

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  21. Curiosity driven exploration to optimize structure–property learning in microscopy

    Digital Discovery · 2025-01-01

    Aditya Vatsavai, Ganesh Narasimha, Yongtao Liu, Jawad Chowdhury, Jan‐Chi Yang, Hiroshi Funakubo, Maxim A Ziatdinov, Rama Krishnan Vasudevan

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  22. Does one need to polish electrodes in an eight pattern? Automation provides the answer

    Digital Discovery · 2025-01-01

    Naruki Yoshikawa, Gun Deniz Akkoc, Sergio Pablo‐García, Yang Cao, Han Hao, Alán Aspuru‐Guzik

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  23. Polymer microparticles in an evolving drug delivery landscape: challenges and the role of machine learning

    International Journal of Pharmaceutics · 2025-06-25

    Zeqing Bao, Jongwhi Kim, Frantz Le Dévédec, Aaron J. Clasky, Christine J. Allen

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  24. El Agente: An autonomous agent for quantum chemistry

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    Yushi Zou, Austin Cheng, Abdulrahman Aldossary, Jiaru Bai, Shi Xuan Leong, Jorge A. Campos-Gonzalez-Angulo, Changhyeok Choi, Cher Tian Ser, Gary Tom, Andrew Wang, Zijian Zhang, Ilya Yakavets, Hao Han, Chris Crebolder, Varinia Bernales, Alán Aspuru‐Guzik

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  25. Self-driving laboratories with artificial intelligence: An overview of process systems engineering perspective

    Computers & Chemical Engineering · 2025-07-26

    You-Hyun Kim, Hayoung Doo, Daeun Shin, Seo Yoon Lee, Seo Yoon Lee, Yugyeong Roh, Seong‐Eun Park, Heejin Song, Yujin Jung, Hyuk Jun Yoo, Sang Soo Han, Jong Woo Kim, Maximilian O. Besenhard, Ye Seol Lee, Jonggeol Na

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  26. Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self‐Driving Lab

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  27. Bayesian Optimization for Chemical Synthesis in the Era of Artificial Intelligence: Advances and Applications

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  28. Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

    ACS Nanoscience Au · 2025-10-14

    Ralph Bulanadi, Jawad Chowdhury, Hiroshi Funakubo, Maxim A Ziatdinov, Rama Krishnan Vasudevan, Arpan Biswas, Yongtao Liu

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  29. A Data-Driven Workflow for Nanomedicine Optimization Using Active Learning and Automated Experimentation

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  30. Pareto-Optimal Experimentation: Human-Guided Multi-Objective Bayesian Optimization in Scanning Probe Microscopy

    Nano Letters · 2025-12-23

    Yu Liu, Sergei V. Kalinin

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  31. Hierarchical optimization of perovskite solar cell fabrication via step-by-step machine learning

    Cell Reports Physical Science · 2025-12-31

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  32. AI-driven electrocatalysis: reinforcement learning-based control and theoretical modeling of the glycerol oxidation reaction

    Energy & Environmental Science · 2026-01-01

    Vladislav A. Mints, Maria‐Magdalena Titirici, Ifan E. L. Stephens

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  33. Can we automate scientific reasoning in closed-loop experiments using large language models?

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    A. Cisse, Max Cooper, Mengjia Zhu, Xenophon Evangelopoulos, Andrew Ian Cooper

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  34. Closed-loop agentic AI in drug discovery

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  35. Closed-loop robotic manipulation of transparent substrates for self-driving laboratories using deep learning micro-error correction

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    Kelsey Fontenot, Anjali Gorti, Iva Goel, Tonio Buonassisi, Alexander E. Siemenn

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  36. Do Self-Driving Laboratories Accelerate Discovery or Automate Uncertainty, Bias, and Irreproducible Decisions?

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  37. Metallurgy-informed Bayesian optimization: rethinking alloy discovery and design

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  38. Toward self-driving laboratory 2.0 for chemistry and materials discovery

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  39. Transfer learning for reaction optimisation: overview of its applications and limits

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  40. Risk Mitigation Strategies for Artificial Intelligence-Enabled Self-Driving Laboratories

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  41. Exploring the limitations of kNN noisy feature detection and recovery for self-driving labs

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  42. Stepwise multi-target optimization of two-step deposition for wide-bandgap perovskite solar cells

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  43. Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

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  44. Self-driving manufacturing labs: A conceptual framework and implementation case studies

    Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2026-05-04

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  45. Polymer informatics: Integrating data‐driven strategies, advanced machine learning, and automated synthesis for next‐generation polymer design

    InfoScience. · 2026-05-24

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  46. Foundation Model-Guided Optimization of Chemical Reaction Spaces for Autonomous Experimentation

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  47. Redefining synthetic efficiency: Chemical and technological shortcuts

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  48. Autonomous laboratories for sustainable nanomaterials discovery

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  49. Machine Learning for Synthetic Organic Chemistry: Methods, Applications, and Best Practices

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