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RESEARCH PAPER · Matter · 2022

An object-oriented framework to enable workflow evolution across materials acceleration platforms

Chang Jie Leong, Andre K. Y. Low, Jose Recatala‐Gomez, Pablo Quijano Velasco, Eléonore Vissol-Gaudin, Jin Da Tan, Balamurugan Ramalingam, Riko I Made, Shreyas Dinesh Pethe, Saumya Sebastian, Yee‐Fun Lim, Zi Hui Jonathan Khoo, Yang Bai, Jayce Jian Wei Cheng, Kedar Hippalgaonkar

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

Open in your workspace →Saved 2026-10-14 · complete coverage
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42 direct citing works

An object-oriented framework to enable workflow evolution across materials acceleration platformsOriginalOrchestrating nimble experiments across interconnected labs37The laboratory of Babel: highlighting community needs for integrated materials data management20What is missing in autonomous discovery: open challenges for the community44Globus automation services: Research process automation across the space–time continuum38Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept3pHbot: Self‐Driven Robot for pH Adjustment of Viscous Formulations via Physics‐informed‐ML**12Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept93Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs75ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories103Illustrating an Effective Workflow for Accelerated Materials Discovery14Structural Evolution of Millisecond Laser-Induced Metastable Crystalline GeTe0Self-Driving Laboratories for Chemistry and Materials Science674Reproducibility in automated chemistry laboratories using computer science abstractions28OCTOPUS: operation control system for task optimization and job parallelization via a user-optimal scheduler12Embodied Artificial Intelligence Must Learn Laboratory Constraints before It Can Autonomously Conduct Pharmaceutical Experiments0Advancing perovskite photovoltaic technology through machine learning‐driven automation49Self-Driving Laboratories: Translating Materials Science from Laboratory to Factory9Uncertainty-aware multi-source modeling for materials property prediction: A case study in ferroelectrics0Synthesis-structure-performance relationships in hydrothermally derived α-Fe2O3 photoanodes for photoelectrochemical water splitting: A critical review0

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20 direct citing papers saved.

  1. Orchestrating nimble experiments across interconnected labs

    Digital Discovery · 2023-01-01

    Dan Guevarra, Kevin Kan, Yungchieh Lai, Ryan J. R. Jones, Lan Zhou, Phillip Donnelly, Matthias Hermann Richter, Helge Sören Stein, John M. Gregoire

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  2. The laboratory of Babel: highlighting community needs for integrated materials data management

    Digital Discovery · 2023-01-01

    Brenden Galen Pelkie, Lilo D. Pozzo

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  3. What is missing in autonomous discovery: open challenges for the community

    Digital Discovery · 2023-01-01

    Phillip M. Maffettone, Pascal Friederich, Sterling G. Baird, Ben J. Blaiszik, Keith A. Brown, Stuart I. Campbell, Orion Cohen, Rebecca L. Davis, Ian T Foster, Navid Haghmoradi, Mark Hereld, Howie Joress, Nicole Jung, Ha-Kyung Kwon, Gabriella Pizzuto, Jacob Rintamaki, Casper Steinmann, Luca Torresi, Shijing Sun

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  4. Globus automation services: Research process automation across the space–time continuum

    Future Generation Computer Systems · 2023-01-18

    Ryan Chard, Jim Pruyne, Kurt Mckee, Josh Bryan, Brigitte E. Raumann, Rachana Ananthakrishnan, Kyle Chard, Ian T Foster

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  5. Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics

    Nature Reviews Materials · 2023-01-24

    Kedar Hippalgaonkar, Qianxiao Li, Xiaonan Wang, John Sheridan Fisher, James Kirkpatrick, Tonio Buonassisi

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  6. Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept

    ChemRxiv · 2023-09-07

    Stanley Lo, Sterling G. Baird, Joshua Schrier, Ben J. Blaiszik, Sergei V. Kalinin, Helen Tran, Taylor D. Sparks, Alán Aspuru‐Guzik

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  7. pHbot: Self‐Driven Robot for pH Adjustment of Viscous Formulations via Physics‐informed‐ML**

    Chemistry - Methods · 2023-12-13

    Aniket Chitre, Jayce Jian Wei Cheng, Sarfaraz Ahamed, Robert C. M. Querimit, Benchuan Zhu, Ke Wang, Long Wang, Kedar Hippalgaonkar, Alexei A. Lapkin

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  8. Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept

    Digital Discovery · 2024-01-01

    Stanley Lo, Sterling G. Baird, Joshua Schrier, Ben J. Blaiszik, Nessa Carson, Ian T Foster, Andrés Aguilar‐Granda, Sergei V. Kalinin, Benji Maruyama, Maria Politi, Helen Tran, Taylor D. Sparks, Alán Aspuru‐Guzik

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  9. 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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  10. 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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  11. Illustrating an Effective Workflow for Accelerated Materials Discovery

    Integrating materials and manufacturing innovation · 2024-06-01

    Mrinalini Mulukutla, A. Nicole Person, Sven Voigt, Lindsey A. Kuettner, Branden B. Kappes, Danial Khatamsaz, Robert Robinson, Daniel Salas, Wenle Xu, Daniel Lewis, Hongkyu Eoh, Kailu Xiao, Haoren Wang, Jaskaran Singh Saini, Raj Mahat, Trevor Hastings, Matthew Skokan, Vahid Attari, Michael Elverud, James D. Paramore, Brady G. Butler, Kenneth S. Vecchio, Surya R. Kalidindi, Douglas Allaire, İbrahim Karaman, Edwin L. Thomas, George M. Pharr, Ankit Srivastava, Raymundo Arróyave

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  12. Structural Evolution of Millisecond Laser-Induced Metastable Crystalline GeTe

    ACS Applied Electronic Materials · 2024-07-11

    Jose Recatala‐Gomez, Yun Li, Nur Qalishah Adanan, Biplab Ghosh, Haiwen Dai, Yang Bai, Chenguang Zhang, Samuel A. Morris, Zhong‐Shan Jin, Wenhao Zhai, Tobias W. W. Maß, Pawan Kumar, Fengxia Wei, Maung Thway, Rafikul Ali Saha, Eduardo Solano, Martin Rosenthal, Maarten B. J. Roeffaers, Nigel M. Kirby, Izabela Miłogrodzka, Robert Edward Simpson, Kwan Wee Tan, Kedar Hippalgaonkar

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  13. 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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  14. Reproducibility in automated chemistry laboratories using computer science abstractions

    Nature Synthesis · 2024-10-10

    Richard B. Canty, Milad Abolhasani

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  15. OCTOPUS: operation control system for task optimization and job parallelization via a user-optimal scheduler

    Nature Communications · 2024-11-08

    Hyuk Jun Yoo, Kwan‐Young Lee, Dong-Hun Kim, Sang Soo Han

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  16. Embodied Artificial Intelligence Must Learn Laboratory Constraints before It Can Autonomously Conduct Pharmaceutical Experiments

    Pharmacophore · 2025-01-01

    Marco De Luca, Giulia Ferraro, Antonio Russo, Elena Rossi

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  17. Advancing perovskite photovoltaic technology through machine learning‐driven automation

    InfoMat · 2025-02-24

    Jiyun Zhang, Jianchang Wu, Vincent Marc Le Corre, Jens Hauch, Yicheng Zhao, Christoph Josef Brabec

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  18. Self-Driving Laboratories: Translating Materials Science from Laboratory to Factory

    ACS Omega · 2025-06-03

    Andre K. Y. Low, Jayce Jian Wei Cheng, Kedar Hippalgaonkar, Leonard W. T. Ng

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  19. Uncertainty-aware multi-source modeling for materials property prediction: A case study in ferroelectrics

    Physical Review Materials · 2026-07-29

    Bo Wang, Yuehui Xian, Yumei Zhou, Dezhen Xue, Yangyang Xu

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  20. Synthesis-structure-performance relationships in hydrothermally derived α-Fe2O3 photoanodes for photoelectrochemical water splitting: A critical review

    Materials chemistry and physics. · 2026-08-05

    Zhan Li, Noraini Mohd

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