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RESEARCH PAPER · MRS Bulletin · 2023

Next-generation intelligent laboratories for materials design and manufacturing

Xiting Peng, Xiaonan Wang

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

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Next-generation intelligent laboratories for materials design and manufacturingOriginalWhat is missing in autonomous discovery: open challenges for the community44Towards self-driving labs for experimental mechanics: a data-centric approach for fatigue crack analysis in aerospace materials0Controlled mixing during colloidal quantum dot synthesis: A proxy-concept based on equivalent parameters1Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept3Closed-Loop Transfer Enables AI to Yield Chemical Knowledge6Knowledge graph representation of zeolitic crystalline materials17Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept93Transforming research laboratories with connected digital twins19Modeling the Properties of Sustainable Self-Compacting Concrete Containing Marble and Glass Powder Wastes Using Response Surface Methodology17Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries15How scanning probe microscopy can be supported by artificial intelligence and quantum computing?10Next generation fatigue crack growth experiments of aerospace materials9Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns10Closed-loop transfer enables artificial intelligence to yield chemical knowledge73Fully automated high-throughput computer-based catalytic material screening framework and its application on the new-generation Tianhe supercomputer2Machine‐Learning‐Enhanced Trial‐and‐Error for Efficient Optimization of Rubber Composites29A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research5AI foundational models in low-carbon energy and chemical engineering and the intelligent discovery platform for novel materials1Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning1Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning8Self-driving laboratories with artificial intelligence: An overview of process systems engineering perspective14Data Distribution Matters: Enhancing model generalization in Data-Driven Materials Discovery by intentionally exploiting both positive and negative data1Advancing atomic layer deposition through artificial intelligence: Generative modeling and predictive analytics for TiO2 growth rate prediction from TDMAT/O30Data-driven approaches for functional ceramics3DeepGear: Manufacturing Deep Learning-based Intelligent Equipment for Bacterial Cellulose Cultivation0

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  1. 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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  2. Towards self-driving labs for experimental mechanics: a data-centric approach for fatigue crack analysis in aerospace materials

    Research Square · 2023-07-12

    Tobias Strohmann, David Melching, Florian Paysan, Eric Dietrich, Guillermo Carlos Requena, Eric Breitbarth

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  3. Controlled mixing during colloidal quantum dot synthesis: A proxy-concept based on equivalent parameters

    Chemical Engineering Journal · 2023-08-14

    Ahmed M. Salaheldin, Doris Segets

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  4. 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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  5. Closed-Loop Transfer Enables AI to Yield Chemical Knowledge

    ChemRxiv · 2023-09-20

    Nicholas H. Angello, David Friday, Changhyun Hwang, Seungjoo Yi, Austin Cheng, Tiara Torres-Flores, Edward R. Jira, Wesley Wang, Alán Aspuru‐Guzik, Martin D. Burke, Charles M. Schroeder, Ying Diao, Nicholas E. Jackson

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  6. Knowledge graph representation of zeolitic crystalline materials

    Digital Discovery · 2024-01-01

    Aleksandar Kondinski, P. P. Rutkevych, Laura Pascazio, Dan N. Tran, Feroz Farazi, Srishti Ganguly, Markus Kraft

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  7. 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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  8. 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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  9. Modeling the Properties of Sustainable Self-Compacting Concrete Containing Marble and Glass Powder Wastes Using Response Surface Methodology

    Sustainability · 2024-02-27

    Youcef Aidjouli, Cherif Belebchouche, Abdelkader Hammoudi, El-Hadj Kadri, Said Zaouai, Sławomir Czarnecki

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  10. Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries

    Applied Physics Reviews · 2024-04-12

    Xiaozhao Liu, Volodymyr A. Koverga, Thi Thu Hoai Nguyen, Anh T. Ngo, Tao Li

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  11. How scanning probe microscopy can be supported by artificial intelligence and quantum computing?

    Microscopy Research and Technique · 2024-06-12

    Agnieszka Pręgowska, Agata Roszkiewicz, Magdalena E Osial, Michael Giersig

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  12. Next generation fatigue crack growth experiments of aerospace materials

    Scientific Reports · 2024-06-18

    Tobias Strohmann, David Melching, Florian Paysan, Eric Dietrich, Guillermo Carlos Requena, Eric Breitbarth

    Read original paper ↗ ·

  13. Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns

    IUCrJ · 2024-06-24

    Shouyang Zhang, Bin Cao, Tianhao Su, Yue Wu, Zhenjie Feng, Jie Xiong, Tong‐Yi Zhang

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  14. Closed-loop transfer enables artificial intelligence to yield chemical knowledge

    Nature · 2024-08-28

    Nicholas H. Angello, David Friday, Changhyun Hwang, Seungjoo Yi, Austin Cheng, Tiara Torres-Flores, Edward R. Jira, Wesley Wang, Alán Aspuru‐Guzik, Martin D. Burke, Charles M. Schroeder, Ying Diao, Nicholas E. Jackson

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  15. Fully automated high-throughput computer-based catalytic material screening framework and its application on the new-generation Tianhe supercomputer

    Computational Materials Science · 2025-02-23

    Can Leng, Xuguang Chen, Jie Liu, Chunye Gong, Bo Yang, Zhuo Tang, Wangdong Yang, Wei‐Qing Huang, Yi‐Ge Zhou, Mengxia Mo, Kenli Li, Keqin Li, Keqin Li, Keqin Li

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  16. Machine‐Learning‐Enhanced Trial‐and‐Error for Efficient Optimization of Rubber Composites

    Advanced Materials · 2025-03-10

    Wei Deng, Lijun Liu, Xiaohang Li, Yanyu Huang, Ming Hu, Yafang Zheng, Yuan Yin, Yan Huan, Shuxun Cui, Zhao‐Yan Sun, Jun Jiang, Xiaoniu Yang, Dapeng Wang

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  17. A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research

    Applied Sciences · 2025-05-07

    Lukas Nolte, Sven Tomforde

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  18. AI foundational models in low-carbon energy and chemical engineering and the intelligent discovery platform for novel materials

    Scientia Sinica Chimica · 2025-05-15

    Haoyu Yin, Yizhe Chen, Xiaonan Wang

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  19. Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning

    Angewandte Chemie · 2025-07-14

    Johann L. Rapp, Dylan M. Anstine, Filipp Gusev, Filipp Nikitin, Kelly H. Yun, Meredith A. Borden, Vittal Bhat, Olexandr Isayev, Frank A. Leibfarth

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  20. Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning

    Angewandte Chemie International Edition · 2025-07-14

    Johann L. Rapp, Dylan M. Anstine, Filipp Gusev, Filipp Nikitin, Kelly H. Yun, Meredith A. Borden, Vittal Bhat, Olexandr Isayev, Frank A. Leibfarth

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  21. 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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  22. Data Distribution Matters: Enhancing model generalization in Data-Driven Materials Discovery by intentionally exploiting both positive and negative data

    Acta Physico-Chimica Sinica · 2026-03-01

    Yiheng Wu, Lijun Liu, Wei Deng, Haodong Jiang, Ruotong Li, Ming Hu, Bo Peng, Dapeng Wang

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  23. Advancing atomic layer deposition through artificial intelligence: Generative modeling and predictive analytics for TiO2 growth rate prediction from TDMAT/O3

    Surface and Coatings Technology · 2026-03-04

    Remya Ampadi Ramachandran, Pouyan Navabi, Majid Jaberi‐Douraki, Urmila M. Diwekar, Cortino Sukotjo, Christos G. Takoudis

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  24. Data-driven approaches for functional ceramics

    Materials Science and Engineering R Reports · 2026-04-01

    Jincheng Qin, Faqiang Zhang, Mingsheng Ma, Yongxiang Li, Zhifu Liu

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  25. DeepGear: Manufacturing Deep Learning-based Intelligent Equipment for Bacterial Cellulose Cultivation

    Unknown journal · 2026-04-24

    Bo Xu

    Read original paper ↗ ·
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