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RESEARCH PAPER · Digital Discovery · 2023

The materials experiment knowledge graph

Michael J. Statt, Brian A. Rohr, Dan Guevarra, Ja'Nya Breeden, Santosh K. Suram, John M. Gregoire

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42 direct citing works

The materials experiment knowledge graphOriginalAutonomous laboratories for accelerated materials discovery: a community survey and practical insights33Chemistry in a graph: modern insights into commercial organic synthesis planning2Knowledge graph representation of zeolitic crystalline materials17Knowledge Graphs for Materials Discovery: Data Structuring, Reasoning, and Applications0A dynamic knowledge graph approach to distributed self-driving laboratories108MatKG: An autonomously generated knowledge graph in Material Science86Designing workflows for materials characterization22A materials terminology knowledge graph automatically constructed from text corpus21Autonomous Laboratories and Closed-Loop Materials Discovery: A Conceptual Framework for Self-Driving Experimentation0Large language models for knowledge graph extraction from tables in materials science12KupferDigital: Ontology‐Based Digital Representation for the Copper Life Cycle2The Prediction of Tensile Strength Performance of Fiber‐Reinforced Composites Based on a Knowledge Graph Constructed From Material Literature4Constructing material network representations for intelligent amorphous alloy design3Designing a unified data structure for solid-electrolyte research projects0Chat-RFB: a flow battery chat system leveraging knowledge graphs and large language models2Combinatorial to autonomous experimentation0Sustaining the growth of the materials informatics ecosystem0Agentic Knowledge Graphs of the LiFePO 4 Cathode for Lithium Ion Battery: Balancing Discovery and Stability with LLMs0Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science0From Data to Discovery: Challenges and Solutions in AI-Driven Materials Science0A survey of agentic materials science and engineering: where are we and where are we going?0Materials by machines: A review on intuition and knowledge-driven learning for rapid discovery and optimization0AI for Accelerated Materials Discovery: From Generative Design to Autonomous Realization2AI agents for MOFs and COFs discovery0Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data0

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  1. Autonomous laboratories for accelerated materials discovery: a community survey and practical insights

    Digital Discovery · 2024-01-01

    Linda Hung, Joyce A. Yager, Danielle R. Monteverde, Dave Baiocchi, Ha-Kyung Kwon, Shijing Sun, Santosh K. Suram

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  2. Chemistry in a graph: modern insights into commercial organic synthesis planning

    Digital Discovery · 2024-01-01

    Claudio Avila, Adam West, Anna Chiara Vicini, William Waddington, Christopher J. Brearley, James Clarke, Andrew M. Derrick

    Read original paper ↗ ·

  3. 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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  4. Knowledge Graphs for Materials Discovery: Data Structuring, Reasoning, and Applications

    Journal of Computational and Data-Driven Materials Engineering · 2024-01-01

    Maria Hernandez, Carlos Vega

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  5. A dynamic knowledge graph approach to distributed self-driving laboratories

    Nature Communications · 2024-01-23

    Jiaru Bai, Sebastian Mosbach, Connor J. Taylor, Dogancan Karan, Kok Foong Lee, Simon D. Rihm, Jethro Akroyd, Alexei A. Lapkin, Markus Kraft

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  6. MatKG: An autonomously generated knowledge graph in Material Science

    Scientific Data · 2024-02-17

    Vineeth Venugopal, Elsa Olivetti

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  7. Designing workflows for materials characterization

    Applied Physics Reviews · 2024-03-01

    Sergei V. Kalinin, Maxim A Ziatdinov, Mahshid Ahmadi, Ayana Ghosh, Kevin M. Roccapriore, Yongtao Liu, Rama Krishnan Vasudevan

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  8. A materials terminology knowledge graph automatically constructed from text corpus

    Scientific Data · 2024-06-07

    Yuwei Zhang, Fang-Yi Chen, Zeyi Liu, Yunzhuo Ju, Dongliang Cui, Jinyi Zhu, Xue Feng Jiang, Xi Guo, Jie He, Lei Zhang, Xiaotong Zhang, Yanjing Su

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  9. Autonomous Laboratories and Closed-Loop Materials Discovery: A Conceptual Framework for Self-Driving Experimentation

    Journal of Computational and Data-Driven Materials Engineering · 2025-01-01

    Thabo Nkosi, Lerato Molefe, Sipho Dlamini, Ayanda Mokoena, Kabelo Ndlovu

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  10. Large language models for knowledge graph extraction from tables in materials science

    Digital Discovery · 2025-01-01

    Max Dreger, Kourosh Malek, Michael Hermann Eikerling

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  11. KupferDigital: Ontology‐Based Digital Representation for the Copper Life Cycle

    Advanced Engineering Materials · 2025-03-28

    Miriam Eisenbart, Thomas Hanke, F. Bauer, Hossein Beygi Nasrabadi, Kurt Junghanns, Gordian Dziwis, Ladji Tikana, Ashak Mahmud Parvez, K. Gerald van den Boogaart, Mohsin Sajjad, Valérie Friedmann, Johannes Preußner, Anantha Narayanan Ramakrishnan, Sandy Klengel, Lars‐Peter Meyer, Michael Martin, Ulrich E. Klotz, Birgit Skrotzki, Matthias Weber

    Read original paper ↗ ·

  12. The Prediction of Tensile Strength Performance of Fiber‐Reinforced Composites Based on a Knowledge Graph Constructed From Material Literature

    Polymer Composites · 2025-05-27

    Qiaochuan Chen, Chen Zhao, Yating Fang, Rui Zhang, Na Song, Peng Ding, Yuexing Han

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  13. Constructing material network representations for intelligent amorphous alloy design

    National Science Review · 2025-09-17

    Shiyun Zhang, Jiachuan Tian, Songling Liu, Huimin Zhang, H. Y. Bai, Yuan‐Chao Hu, Weihua Wang

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  14. Designing a unified data structure for solid-electrolyte research projects

    Science and Technology of Advanced Materials Methods · 2025-10-29

    Yasuhiro Fujiwara, Kota Suzuki, Satoshi Hori, Yoshiyuki Inaguma, Akitoshi Hayashi, Masaki Azuma, Yasutoshi Iriyama, Hirotoshi Yamada, Tetsuhiro Katsumata, Kazunori Takada, Ryoji Kanno, Masahiko Demura

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  15. Chat-RFB: a flow battery chat system leveraging knowledge graphs and large language models

    Digital Discovery · 2026-01-01

    Haotian Wang, Xuefeng Bai, Zhiling Zheng, Xin Zhang, Ruipeng Jin, Hao-Tian An, Zheng-He Xie, Xiu‐Liang Lv, Jian-Rong Li

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  16. Combinatorial to autonomous experimentation

    Elsevier eBooks · 2026-01-01

    Krishna Rajan

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  17. Sustaining the growth of the materials informatics ecosystem

    Elsevier eBooks · 2026-01-01

    Krishna Rajan

    Read original paper ↗ ·

  18. Agentic Knowledge Graphs of the LiFePO 4 Cathode for Lithium Ion Battery: Balancing Discovery and Stability with LLMs

    Journal of Chemical Information and Modeling · 2026-01-22

    Lee Bin Choi, Ohyeon Lee, Sanghun Lee

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  19. Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science

    Journal of Cheminformatics · 2026-03-17

    Victor A. Dudarev, Alfred Ludwig

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  20. From Data to Discovery: Challenges and Solutions in AI-Driven Materials Science

    Journal of the Physical Society of Japan · 2026-03-25

    Hieu‐Chi Dam, Hiori Kino, Takashi Miyake

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  21. A survey of agentic materials science and engineering: where are we and where are we going?

    Journal of Materials Informatics · 2026-05-26

    Jiayi Zhu, Longhan Zhang, Yizhang Zhu, Xiaotian Lin, Yifan Wu, Shimin Di, Bang Liu, Yuyu Luo, Tong‐Yi Zhang

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  22. Materials by machines: A review on intuition and knowledge-driven learning for rapid discovery and optimization

    Materials Research Bulletin · 2026-05-29

    Mohannad Zeyad Naser, Prasada Rao Rangaraju

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  23. AI for Accelerated Materials Discovery: From Generative Design to Autonomous Realization

    Chemical Reviews · 2026-08-03

    Jiwoo Choi, Seongmin Kim, Junkil Park, Junyoung Choi, Sunggi An, Yousung Jung

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  24. AI agents for MOFs and COFs discovery

    AI Agent · 2026-08-17

    Jiayu Yu, Zihao Jiang, Donglin He

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  25. Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

    Advanced Engineering Materials · 2026-10-04

    Ahmed Amrani, Mohamed Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean-Philippe Poli

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