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RESEARCH PAPER · Matter · 2019

Distilling a Materials Synthesis Ontology

Edward Kim, Kejun Huang, Olga Kononova, Gerbrand Ceder, Elsa Olivetti

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42 direct citing works

Distilling a Materials Synthesis OntologyOriginalText-mined dataset of inorganic materials synthesis recipes259Representing Multiword Chemical Terms through Phrase-Level Preprocessing and Word Embedding13Annotating and Extracting Synthesis Process of All-Solid-State Batteries from Scientific Literature14Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery99Opportunities and Challenges for Machine Learning in Materials Science523Data-driven materials research enabled by natural language processing and information extraction302Manufacturing scalability implications of materials choice in inorganic solid-state batteries65Machine learning for advanced energy materials208Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21 st century55Opportunities and challenges of text mining in materials research180Materials graph ontology23Toward Better and Smarter Batteries by Combining AI with Multisensory and Self‐Healing Approaches72Rational Solid-State Synthesis Routes for Inorganic Materials115Looking through glass: Knowledge discovery from materials science literature using natural language processing60IP Analytics and Machine Learning Applied to Create Process Visualization Graphs for Chemical Utility Patents4An exploratory analysis: extracting materials science knowledge from unstructured scholarly data4Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning1Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning4Fine-Tuning BERT Model for Materials Named Entity Recognition30Knowledge Graph-Empowered Materials Discovery13ULSA: unified language of synthesis actions for the representation of inorganic synthesis protocols28A review of the recent progress in battery informatics178Making the collective knowledge of chemistry open and machine actionable85Cost Profile of Membranes That Use Polymers of Intrinsic Microporosity (PIMs)16Challenges in Information-Mining the Materials Literature: A Case Study and Perspective21Using Machine Learning Language Models to Generate Innovation Knowledge Graphs for Patent Mining26Into the Unknown: How Computation Can Help Explore Uncharted Material Space65Realizing the cooking recipe of materials synthesis through large language models14Retrosynthesis from transforms to predictive sustainable chemistry and nanotechnology: a brief tutorial review19Review and Alignment of Domain-Level Ontologies for Materials Science28Unveiling the synthesis patterns of nanomaterials: a text mining and meta-analysis approach with ZIF-8 as a case study9The promise and pitfalls of AI for molecular and materials synthesis22Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO312Natural Language Processing7Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends56Unified Language of Operation Units for Robot-Executable Synthesis Protocols0Use of Large Language Models for Extracting and Analyzing Data from Heterogeneous Catalysis Literature18

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  1. Text-mined dataset of inorganic materials synthesis recipes

    Scientific Data · 2019-10-15

    Olga Kononova, Haoyan Huo, Tanjin He, Ziqin Rong, Tiago Botari, Wenhao Q. Sun, Vahe Tshitoyan, Gerbrand Ceder

    Read original paper ↗ ·

  2. Representing Multiword Chemical Terms through Phrase-Level Preprocessing and Word Embedding

    ACS Omega · 2019-10-31

    Liyuan Huang, Chen Ling

    Read original paper ↗ ·

  3. Annotating and Extracting Synthesis Process of All-Solid-State Batteries from Scientific Literature

    arXiv (Cornell University) · 2020-02-18

    Fusataka Kuniyoshi, Kohei Makino, Jun Ozawa, Makoto Miwa

    Read original paper ↗ ·

  4. Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery

    Annual Review of Materials Research · 2020-04-21

    Changwon Suh, Clyde Fare, James A. Warren, Edward O. Pyzer‐Knapp

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  5. Opportunities and Challenges for Machine Learning in Materials Science

    Annual Review of Materials Research · 2020-05-06

    Dane D. Morgan, Ryan Jacobs

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  6. Data-driven materials research enabled by natural language processing and information extraction

    Applied Physics Reviews · 2020-12-01

    Elsa Olivetti, Jacqueline M. Cole, Edward Kim, Olga Kononova, Gerbrand Ceder, T. Yong-Jin Han, Anna M. Hiszpanski

    Read original paper ↗ ·

  7. Manufacturing scalability implications of materials choice in inorganic solid-state batteries

    Joule · 2021-01-10

    Kejun Huang, Gerbrand Ceder, Elsa Olivetti

    Read original paper ↗ ·

  8. Machine learning for advanced energy materials

    Energy and AI · 2021-01-24

    Liu Yun, Oladapo Christopher Esan, Zhefei Pan, Liang An

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  9. Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21 st century

    International Journal of Applied Glass Science · 2021-01-26

    Ravinder, Vineeth Venugopal, Suresh Bishnoi, Sourabh Singh, Mohd Faiz Mohammad Zaki, Hargun Singh Grover, Mathieu Bauchy, Manish Agarwal, N. M. Anoop Krishnan

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  10. Opportunities and challenges of text mining in materials research

    iScience · 2021-02-07

    Olga Kononova, Tanjin He, Haoyan Huo, Amalie Trewartha, Elsa Olivetti, Gerbrand Ceder

    Read original paper ↗ ·

  11. Materials graph ontology

    Materials Letters · 2021-04-09

    Sven P. Voigt, Surya R. Kalidindi

    Read original paper ↗ ·

  12. Toward Better and Smarter Batteries by Combining AI with Multisensory and Self‐Healing Approaches

    Advanced Energy Materials · 2021-04-30

    Tejs Vegge, Jean‐Marie Tarascon, Kristina Edström

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  13. Rational Solid-State Synthesis Routes for Inorganic Materials

    Journal of the American Chemical Society · 2021-06-11

    Muratahan Aykol, Joseph H. Montoya, Jens S. Hummelshøj

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  14. Looking through glass: Knowledge discovery from materials science literature using natural language processing

    Patterns · 2021-06-24

    Vineeth Venugopal, Sourav Sahoo, Mohd Faiz Mohammad Zaki, Manish Agarwal, Nitya Nand Gosvami, N. M. Anoop Krishnan

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  15. IP Analytics and Machine Learning Applied to Create Process Visualization Graphs for Chemical Utility Patents

    Processes · 2021-07-30

    Amy J.C. Trappey, Charles V. Trappey, Chih-Ping Liang, Hsin-Jung Lin

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  16. An exploratory analysis: extracting materials science knowledge from unstructured scholarly data

    The Electronic Library · 2021-08-09

    Xintong Zhao, Jane Greenberg, Vanessa Meschke, Eric S. Toberer, Xiaohua Tony Hu

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  17. Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning

    arXiv (Cornell University) · 2021-09-27

    Xintong Zhao, Steven A. Lopez, Semion K. Saikin, Xiaohua Hu, Jane Greenberg

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  18. Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning

    Proceedings of the Association for Information Science and Technology · 2021-10-01

    Xintong Zhao, Steven A. Lopez, Semion K. Saikin, Xiaohua Tony Hu, Jane Greenberg

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  19. Fine-Tuning BERT Model for Materials Named Entity Recognition

    IEEE International Conference on Big Data (BigData) · 2021-12-15

    Xintong Zhao, Jane Greenberg, Yuan An, Xiaohua Tony Hu

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  20. Knowledge Graph-Empowered Materials Discovery

    IEEE International Conference on Big Data (BigData) · 2021-12-15

    Xintong Zhao, Jane Greenberg, Scott McClellan, Yong‐Jie Hu, Steven A. Lopez, Semion K. Saikin, Xiaohua Tony Hu, Yuan An

    Read original paper ↗ ·

  21. ULSA: unified language of synthesis actions for the representation of inorganic synthesis protocols

    Digital Discovery · 2022-01-01

    Zheren Wang, Kevin Cruse, Yuxing Fei, Ann Chia, Yan Zeng, Haoyan Huo, Tanjin He, Bowen Deng, Olga Kononova, Gerbrand Ceder

    Read original paper ↗ ·

  22. A review of the recent progress in battery informatics

    npj Computational Materials · 2022-02-18

    Chen Ling

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  23. Making the collective knowledge of chemistry open and machine actionable

    Nature Chemistry · 2022-04-01

    Kevin Maik Jablonka, Luc Patiny, Berend Smit

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  24. Cost Profile of Membranes That Use Polymers of Intrinsic Microporosity (PIMs)

    Membranes · 2022-04-17

    Despina A. Gkika, Volkan Filiz, Sofia Rangou, George Z. Kyzas, Athanasios C. Mitrοpoulos

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  25. Challenges in Information-Mining the Materials Literature: A Case Study and Perspective

    Chemistry of Materials · 2022-05-24

    Andrew K. Smith, Vinayak Bhat, Qianxiang Ai, Chad M. Risko

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  26. Using Machine Learning Language Models to Generate Innovation Knowledge Graphs for Patent Mining

    Applied Sciences · 2022-09-29

    Amy J.C. Trappey, Chih-Ping Liang, Hsin-Jung Lin

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  27. Into the Unknown: How Computation Can Help Explore Uncharted Material Space

    Journal of the American Chemical Society · 2022-10-07

    Austin M. Mroz, Víctor Posligua, Andrew Tarzia, Emma Helen Wolpert, Kim E. Jelfs

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  28. Realizing the cooking recipe of materials synthesis through large language models

    Journal of Materials Chemistry A · 2023-01-01

    Jaydeep Thik, Siwen Wang, Chuhong Wang, Hadi Mansourifar, Honghong Lin, Keiichi Okubo, Chen Ling

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  29. Retrosynthesis from transforms to predictive sustainable chemistry and nanotechnology: a brief tutorial review

    Green Chemistry · 2023-01-01

    Alicja Mikołajczyk, Uladzislau Zhdan, Sylvain Antoniotti, Adam Smoliński, Karolina Jagiełło, Piotr Skurski, Moussab Harb, Tomasz Puzyn, Jarosław Polański

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  30. Review and Alignment of Domain-Level Ontologies for Materials Science

    IEEE Access · 2023-01-01

    Anne F. de Baas, Pierluigi Del Nostro, Jesper Friis, Emanuele Ghedini, Gerhard Goldbeck, Ilaria Maria Paponetti, Andrea Pozzi, Arkopaul Sarkar, Lan Yang, Francesco Antonio Zaccarini, Daniele Toti

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  31. Unveiling the synthesis patterns of nanomaterials: a text mining and meta-analysis approach with ZIF-8 as a case study

    Digital Discovery · 2023-01-01

    Joseph R. H. Manning, Lev Sarkisov

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  32. The promise and pitfalls of AI for molecular and materials synthesis

    Nature Computational Science · 2023-05-18

    Nicholas David, Wenhao Q. Sun, Connor W. Coley

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  33. Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO3

    Chemistry of Materials · 2023-12-29

    Kevin Cruse, Viktoriia Baibakova, Maged Abdelsamie, Kootak Hong, Christopher J. Bartel, Amalie Trewartha, Anubhav Jain, Carolin M. Sutter‐Fella, Gerbrand Ceder

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  34. Natural Language Processing

    Machine intelligence for materials science · 2024-01-01

    N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo

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  35. Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends

    SN Computer Science · 2024-07-22

    Alireza Valizadeh, Mohammad Hossein Amirhosseini

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  36. Unified Language of Operation Units for Robot-Executable Synthesis Protocols

    Communications in computer and information science · 2025-01-01

    Yun Zhi Fu, Xiwen Liu

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  37. Use of Large Language Models for Extracting and Analyzing Data from Heterogeneous Catalysis Literature

    ACS Catalysis · 2025-08-11

    Benjamin W. Walls, Suljo Linic

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