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RESEARCH PAPER · ChemRxiv · 2022

Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models

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Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple modelsOriginalThe rise of automated curiosity-driven discoveries in chemistry20Self-Driving Laboratory for Polymer Electronics86Element selection for functional materials discovery by integrated machine learning of elemental contributions to properties15Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap7A Data-Science Approach to Experimental Catalyst Discovery: Integrating Exploration, Exploitation, and Serendipity5

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  1. The rise of automated curiosity-driven discoveries in chemistry

    Chemical Science · 2023-01-01

    Latimah Bustillo, Teodoro Laino, Tiago Rodrigues

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  2. Self-Driving Laboratory for Polymer Electronics

    Chemistry of Materials · 2023-03-09

    Aikaterini Vriza, Henry Chan, Jie Xu

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  3. Element selection for functional materials discovery by integrated machine learning of elemental contributions to properties

    npj Computational Materials · 2023-09-04

    Andrij Vasylenko, Dmytro Antypov, Vladimir V. Gusev, Michael W. Gaultois, Matthew Stephen Dyer, Matthew J. Rosseinsky

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  4. Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap

    Machine Learning Science and Technology · 2023-12-01

    Ryan M. Jacobs, Philip E. Goins, Dane D. Morgan

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  5. A Data-Science Approach to Experimental Catalyst Discovery: Integrating Exploration, Exploitation, and Serendipity

    ACS Catalysis · 2025-05-08

    Sunao Nakanowatari, KEISUKE G. TAKAHASHI, Hieu‐Chi Dam, Toshiaki Taniike

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