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RESEARCH PAPER · The Journal of Physical Chemistry C · 2020

Can Machines “Learn” Halide Perovskite Crystal Formation without Accurate Physicochemical Features?

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

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42 direct citing works

Can Machines “Learn” Halide Perovskite Crystal Formation without Accurate Physicochemical Features?OriginalRobot-Accelerated Perovskite Investigation and Discovery186The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry3The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry6The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry2Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion19Active meta-learning for predicting and selecting perovskite crystallization experiments24Polymer Photoelectrodes for Solar Fuel Production: Progress and Challenges108Machine learning in energy chemistry: introduction, challenges and perspectives31The role of machine learning in perovskite solar cell research42Machine Learning in Perovskite Solar Cells: Recent Developments and Future Perspectives76Machine learning–assisted colloidal synthesis: A review39

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  1. Robot-Accelerated Perovskite Investigation and Discovery

    Chemistry of Materials · 2020-06-04

    Zhi Li, Mansoor Ani Najeeb, Liana Alves, Alyssa Sherman, Venkateswaran Shekar, Peter L. Cruz Parrilla, Ian M. Pendleton, Wesley Wang, Philip W. Nega, Mat­thias Zeller, Joshua Schrier, Alexander J. Norquist, Emory M. Chan

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  2. The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry

    The Journal of Physical Chemistry C · 2020-11-05

    Andrew L. Ferguson, Johannes Hachmann, Thomas F. Miller, Jim Pfaendtner

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  3. The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry

    The Journal of Physical Chemistry B · 2020-11-05

    Andrew L. Ferguson, Johannes Hachmann, Thomas F. Miller, Jim Pfaendtner

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  4. The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry

    The Journal of Physical Chemistry A · 2020-11-05

    Andrew L. Ferguson, Johannes Hachmann, Thomas F. Miller, Jim Pfaendtner

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  5. Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion

    Journal of Chemical Information and Modeling · 2021-04-02

    Yuanqing Tang, Zhi Li, Mansoor Ani Najeeb, Hamed Eramian, Emory M. Chan, Alexander J. Norquist, D. Frank Hsu, Joshua Schrier

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  6. Active meta-learning for predicting and selecting perovskite crystallization experiments

    The Journal of Chemical Physics · 2022-01-23

    Venkateswaran Shekar, Gareth Nicholas, Mansoor Ani Najeeb, Margaret Zeile, Vincent Yu, Xiaorong Wang, Dylan Slack, Zhi Li, Philip W. Nega, Emory M. Chan, Alexander J. Norquist, Joshua Schrier, Sorelle A. Friedler

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  7. Polymer Photoelectrodes for Solar Fuel Production: Progress and Challenges

    Chemical Reviews · 2022-06-14

    Madasamy Thangamuthu, Qiushi Ruan, Peter Osei Ohemeng, Bing Luo, Dengwei Jing, Robert Godin, Junwang Tang

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  8. Machine learning in energy chemistry: introduction, challenges and perspectives

    Energy Advances · 2023-01-01

    Yuzhi Xu, Jiankai Ge, Cheng‐Wei Ju

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  9. The role of machine learning in perovskite solar cell research

    Journal of Alloys and Compounds · 2023-06-01

    Chen Chen, Ayman Maqsood, T. Jesper Jacobsson

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  10. Machine Learning in Perovskite Solar Cells: Recent Developments and Future Perspectives

    Energy Technology · 2023-09-13

    Nitin Kumar Bansal, Snehangshu Mishra, Himanshu Dixit, Shivam Porwal, Paulomi Singh, Trilok Singh

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  11. Machine learning–assisted colloidal synthesis: A review

    Materials Today Chemistry · 2023-12-07

    Dayana Gulevich, Igor R. Nabiev, Pavel S. Samokhvalov

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