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10.1038-s43246-022-00269-9 |
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|a 26624443 (ISSN)
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|a Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method
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|b Springer Nature
|c 2022
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|z View Fulltext in Publisher
|u https://doi.org/10.1038/s43246-022-00269-9
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|a Fractionally doped perovskites oxides (FDPOs) have demonstrated ubiquitous applications such as energy conversion, storage and harvesting, catalysis, sensor, superconductor, ferroelectric, piezoelectric, magnetic, and luminescence. Hence, an accurate, cost-effective, and easy-to-use methodology to discover new compositions is much needed. Here, we developed a function-confined machine learning methodology to discover new FDPOs with high prediction accuracy from limited experimental data. By focusing on a specific application, namely solar thermochemical hydrogen production, we collected 632 training data and defined 21 desirable features. Our gradient boosting classifier model achieved a high prediction accuracy of 95.4% and a high F1 score of 0.921. Furthermore, when verified on additional 36 experimental data from existing literature, the model showed a prediction accuracy of 94.4%. With the help of this machine learning approach, we identified and synthesized 11 new FDPO compositions, 7 of which are relevant for solar thermochemical hydrogen production. We believe this confined machine learning methodology can be used to discover, from limited data, FDPOs with other specific application purposes. © 2022, The Author(s).
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|a Catalysis sensors
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|a Cost effective
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|a Cost effectiveness
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|a Digital storage
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|a Forecasting
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|a Hydrogen production
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|a Hydrogen storage
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|a Machine learning
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|a Machine learning methods
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|a Machine-learning
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|a Perovskite
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|a Perovskite oxides
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|a Piezoelectric
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|a Prediction accuracy
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|a Solar energy
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|a Solar power generation
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|a Solar thermo-chemical hydrogen
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|a Thermochemical hydrogen production
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|a Ubiquitous application
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|a Ding, F.
|e author
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|a Luo, F.
|e author
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|a Santomauro, A.
|e author
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|a Tong, J.
|e author
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|a Zhai, X.
|e author
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|a Zhao, Z.
|e author
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|t Communications Materials
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