Toward the Prediction of Electrochromic Properties of WO(3) Films: Combination of Experimental and Machine Learning Approaches.
- DOI
- 10.1021/acs.jpclett.2c02248
- Published
- 2022 Sep 1
- Container
- The journal of physical chemistry letters
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1021/acs.jpclett.2c02248,
title = {Toward the Prediction of Electrochromic Properties of WO(3) Films: Combination of Experimental and Machine Learning Approaches.},
author = {Faceira B and Teule-Gay L and Rignanese GM and Rougier A},
year = {2022},
journal = {The journal of physical chemistry letters},
doi = {10.1021/acs.jpclett.2c02248},
url = {https://doi.org/10.1021/acs.jpclett.2c02248}
}RIS
TY - JOUR TI - Toward the Prediction of Electrochromic Properties of WO(3) Films: Combination of Experimental and Machine Learning Approaches. AU - Faceira B AU - Teule-Gay L AU - Rignanese GM AU - Rougier A PY - 2022 JO - The journal of physical chemistry letters DO - 10.1021/acs.jpclett.2c02248 UR - https://doi.org/10.1021/acs.jpclett.2c02248 ER -
APA
B, F., L, T., GM, R., & A, R. (2022). Toward the Prediction of Electrochromic Properties of WO(3) Films: Combination of Experimental and Machine Learning Approaches.. The journal of physical chemistry letters. https://doi.org/10.1021/acs.jpclett.2c02248
Source records
- pubmed · retrieved 2026-09-27T08:50:37.425Z
- europe-pmc · retrieved 2026-09-27T08:50:37.426Z
- hal · retrieved 2026-09-27T08:50:37.465Z