Interpretable Machine Learning-Based QSPR Modeling for Predicting Hydrogen Adsorption Performance of Ester Oil Impregnating Agents
- DOI
- 10.1021/acsomega.6c11253
- Published
- 2026-10-22
- Container
- ACS Omega
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acsomega.6c11253,
title = {Interpretable Machine
Learning-Based QSPR Modeling
for Predicting Hydrogen Adsorption Performance of Ester Oil Impregnating
Agents},
author = {Xiaoyu Wang and Chao Ju and Huaigang Su and Qin Zhao and Haichao Liu and Qilong Zhao and Wenjing Lou},
year = {2026},
journal = {ACS Omega},
doi = {10.1021/acsomega.6c11253},
url = {https://doi.org/10.1021/acsomega.6c11253}
}RIS
TY - JOUR TI - Interpretable Machine Learning-Based QSPR Modeling for Predicting Hydrogen Adsorption Performance of Ester Oil Impregnating Agents AU - Xiaoyu Wang AU - Chao Ju AU - Huaigang Su AU - Qin Zhao AU - Haichao Liu AU - Qilong Zhao AU - Wenjing Lou PY - 2026 JO - ACS Omega DO - 10.1021/acsomega.6c11253 UR - https://doi.org/10.1021/acsomega.6c11253 ER -
APA
Wang, X., Ju, C., Su, H., Zhao, Q., Liu, H., Zhao, Q., & Lou, W. (2026). Interpretable Machine Learning-Based QSPR Modeling for Predicting Hydrogen Adsorption Performance of Ester Oil Impregnating Agents. ACS Omega. https://doi.org/10.1021/acsomega.6c11253
Source records
- crossref · retrieved 2026-11-07T15:40:36.941Z