Optimizing Ash Content in Biomass Hydrothermal Liquefaction through Machine Learning and Sustainability Assessment
- DOI
- 10.1021/acs.est.6c05758
- Published
- 2026-09-02
- Container
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acs.est.6c05758,
title = {Optimizing Ash Content
in Biomass Hydrothermal Liquefaction
through Machine Learning and Sustainability Assessment},
author = {Tonggui Liu and Donghai Xu and Guanyu Jiang and Phillip E. Savage and Lili Qian and Xin Ding and Shuzhong Wang and Ya-Ling He},
year = {2026},
journal = {Environmental Science \&
Technology},
doi = {10.1021/acs.est.6c05758},
url = {https://doi.org/10.1021/acs.est.6c05758}
}RIS
TY - JOUR TI - Optimizing Ash Content in Biomass Hydrothermal Liquefaction through Machine Learning and Sustainability Assessment AU - Tonggui Liu AU - Donghai Xu AU - Guanyu Jiang AU - Phillip E. Savage AU - Lili Qian AU - Xin Ding AU - Shuzhong Wang AU - Ya-Ling He PY - 2026 JO - Environmental Science & Technology DO - 10.1021/acs.est.6c05758 UR - https://doi.org/10.1021/acs.est.6c05758 ER -
APA
Liu, T., Xu, D., Jiang, G., Savage, P. E., Qian, L., Ding, X., Wang, S., & He, Y. (2026). Optimizing Ash Content in Biomass Hydrothermal Liquefaction through Machine Learning and Sustainability Assessment. Environmental Science & Technology. https://doi.org/10.1021/acs.est.6c05758
Source records
- crossref · retrieved 2026-11-07T04:01:44.618Z