A review of machine learning applications in soil heavy-metal remediation: material design, process optimization, and future challenges.
- DOI
- 10.1007/s10653-026-03329-y
- Published
- 2026 Jul 14
- Container
- Environmental geochemistry and health
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s10653-026-03329-y,
title = {A review of machine learning applications in soil heavy-metal remediation: material design, process optimization, and future challenges.},
author = {Fu M and Tang Z and Liu Y and Zhou Y and Zhang C},
year = {2026},
journal = {Environmental geochemistry and health},
doi = {10.1007/s10653-026-03329-y},
url = {https://doi.org/10.1007/s10653-026-03329-y}
}RIS
TY - JOUR TI - A review of machine learning applications in soil heavy-metal remediation: material design, process optimization, and future challenges. AU - Fu M AU - Tang Z AU - Liu Y AU - Zhou Y AU - Zhang C PY - 2026 JO - Environmental geochemistry and health DO - 10.1007/s10653-026-03329-y UR - https://doi.org/10.1007/s10653-026-03329-y ER -
APA
M, F., Z, T., Y, L., Y, Z., & C, Z. (2026). A review of machine learning applications in soil heavy-metal remediation: material design, process optimization, and future challenges.. Environmental geochemistry and health. https://doi.org/10.1007/s10653-026-03329-y
Source records
- pubmed · retrieved 2026-09-25T04:18:22.449Z