Experimental and artificial intelligence molecular models to predict quenching behavior of carbon materials from petroleum waste for sustainable corrosion monitoring.
- DOI
- 10.1039/d5ra02534f
- Published
- 2025 Oct 14
- Container
- RSC advances
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1039/d5ra02534f,
title = {Experimental and artificial intelligence molecular models to predict quenching behavior of carbon materials from petroleum waste for sustainable corrosion monitoring.},
author = {Zarewa MU and Saleh TA},
year = {2025},
journal = {RSC advances},
doi = {10.1039/d5ra02534f},
url = {https://doi.org/10.1039/d5ra02534f}
}RIS
TY - JOUR TI - Experimental and artificial intelligence molecular models to predict quenching behavior of carbon materials from petroleum waste for sustainable corrosion monitoring. AU - Zarewa MU AU - Saleh TA PY - 2025 JO - RSC advances DO - 10.1039/d5ra02534f UR - https://doi.org/10.1039/d5ra02534f ER -
APA
MU, Z., & TA, S. (2025). Experimental and artificial intelligence molecular models to predict quenching behavior of carbon materials from petroleum waste for sustainable corrosion monitoring.. RSC advances. https://doi.org/10.1039/d5ra02534f
Source records
- pubmed · retrieved 2026-11-10T07:10:40.493Z