A generalizable time-gated Raman spectroscopy–machine learning workflow for accurate identification of challenging plastics in electronic waste
- DOI
- 10.1016/j.wasman.2026.115826
- Published
- 2026-10
- Container
- Waste Management
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.wasman.2026.115826,
title = {A generalizable time-gated Raman spectroscopy–machine learning workflow for accurate identification of challenging plastics in electronic waste},
author = {Sydney N. Pedari and Hieu Minh Le and Vy Tran and Daniel S. Grégoire and Yaxi Hu},
year = {2026},
journal = {Waste Management},
doi = {10.1016/j.wasman.2026.115826},
url = {https://doi.org/10.1016/j.wasman.2026.115826}
}RIS
TY - JOUR TI - A generalizable time-gated Raman spectroscopy–machine learning workflow for accurate identification of challenging plastics in electronic waste AU - Sydney N. Pedari AU - Hieu Minh Le AU - Vy Tran AU - Daniel S. Grégoire AU - Yaxi Hu PY - 2026 JO - Waste Management DO - 10.1016/j.wasman.2026.115826 UR - https://doi.org/10.1016/j.wasman.2026.115826 ER -
APA
Pedari, S. N., Le, H. M., Tran, V., Grégoire, D. S., & Hu, Y. (2026). A generalizable time-gated Raman spectroscopy–machine learning workflow for accurate identification of challenging plastics in electronic waste. Waste Management. https://doi.org/10.1016/j.wasman.2026.115826
Source records
- crossref · retrieved 2026-09-25T11:55:50.676Z