A generalizable time-gated Raman spectroscopy–machine learning workflow for accurate identification of challenging plastics in electronic waste

Sydney N. Pedari, Hieu Minh Le, Vy Tran, Daniel S. Grégoire, Yaxi Hu

Open source

DOI
10.1016/j.wasman.2026.115826
Published
2026-10
Container
Waste Management
Publisher
Elsevier BV
Open access
unknown

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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

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