Quantitative Prediction of Coal-Gangue Content Using Terahertz Time-Domain Spectroscopy and Physics-Informed Machine Learning.

Liu Z, Hu L, Xu J, Yang Y, Li S, Xu Z, Liu L, Li J, Liu H, Ye D

DOI: 10.3390/ma19173776
Published: 2026 Sep 4
Container: Materials (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/ma19173776,
  title = {Quantitative Prediction of Coal-Gangue Content Using Terahertz Time-Domain Spectroscopy and Physics-Informed Machine Learning.},
  author = {Liu Z and Hu L and Xu J and Yang Y and Li S and Xu Z and Liu L and Li J and Liu H and Ye D},
  year = {2026},
  journal = {Materials (Basel, Switzerland)},
  doi = {10.3390/ma19173776},
  url = {https://doi.org/10.3390/ma19173776}
}

RIS

TY  - JOUR
TI  - Quantitative Prediction of Coal-Gangue Content Using Terahertz Time-Domain Spectroscopy and Physics-Informed Machine Learning.
AU  - Liu Z
AU  - Hu L
AU  - Xu J
AU  - Yang Y
AU  - Li S
AU  - Xu Z
AU  - Liu L
AU  - Li J
AU  - Liu H
AU  - Ye D
PY  - 2026
JO  - Materials (Basel, Switzerland)
DO  - 10.3390/ma19173776
UR  - https://doi.org/10.3390/ma19173776
ER  -

APA

Z, L., L, H., J, X., Y, Y., S, L., Z, X., L, L., J, L., H, L., & D, Y. (2026). Quantitative Prediction of Coal-Gangue Content Using Terahertz Time-Domain Spectroscopy and Physics-Informed Machine Learning.. Materials (Basel, Switzerland). https://doi.org/10.3390/ma19173776

Source records

pubmed · retrieved 2026-09-25T06:14:54.701Z