Terahertz spectroscopy combined with machine-learning models for crude oil classification

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Zhang, Shanzhe, et al. “Terahertz Spectroscopy Combined With Machine-Learning Models for Crude Oil Classification”. Terahertz Science and Technology, vol. 16, no. 1, 2023, pp. 41-53, https://doi.org/10.3724/tst.041-053.2023.03.01.
Zhang, S., Zheng, D., Sun, X., Liu, C., Wu, J., & Yan, S. (2023). Terahertz spectroscopy combined with machine-learning models for crude oil classification. Terahertz Science and Technology, 16(1), 41-53. https://doi.org/10.3724/tst.041-053.2023.03.01
Zhang S, Zheng D, Sun X, Liu C, Wu J, Yan S. Terahertz spectroscopy combined with machine-learning models for crude oil classification. Terahertz Science and Technology. 2023;16(1):41-53.
Refrences
Title Journal Journal Categories Citations Publication Date
Gao GH, Cao J, Xu TW. Nuclear magnetic resonance spectroscopy of crude oil as proxies for oil source and thermal maturity based on H-1 and C-13 spectra. Fuel, 2022, 271: Fuel
  • Social Sciences: Industries. Land use. Labor: Special industries and trades: Energy industries. Energy policy. Fuel trade
  • Technology: Chemical technology: Chemical engineering
  • Technology: Chemical technology: Chemical engineering
  • Science: Chemistry
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Zhang S Z, Sun X R, Liu C L. Characterization of wax appearance temperature of model oils using laser-induced voltage. 2022, 34: 2022