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                  International Journal of Terahertz Science and Technology
Vol.16, No.1, March 2023. PP.1-53(5)--Focus issue on "Application of terahertz spectroscopy"
date£º2023-03-31 23:56:32 Click No.£º598

Preface

Terahertz technology has been widely used in physics, chemistry, biology, materials science and other fields due to its advantages of non-contact, high sensitivity and immunity from electromagnetic interference, which was honored as ¡®one of the top ten technologies that will change the future world¡¯ at the Xiangshan Science and Technology Conference in November 2005.

In order to timely report and display the latest research progress of terahertz technology in the fields of fossil energy, agricultural products, et al., a special topic ¡®Application of terahertz spectroscopy¡¯ was organized, where these papers cover the applications of terahertz spectroscopy combined with artificial intelligence algorithms in detection and characterization of, such as cottonseed fullness, trace crude oil in quartz sand, high sensitivity polyethylene, crude oil types, and magnetic field induced reduction of intermolecular force between the normal alkanes.

In short, terahertz technology is becoming one of the important optical characterization means and will play an increasingly important role in various fields. Here, by introducing this issue of the topic, we firmly believe that there will be more researchers to join in this field and achieve more excellent results!

 

Guest Editor: Kun Zhao, from China University of Petroleum

March 30, 2023


TST, Vol. 16, No. 1, PP. 1-11

(Invited paper) Detection method of cottonseed fullness on the basis of terahertz spectroscopy and imaging technology

Junjie Wang, Yang Li, Jingzhu Wu *, Cuiling Liu, Xiaorong Sun, and Shanzhe Zhang
Beijing Key Laboratory of Food Safety Big Data Technology, Beijing Technology and Business University, Beijing 100048, China
* E-mail:
pubwu@163.com

(Received March 2023)

Abstract: Cottonseed fullness is an important indicator in characterizing the quality of cottonseed. This paper explores the application of terahertz time-domain spectral transmission imaging technology with image refactoring image processing and other methods in cottonseed fullness detection research. In this study, the Terapulse 4000 terahertz (THz) time-domain spectroscopy system and a transmission imaging accessory are used to collect THz spectral images of cottonseed samples. Certain differences can be observed in the composition and spatial distribution of the seed kernel and the seed cavity for which terahertz images at different depths is useful in clearly distinguishing the seed kernel and the seed cavity. To explore the imaging results of the samples under different refactoring methods and use the maximum inter-class variance method (Otsu method) to remove the background to obtain complete sample images, the mathematical morphology algorithm is used to select the circular structural element with a side length of 3 as the check image for dilation corrosion and non-destructively extract the images of different tissues of cottonseed. The THz time-domain spectral images are organized, and then a fullness model of cottonseed based on the THz time-domain spectral images is established according to the enrichment quantification calculation formula. Experimental results show that the non-destructive testing of cottonseed samples can be achieved by using terahertz time-domain spectral imaging technology and is expected to provide a theoretical basis and a method reference for shelled seeds¡¯ non-destructive testing.

Keywords: Terahertz time-domain spectral transmission imaging technology, Cottonseed fullness, Image refactoring, Image processing

doi:

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TST, Vol. 16, No. 1, PP. 12-18

(Invited paper) Terahertz spectroscopy properties of trace crude oil in quartz sand

Zhaohui Meng 1, Yan Zhang 2, 3, Ru Chen 2, 3, Kun Zhao 1*, 2, 3, Honglei Zhan 1, and Xinyang Miao 1
1 College of New Energy and Materials, China University of Petroleum, Beijing 102249, China
2 Beijing Key Laboratory of Optical Detection Technology for Oil and Gas, China University of Petroleum, Beijing 102249, China
3 Key Laboratory of Oil and Gas Terahertz Spectroscopy and Photoelectric Detection, Petroleum and Chemical Industry Federation, China University of Petroleum, Beijing 102249, China
*1 Email:
zhk@cup.edu.cn

(Received March 2023)

Abstract: The purpose of this article is to classify the types of crude oils from different regions and oil-quartz sand mixture with different oil content with terahertz time-domain spectroscopy (THz-TDS). Multivariate statistical methods, including cluster analysis (CA) and principal component analysis (PCA), are used to build models between THz parameters and crude oils from different regions. The sample absorbance first increases and then decreases  with the increase of oil content, revealing that the THz response is caused by the cracks and oil content simultaneously. When the oil content is smaller than the critical concentration, the existence of cracks makes more scattering; meanwhile, the more the oil content is , the larger the THz absorption becomes when the oil content is  larger than the critical concentration. Consequently, the combination of THz technology as well as multivariate statistical methods could be an effective method for rapid identification of crude oils content and the geographical locations of crude oils.

Keywords: Terahertz time-domain spectroscopy, Crude oil, Trace, Multivariate statistical methods

doi:

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TST, Vol. 16, No. 1, PP. 19-28

(Invited paper) Magnetic field induced reduction of intermolecular force between the normal alkanes

Lu Tian 1*, and Baoping Zhang 2
1 School of Physics, Northwest University, Xi¡¯an 710127, China;
2 Institute of Photonics and Photon-Technology, Northwest University, Xi¡¯an 710127, China;
*1 Email:
tianlu@nwu.edu.cn

(Received March 2023)

Abstract: Magnetic field can significantly change the characteristics of alkanes and related petroleum products, and the physical mechanism has received much attention for several years. Terahertz time-domain spectroscopy (THz-TDS) is employed in this paper to characterize the optical parameters and diamagnetic anisotropy properties of liquid normal alkanes (n-alkanes) under the action of a magnetic field. The corresponding absorption coefficients of samples are obtained by a fast Fourier transform, and the orientation characteristics of n-alkanes are analyzed under a relative weak magnetic field. The results indicate THz-TDS has great potential for the identification of intermolecular interaction in the organic molecules.

Keywords: Magnetic, Molecular, Interaction, Alkanes, Terahertz.

doi:

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TST, Vol. 16, No. 1, PP. 29-40

(Invited paper) Characterizations of high-density polyethylene by terahertz time-domain spectroscopy

Tong Zhang, Siqi Zhang, Zhiyuan Zheng *, Jingya Zhu, Bochao Guan, and Haochong Huang
School of Science, China University of Geosciences (Beijing), Beijing, 100083, China
* Email:
zhyzheng@cugb.edu.cn

(Received March 2023)

Abstract: The optical properties of high-density polyethylene (HDPE) in the terahertz band are characterized by terahertz time-domain spectroscopy (THz-TDS). The results show that the THz-TDS can effectively distinguish the particle size of HDPE and filler content of HDPE. And it can also be used to characterize the adsorption characteristics of HDPE. These indicate that it can improve the performance of HDPE, industrial production and even environmental pollution of micro-size of HDPE.

Keywords: High-density polyethylene, Terahertz spectrum, Filler, Absorption coefficient, Microplastics.

doi:

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TST, Vol. 16, No. 1, PP. 41-53

(Invited paper) Terahertz spectroscopy combined with machine-learning models for crude oil classification

Shanzhe Zhang 1, 2*, Dongyu Zheng 1, 2, Xiaorong Sun 1, 2*, Cuiling Liu 1, 2, Jingzhu Wu 1, 2, and Sining Yan 1, 2
1 School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China
2 Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China
*2 Email:
zhangsz@btbu.edu.cn; sxrchy@sohu.com

(Received March 2023)

Abstract: The classification of crude oils plays an important role in the petroleum transportation and production. In this paper, terahertz time-domain spectroscopy(THz-TDS) is used to assess seven various crude oils combined with machine-learning algorithms. From THz-TDS, frequency, refractive index and absorption coefficient are used to set models, which are based on Extreme Gradient Boosting (XGBoost), Random Forest (RF) and K-Nearest Neighbors (KNN), respectively. In order to evaluate the accuracy of each model, the confusion matrix and the Area under the curve (AUC) are introduced to access the classification ability, and 5-fold cross-validation are used to compare the generalization ability and robustness. Compared to other models, the classification accuracy of XGBoost reaches the maximum 0.9622. Meanwhile, the test 5-fold cross-validation F1-score and the AUC of XGBoost model are higher than other models, which indicates the high consistency and robustness. Experimental results suggests that terahertz time-domain spectroscopy may be a powerful tool for the identification of various crude oils.

Keywords: Terahertz spectroscopy, Crude oil classification

doi:

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