Terahertz Time-domain Spectroscopy Technology Research Articles

Research on the Application of THz-TDS in Coal–Rock Interface Recognition

The recognition of coal–rock interface is very crucial for research in the intelligent production of coal mines. To this end, the study investigated the application of terahertz time-domain spectroscopy in the recognition of coal–rock interface, including the identification of coal–rock and coal–rock mixtures, as well as the accurate characterization of coal seam thickness. Terahertz detection was used to obtain the optical parameter information of pressed pellets prepared by mixing two different kinds of coal and two kinds of rock. Based on the experiment’s results, a database was established for the identification of coal–rock interfaces for coal mining machines. The terahertz detection was performed on 10 different kinds of sheet anthracite with different thicknesses, and the terahertz spectra of coal seams with different thicknesses were simulated and calculated using simulation software. By comparing the two effective mining thicknesses, parameters can be provided for coal seam mining. The experiment and simulation show that the terahertz time-domain spectroscopy technology has a promising application prospect in the identification of coal–rock interface.

Classification of wheat grain varieties using terahertz spectroscopy and convolutional neural network

Wheat quality and quantity differ in diverse climates. Therefore, it is essential to identify the variety before purchasing and warehousing. In this study, a study on variety discrimination for 12 wheat varieties (strong-gluten wheat, medium-gluten wheat, weak-gluten wheat) using the Terahertz time-domain spectroscopy (THz-TDS) technology in combination with a Convolutional neural network (CNN). Firstly, the original Time-domain spectra (TDS) of wheat in the range of 0.1–2.0 THz were acquired, and the Frequency domain spectra (FDS), the absorption coefficient spectra in the range of 0.2–1.0 THz were obtained through Fourier Transform. Then, Competitive adaptive reweighted sampling (CARS) algorithms were applied to screen the feature spectrum. Finally, the Support vector machine (SVM), the Least square support vector machine (LS-SVM), the Back-propagation neural networks (BPNN) and CNN models were constructed using feature spectral data. By comparing the four models, it was found that the calibration set accuracy and prediction set accuracy of the CNN model reached 98.7% and 97.8% respectively, with an error recognition rate of only 2.2%. The research results show that combining THz-TDS technology with CNN has the advantages of accurate recognition and high efficiency. It can identify different wheat varieties and can be used for seed classification and quality detection.

Defect detection of composite materials for cable insulation layer based on terahertz

Hidden defects can seriously affect the insulation performance of cables and pose safety hazards. In this article, a novel Non-Destructive evaluation technique for insulation materials based on terahertz time-domain spectroscopy technology is proposed. Firstly, terahertz time-domain spectroscopy technology was used to perform reflective scanning on insulation materials. Various imaging algorithms were used to image terahertz defects. The results showed that the maximum imaging and peak to peak time imaging were effective. At the same time, bilateral filtering was used to process terahertz defect images. The results showed that bilateral filtering not only filtered out noise in terahertz images, but also retained edge details. Terahertz time-domain spectroscopy technology offers a fresh approach for detecting cable insulation material defects non-destructively, and finds application in various electrical environment inspections.

Progress in application of terahertz time-domain spectroscopy for pharmaceutical analyses.

Terahertz time-domain spectroscopy is an analytical method using terahertz time-domain pulses to study the physical and chemical properties of substances. It has strong potential for application in pharmaceutical analyses as an original non-destructive, efficient and convenient technology for spectral detection. This review briefly introduces the working principle of terahertz time-domain spectroscopy technology, focuses on the research achievements of this technology in analyses of chemical drugs, traditional Chinese medicine and biological drugs in the past decade. We also reveal the scientific feasibility of practical application of terahertz time-domain spectroscopy for pharmaceutical detection. Finally, we discuss the problems in practical application of terahertz time-domain spectroscopy technology, and the prospect of further development of this technology in pharmaceutical analyses. We hope that this review can provide a reference for application of terahertz time-domain spectroscopy technology in pharmaceutical analyses in the future.

Prediction of IDH mutation status of glioma based on terahertz spectral data

Gliomas are the most common type of primary tumor in the central nervous system in adults. Isocitrate dehydrogenase (IDH) mutation status is an important molecular biomarker for adult diffuse gliomas. In this study, we were aiming to predict IDH mutation status based on terahertz time-domain spectroscopy technology. Ninety-two frozen sections of glioma tissue from nine patients were included, and terahertz spectroscopy data were obtained. Through Least Absolute Shrinkage and Selection Operator (LASSO), Principal component analysis (PCA), and Random forest (RF) algorithms, a predictive model for predicting IDH mutation status in gliomas was established based on the terahertz spectroscopy dataset with an AUC of 0.844. These results indicate that gliomas with different IDH mutation status have different terahertz spectral features, and the use of terahertz spectroscopy can establish a predictive model of IDH mutation status, providing a new way for glioma research.

Research on Defect Detection Imaging of Ceramic Matrix Composites Based on Terahertz Time-domain Spectroscopy Technology

Research on Defect Detection Imaging of Ceramic Matrix Composites Based on Terahertz Time-domain Spectroscopy Technology

Biomedical applications of terahertz spectra in clinical and molecular pathology of human glioma

Gliomas are the most common type of primary tumor originating in the central nervous system of adults. Tumor histological type, pathological grade, and molecular pathology are significant prognosis and predictive factors. In this study, we were aiming to predict histological type and molecular pathological features based on terahertz time-domain spectroscopy technology. Nine gliomas with different grades, one meningioma, and one lymphoma were enrolled. There were significant differences in terahertz absorption coefficient between normal brain tissue, tumoral-periphery, and tumoral-center tissue in specific frequency bands (0.2–1.4 THz). Histological type, pathological grade, and glioma-specific biomarkers were closely related to the terahertz absorption coefficient in both tumoral-periphery and tumoral-center tissues. Interestingly, tumoral-periphery showed more obvious differences than tumoral-center tissues in almost all aspects. All the results show that the terahertz technology has potential application value in the intraoperative real-time glioma recognition and diagnosis of glioma histological and molecular pathological features.

Terahertz transmission characteristics of xanthan gum colloids in a microfluidic chip

Terahertz time-domain spectroscopy (THz-TDS) technology has great application prospects for the detection of biological macromolecules, whereas microfluidic technology uses micro-channel networks to manipulate liquids, which can reduce the influence of hydrogen bonds in liquids on THz waves. The combination of these two technologies makes the detection of THz waves in aqueous solutions of biomolecules more accurate and efficient. In this study, microfluidic technology and THz-TDS technology were applied to study the THz transmission characteristics of xanthan gum, providing three feasible methods for the detection of xanthan gum colloids.

Detection of carbendazim in oranges with metal grating integrated microfluidic sensor in terahertz

A novel microfluidic metal grating integrated terahertz sensor has been designed, which is composed of a metal microstructure array-dielectric layer-metal layer, where the dielectric layer is the microfluidic channel carrying the analyte. By adjusting the structural parameters of the metal grating sensor, a highly confined electromagnetic field can be obtained in the microfluidic channel, thereby significantly enhancing the interaction between the analyte and the terahertz wave and improving the terahertz detection sensitivity. The metal grating described in this paper is composed of an array of square holes, which is manufactured using laser micromachining technology, so that the measurement method is simplified and improved. The results show that the addition of different concentrations of carbendazim solution resulted in a redshift of the overall spectrum, with the highest sensitivity reaching 8.773 GHz/mg L−1, which is about eight times more sensitive than the traditional terahertz transmission sensor. The relative error of using this method to determine carbendazim levels in orange juice samples was less than 5.3%. The terahertz time-domain spectroscopy technology combined with the metal grating integrated microfluidic sensor can improve the sensitivity of sample detection and realize the rapid detection and analysis of trace elements.

Detection of Adulteration of Panax Notoginseng Powder by Terahertz Technology

The combined terahertz time-domain spectroscopy (THz-TDS) and chemometric technology is used to detect the adulteration of similar substances in Panax notoginseng powder. Four kinds of samples are prepared in the experiment, three kinds of adulterated samples are Panax notoginseng powder adulterating with zedoary turmeric powder, Panax notoginseng powder adulterating with wheat flour, and Panax notoginseng powder adulterating with rice flour, respectively. The values of adulterated concentration are from 5% to 60%, the interval of adulterated concentration is 5%, and the other sample is pure Panax notoginseng powder. The modeling and prediction sets are divided by 3 : 1 by class. The feature information of models is extracted by elimination of uninformative variable (UVE) method and successive projection algorithm (SPA); combining with back propagation neural network (BPNN), the UVE-BPNN and SPA-BPNN qualitative models are established, respectively. The model’s results show that the UVE-BPNN model is better; the classification accuracy of the prediction set of UVE-BPNN is 95%. Then, the least square support vector machine (LS-SVM) algorithm and partial least square (PLS) algorithm are used to establish the quantitative analysis model. The model’s results show that the LS-SVM model is better among the quantitative analysis models of zedoary turmeric powder and wheat flour, the correlation coefficient of prediction (RP) is 0.90 and 0.93 of LS-SVM, respectively, and the root mean square error of prediction (RMSEP) of LS-SVM is 0.072 and 0.068, respectively. Among the quantitative analysis models for rice noodles, the PLS model is better, with the RP of 0.94 and RMSEP of 0.06. The results show that the combined THz-TDS and chemometric technology can be used to determine the adulteration of similar substances in Panax notoginseng powder quickly, accurately, and nondestructively.

Nondestructive Evaluation of Thermal Barrier Coatings Thickness Using Terahertz Technique Combined with PCA–GA–ELM Algorithm

Thermal barrier coatings (TBCs) are usually used in high temperature and harsh environment, resulting in thinning or even spalling off. Hence, it is vital to detect the thickness of the TBCs. In this study, a hybrid machine learning model combined with terahertz time-domain spectroscopy technology was designed to predict the thickness of TBCs. The terahertz signals were obtained from the samples prepared in laboratory and actual turbine blade. The principal component analysis (PCA) method was used to decrease the data dimensions. Finally, an extreme learning machine (ELM) was proposed to establish the thickness of TBCs prediction model. Genetic algorithm (GA) was selected to optimize the model to make it more accurate. The results showed that the root correlation coefficient (R2) exceeded 0.97 and the errors (root mean square error and mean absolute percentage error) were less than 2.57. This study proposes that terahertz time-domain technology combined with PCA–GA–ELM model is accurate and feasible for evaluating the thickness of the TBCs.

Non-destructive detection for foreign bodies of tea stalks in finished tea products using terahertz spectroscopy and imaging

Foreign bodies e.g. tea stalks are easily to mix into tea leaves during picking up tea leaves with machine harvester. Tea stems have become a major physical pollutant for finishing tea products, and they cannot be effectively detected with machine vision in the visible region. In the current study, terahertz time domain spectroscopy (THz-TDS) and imaging was employed to rapidly and non-destructively detect tea stalk foreign bodies in tea leaves. With the input variables of THz time-domain signal and frequency-domain absorption coefficients, the K nearest neighbor (KNN) qualitative discriminant models were developed with combination of baseline correction algorithms of adaptive iteratively reweighted penalized least squares (AirPLS), asymmetric least squares (AsLS), background correction (Backcor) and baseline estimation and denoising with sparsity (BEADS). Results showed that the AirPLS-KNN model with the input vector of THz time-domain signals presented the best performance, with the accuracy rate of prediction and recall rate reaching 97.3% and 0.96, respectively. With 0.2 mm step length of both the X and Y directions, the THz transmission imaging was scanned to obtain the THz image of 150X130 pixel2 whose resolution and imaging duration were 1.09 mm and 4.4 min respectively, so the outline of tea stalks could be well identified. In conclusion, the THz-TDS and imaging technology serves as a new means for non-destructive detection of tea stalk foreign bodies in tea leaves.

Detection of aging in the common explosive RDX using terahertz time-domain spectroscopy

A method to detect the aging in cyclotrimethylene-trinitramine (RDX), using terahertz (THz) waves, is reported in this paper. The absorption spectra of RDX are analyzed, and any changes of the characteristic absorption peaks (before and after aged treatment of RDX in laboratory) are compared. When RDX samples undergo aging, the characteristic absorption peaks (at 1.02 THz, 1.36 THz, 1.58 THz, and 2.37 THz) disappear, which corresponds to the fracture of N- N O 2 bonds in RDX molecules. These results show that THz time-domain spectroscopy technology may be used not only for analysis but also for detection of aging in RDX and similar materials.

Terahertz Spectral Properties of 5-Substituted Uracils

Applications of terahertz time-domain spectroscopy (THz-TDS) in the fields of chemistry and biomedicine have recently received increased attention. Specifically, THz-TDS is particularly effective for the identification of alkaloid molecules, because it can distinguish the vibration types of base molecules in the THz band and provide a direct characteristic spectrum for the configuration and conformation of biomolecules. However, when THz-TDS technology is used to identify alkaloid molecules, most of them are concentrated in the 0.1–3.0 THz band, limiting the amount of information that can be obtained. In this work, a wide-spectrum THz-TDS system was independently built to explore the absorption spectra of uracil and its 5-substituents in the range of 1.3–6.0 THz. We found that, in the THz band, uracil and its 5-substituents have similar absorption peaks near 4.9 and 3.3 THz, while the 5-substituents have an additional absorption peak in the range of 1.5–2.5 THz. This absorption peak is red-shifted as the relative atomic mass of the 5-substituted atoms increases. Gaussian software was adopted to calculate the absorption spectra of the samples. The simulation conclusions were in good agreement with the experimental results, revealing that the vibration of the base molecule at low frequencies can be attributed to the inter-molecular vibration. This work demonstrates that THz-TDS technology can be used to accurately identify biomolecules with similar molecular structures, reflecting the importance of molecular structure in biological activity.

Sensitive characterizations of polyvinyl chloride using terahertz time-domain spectroscopy

The optical properties of polyvinyl chloride have been investigated by the terahertz time-domain spectroscopy technology to highlight their application. Optical parameters such as absorption coefficient, phase difference and refractive index have presented different characterizations among different particle sizes, types and proportion blends. The adsorption properties of polyvinyl chloride on methyl orange were studied and characterized by terahertz spectroscopy at different times. These results provide a database for the efficient utilization and performance improvement of polyvinyl chloride and its blends in terahertz technology, which are of great significance for the non-destructive testing of plastic products in industrial production and the adsorption analysis of microplastics in the environment.

Application of THz-TDS Technology in on-line detection of vacuum degree of arc extinguishing chamber

Terahertz time-domain spectroscopy (THz-TDS) is a non-destructive detection technology for carrying information inside a sample through a wide-band terahertz pulse carrying medium information. This paper briefly describes the imaging principle, characteristics, development and application direction of THz-TDS technology. The theoretical basis of THz-TDS technology applied in vacuum degree on-line monitoring is analyzed and verified by experiments. The experimental results show that with the change of vacuum degree, the signal amplitude attenuation and time delay of THz spectrum will change regularly. It shows that the spectrum and absorption spectrum obtained by THz-TDS imaging technology can sensitively distinguish the change of pressure in vacuum environment, that is, the change of vacuum degree. At the same time, the related air environmental pollution information also has strong absorption characteristics in the terahertz band, which makes the use of terahertz spectroscopy technology to detect pollutants in the atmosphere have a good development prospect.

Vibrational modes optimization and terahertz time-domain spectroscopy of L-Lysine and L-Lysine hydrate

To date, it is challengeable to clearly identify and accurately characterize molecular vibrational modes of an amino acid and its hydrate. In this work, the terahertz absorption spectra of L-Lysine (Lys) and L-Lysine hydrate (Lys·H2O) have been measured by terahertz time-domain spectroscopy (THz-TDS) at the range of 0.3–2.5 THz under room temperature. The structural changes of Lys and Lys·H2O are sensitively observed by THz spectroscopy. Based on density functional theory (DFT), the vibrational frequencies of Lys and Lys·H2O are analyzed, the Lys single molecule model and the most optimal Lys·H2O single molecule model are established. The collective vibrational modes of Lys and Lys·H2O have been identified by potential energy distribution (PED) analysis and molecular vibrational animation of GaussView. The results demonstrate that the collective vibrational modes of Lys and Lys·H2O at various frequencies are originated from the dihedral torsion or the bond angle bend of different molecular chains in a single molecule, which drives the vibrations of related groups. Therefore, the combination of THz-TDS technology and PED analysis opens up an opportunity for identifying Lys and its hydrate, which provides a theoretical reference for studying vibrational modes of biomolecules.

Quantitative analysis of alum based on Terahertz time-domain spectroscopy technology and Support vector machine

In this paper, the Terahertz time-domain spectroscopy (THz-TDS) technique was used to quantitatively analyze the alum proportion in sweet potato starch. Terahertz time-domain spectra and frequency-domain spectra of pure sweet potato starch and pure alum and their mixtures were obtained. The absorption coefficient spectrum and refractive index spectrum of the samples were calculated. Results show that alum exhibit unique absorption peaks in the terahertz range, and can thus be identified with its absorption fingerprints in the detection from Sweet potato starch. Differences in the refractive index can also be observed between the alum and the sweet potato starch. The Partial Least Squares (PLS) and the Support vector machine (SVM) algorithm were used to establish the mathematical model between the absorption coefficient and the proportion. Results show that the prediction accuracy can reach 99.8% and 99.9%. Comparing the two predictive models, SVM has a better prediction effect. In all, the THz-TDS system plus SVM method is very promising for the further quantitative analysis of alum in sweet potato starch, with the characteristics of being nondestructive and laborsaving compared to other analytical tools.

Terahertz nondestructive imaging for foreign object detection in glass fibre-reinforced polymer composite panels

Terahertz time-domain spectroscopy (THz-TDS) technology, a new powerful nondestructive testing (NDT) method, can provide noninvasive, noncontact, nonionizing radiation to penetrate common nonmetallic materials. In this study, we have employed THz-TDS technology to detect hidden inclusions with various shapes and materials in glass fiber reinforced polymer (GFRP) composite solid panels. Traditional transmission and reflection THz-TDS imaging are performed for detecting inclusions in GFRP solid panels. Next, the spectral difference between defect area and non-defect area has been analyzed, and different parameters for imaging are selected according to defect characteristics, which greatly improves defect detection. The THz-TDS imaging results are compared with those employing X-ray computed tomography (CT) and ultrasonic C-scan, particularly in terms of spatial resolution and overall image quality. It is found that THz-TDS technology can successfully detect hidden inclusions with relatively high image quality, and has an acceptable precision for measuring inclusion size. As such, THz-TDS technology has certain advantages in evaluating the reliability of GFRP composites.

Simulations and time-domain spectroscopy measurements for terahertz radar-cross section

Terahertz time-domain spectroscopy technology has a wide range of applications in security inspection, nondestructive testing, biomedical, etc. But its application to target characteristics has been under debates, because there exist so many differences between terahertz continuous wave and ultra short pulse wave (single pulse width about 1 ps). For investigating the problem of quantitatively measuring the terahertz radar cross section, in this paper, a terahertz time domain spectroscopy scattering measurement system is built based on the technology of terahertz time domain spectroscopy. After system optimization and error minimization of location and system, time domain echoes of targets, such as sphere, disk, cylinder and complex targets, are measured. After the process of fast Fourier transformation and calibration, radar cross sections of the above-mentioned targets in a frequency range of 0.2–1.6 THz are calculated. Furthermore, the surface integral equation method and multilevel fast multipole algorithm are used to simulate the radar-cross section (RCS) results. The measured radar cross section results are compared with the simulations, and their error is less than 3 dB. The error arises mainly from the location and uneven distribution of terahertz wave on quiet zone. Generally, it is acceptable though there is still much work to do. The accuracy of RCS measurement of terahertz time domain is varified. All those are progressing in terahertz time domain spectroscopy technology used in target characteristics. Moreover, the methods of improving dynamic range in high frequency and enlarging quiet zone are the focus of follow-up studies.