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In this paper, we report our use of a hardware encoder-based synchronization method for a fast terahertz time-domain spectroscopy raster scanner built with the commercially available TeraFlash Smart platform. We describe the principles of our method, including our incorporation of synchronization signals from various devices included in the scanner. We also describe its implementation in a microcontroller with a dedicated counter. By such means, a fast scanning mode was obtained, which was 35 times faster than a traditional step-by-step approach. To validate the proposed synchronization method, we carried out measurements using the USAF 1951 resolution test and a fiberglass plate with a set of intentionally introduced defects. Our results confirmed that the TDS scanner with the developed synchronization method was able to capture high-quality images with resolutions as high as those obtained using traditional step-by-step scanning, but with significantly reduced scanning times.

Alumina ceramics are widely used in the military as a component of ballistic covers due to their high number of mechanical properties such as strength, hardness, and wear resistance. However, alumina exhibits brittle fracture behavior which may lead to the catastrophic failure in construction. Due to that, it needs to be monitored during its lifetime. Thus, the non-destructive testing methods may be very important to ensure the safe and reliable use of these elements through non-invasive, contactless monitoring. In the frame of this work, the potential of Terahertz (THz) transmission measurements is demonstrated, and a selected application using THz systems is presented. The studies were conducted on military-designated ceramic materials at the frequency of 300 GHz. The data were next compared, with the images obtained via X-rays acting as a reference. As the results showed, there is a full agreement between the data obtained with the use of THz radiation and X-rays. This work shows the ability of THz radiation for contactless, non-destructive control of defects in alumina ceramics.

In order to meet the increasing demand of non-destructive testing (NDT) in engineering practice, a continuous terahertz NDT platform based on linear scanning has been developed, with a center frequency of 154 GHz and a bandwidth of 56 GHz. This system combines frequency modulation continuous wave (FMCW) radar technology with a continuous scanning structure, as well as a data acquisition platform to provide a non-contact detection method; this is highly efficient and compensates for the shortcomings of traditional methods such as microwave, X-ray, ultrasonic, and others in safety inspection and special detection. In addition, a signal processing method of spectral refinement and correction is proposed in this paper for accurate thickness measurement. The results show that the method has a high accuracy for ABS, PVC, and ceramic matrix composites. By extracting the characteristic parameters, the detection and imaging of prefabricated defects, such as debonding and bubbles in composite materials, have been successfully achieved. This helps to evaluate the internal state of the inspected object more intuitively and further meets the requirements of industrial NDT.

The increasing scarcity of natural resources, worsening global climate change, environmental degradation, and rising demand for food are forcing the biotechnology and plastics industries to seek and apply circular economy models that would lead to a sustainable transition in the production and use of bioplastics. Circular economy models can improve the economic productivity of bio-based plastics and have a positive impact on the environment by reducing conventional plastic waste and the consumption of petrochemical feedstocks for plastic production. In addition, some agricultural wastes that have the potential to be used as bioplastics can be reused. Terahertz (THz) systems are already used in the plastics and rubber industries for non-destructive testing, detection, imaging, and quality control. Several reports have highlighted the potential applications of THz spectroscopy and imaging in polymer analysis and plastics characterisation. This potential is even greater with chemometric methods and artificial intelligence algorithms. In this review, we focus on applications that support the transformation of the biotechnology sector to the circular economy, particularly via the transition from conventional plastics to bioplastics. In this review, we discuss the potential of THz systems for the characterisation and analysis of bioplastics and biopolymers. The results of previous studies on biopolymers in the THz frequency range are summarised. Furthermore, the potential of using artificial intelligence approaches such as machine learning as advanced analytical methods in THz spectroscopy and imaging, in addition to the conventionally used chemometric methods, is discussed. The results of this review highlight that THz technology can contribute to closed technological circles in important areas of biotechnology and the related plastics and rubber industries.

Retention of rice freshness is highly dependent on storage temperature. Timely and accurate identification of rice freshness is critical to ensure food security. Here, we characterize the freshness of rice in reference to storage temperature. Terahertz reflection imaging is a non-destructive and deeply penetrating technique that can be used for detecting rice freshness. Due to the shortcomings of traditional machine learning, such as limited processing of nonlinear problems and insufficient computing power. Deep learning has the advantages of strong learning ability and high portability. Therefore, for rice freshness identification, the VGG19 network and the Inception-ResNet-v2 network were used in this paper. Moreover, we propose an improved 1D-VGG19-Inception-ResNet-A network. This network possesses the advantages of low time consumption from the 1D-VGG19 network and high classification accuracy from the 1D-Inception-ResNet-V2 network. Compared with the traditional algorithms, the accuracy of the proposed network is significantly improved, with the rice freshness recognition accuracy of 99.80%. The experimental results indicate that terahertz spectral imaging and deep learning algorithms are viable tools for monitoring rice freshness.

To reduce the water footprint in agriculture, the recent push toward precision irrigation management has initiated a sharp rise in photonics-based hydration sensing in plants in a non-contact, non-invasive manner. Here, this aspect of sensing was employed in the terahertz (THz) range for mapping liquid water in the plucked leaves of Bambusa vulgaris and Celtis sinensis. Two complementary techniques, broadband THz time-domain spectroscopic imaging and THz quantum cascade laser-based imaging, were utilized. The resulting hydration maps capture the spatial variations within the leaves as well as the hydration dynamics in various time scales. Although both techniques employed raster scanning to acquire the THz image, the results provide very distinct and different information. Terahertz time-domain spectroscopy provides rich spectral and phase information detailing the dehydration effects on the leaf structure, while THz quantum cascade laser-based laser feedback interferometry gives insight into the fast dynamic variation in dehydration patterns.

In this study, we develop a 3D THz time-of-flight (TOF) imaging technique by using reflective optics to preserve the high-frequency components from a THz antenna. We use an Fe:InGaAs/InAlAs emitter containing relatively high-frequency components. THz-TOF imaging with asynchronous optical sampling (ASOPS) enables the rapid scanning of 100 Hz/scan with a time delay span of 100 ps. We characterize the transverse resolution using knife edge tests for a focal length of 5; the Rayleigh resolution has been measured at 1.0 mm at the focal plane. Conversely, the longitudinal resolution is determined by the temporal pulse width, confirmed with various gap structures enclosed by a quartz substrate. The phase analysis reveals that reflected waves from the top interface exhibit a phase shift when the gap is filled by high-indexed materials such as water but shows in-phase behavior when it is filled with air and low-indexed material. Our imaging tool was effective for inspecting the packaged chip with high lateral and longitudinal resolution. Importantly, the phase information in 2D and 3D images is shown to be a powerful tool in identifying the defect—in particular, delamination in the chip—which tends to be detrimental to the packaged chip’s stability.

For decades, terahertz (THz) microscopic imaging has been limited by the resolution of the system due to the larger wavelength, the power of the source, and the equivalent noise power of the detector, so a lot of research has focused on single-point scanning imaging. With the development of hardware, full-field THz imaging based on high-power continuous-wave THz sources have been developed such as the direct intensity imaging method and lensless coherent imaging. In particular, the THz direct intensity imaging method requires no complicated computational reconstruction, while the high resolution, as a key issue, still needs to be improved. In this paper, the rotating coherent scattering microscopy was applied to THz imaging for the first time. Here, we designed and fabricated a hemisphere lens with high-resistance silicon. The tilted hemisphere lens transformed the incident divergent beam into a plane wave, and the total internal reflection occurred in the planar surface within the hemispherical lens, and generated evanescent waves in the rare medium. At the same time, the sample was placed very close to the plane of the hemispherical lens, so that the sample was illuminated by the evanescent waves. The scattered waves carried high frequency information to the far field, and thus through an objective, the super-resolution imaging was achieved along a single direction. Then, the hemispherical lens was rotated to obtain coherent scattering microscopic images under different evanescent wave illumination angles. Finally, the full-field super-resolution imaging results were obtained through incoherent superposition.

This paper presents the development, performance, integration, and implementation of a 150 GHz FMCW radar based on a homodyne harmonic mixing scheme for noncontact, nondestructive testing. This system offers high-dynamic-range measurement capabilities up to 100 dB and measurement rates up to 7.62 kHz. Such interesting characteristics make this system attractive for imaging applications or contactless sensing. Numerous samples of different materials and geometries were imaged by taking advantage of the radar’s performance. By taking into account the nonionizing capability of the system, new applicative fields such as food industry and pharmaceutical packaging were explored.

Lenses/mirrors with fast data acquisition speeds and extended focal depths have practical importance in terahertz (THz) imaging systems. Thus, a high-speed 600 GHz-band THz imaging scanner system with enhanced focal depth is presented in this work. A polygon mirror with a 250 Hz scanning frequency and an integrated off-axis parabolic (OAP) mirror with an ~170 mm focal depth were employed for 2D imaging. The simulation and experimental results show that a spatial resolution of ~2 mm can be achieved as the imaging distance varies from ~85 to 255 mm. The proposed system was applied to image a hidden metal object as a potential security application, demonstrating that this system can image targets with an enhanced focal depth.

We built a high-speed TDS setup with the use of electronically controlled optical sampling (ECOPS), which can measure up to 1600 terahertz pulses per second. The movement of the sample was provided by two fast-speed motorized linear stages constituting the gantry. We developed a flat-bar-based metal marker approach for the synchronization of continuous line-by-line scans. We carefully compared the performance of the terahertz reflection time-domain spectroscopy (TDS) scanner operating in a slow point-by-point and a one-hundred-times faster line-by-line imaging scheme. We analyzed images obtained for both schemes for a uniform metallic breadboard with holes, as well as a glass composite sample with defects. Although the measurement time was reduced by 100 times in terms of the line-by-line scheme, the overall performance in both schemes was almost identical in terms of the defects’ sizes, shapes and locations. The results proved that the proposed ECOPS TDS system can provide uniform and extremely fast scanning without any deterioration in image quality.

Terahertz (THz) imaging is a powerful technique allowing us to explore non-conducting materials or their arrangements such as envelopes, packaging substances, and clothing materials in a nondestructive way. The direct implementation of THz imaging systems relies, on the one hand, on their convenience of use and compactness, minimized optical alignment, and low power consumption; on the other hand, an important issue remains the system cost and its figure of merit with respect to the image quality and recording parameters. In this paper, we report on the design and performance of an extraordinary low-cost THz imaging system relying on a InP Gunn diode emitter, paraffin wax optics, and commercially available GaAs high-electron-mobility transistors (HEMTs) with a gate length of 200 nm as the sensing elements in a room temperature environment. The design and imaging performance of the system at 94 GHz is presented, and the spatial resolution in the range of the illumination wavelength (∼3 mm) and contrast of nearly two orders of magnitude is determined. The operation of two models of the HEMTs of the same nominal 20 GHz cut-off frequency, but placed in different packages and printed circuit board layouts was evaluated at 94 GHz and 0.307 THz. The presence of two competing contributions—self-resistive mixing and radiation coupling through the antenna effects of the printed circuit boards—to the detected signal is revealed by the signal dependence on the gate-to-source voltage, resulting in a cross-sectional responsivity of 27 V/W and noise-equivalent power of 510 pW/Hz at 94 GHz. Further routes in the development of low-cost THz imaging systems in the range of EUR 100 are considered.

Photodynamic therapy (PDT) is considered a promising noninvasive therapeutic strategy in biomedicine, especially by utilizing low-level laser therapy (LLLT) in visible and near-infrared spectra to trigger biological responses. The major challenge of PDT in applications is the complicated and time-consuming biological methodological measurements in identification of light formulas for different diseases. Here, we demonstrate a rapid and label-free identification method based on artificial intelligence (AI)-assisted terahertz imaging for efficient light formulas in LLLT of acute lung injury (ALI). The gray histogram of terahertz images is developed as the biophysical characteristics to identify the therapeutic effect. Label-free terahertz imaging is sequentially performed using rapid super-resolution imaging reconstruction and automatic identification algorithm based on a voting classifier. The results indicate that the therapeutic effect of LLLT with different light wavelengths and irradiation times for ALI can be identified using this method with a high accuracy of 91.22% in 33 s, which is more than 400 times faster than the biological methodology and more than 200 times faster than the scanning terahertz imaging technology. It may serve as a new tool for the development and application of PDT.

Strong terahertz (THz) emission from the methylammonium lead iodide (MAPbI3) perovskite semiconductors has been observed following above-bandgap photoexcitation, yet local THz responses of crystalline microstructures are absent. We implement laser THz emission microscope (LTEM), yet-to-be applied to the perovskite semiconductors, as a novel and complementary tool to evaluate the electronic and grain heterogeneity of MAPbI3 thin films. Two MAPbI3 samples with different grain sizes are studied. Using this approach, we show that the one with a larger grain size gives more uniform THz radiation. More significant spatial THz intensity fluctuation is observed for the sample with a smaller grain size.

The acquisition speed of terahertz time-domain spectroscopy systems has undergone a significant improvement in recent years. With the development of dual-laser-based sampling techniques such as ASOPS or ECOPS, waveform acquisition rates in the kilohertz range have become feasible. Here, we present measurements of sub-wavelength layers in multilayer systems at a rate of 1.6 kHz, where the individual layer thicknesses are analyzed in real time. For demonstration, we image layers on metallic and non-metallic disks with a 300 mm diameter, acquiring 240,000 pixels in only 2.5 min. By combining a rotation of the samples with a linear translation of the measurement head, we maximize the measurement yield. Owing to a “single-shot” (625 µs) dynamic range of 40 dB and a bandwidth above 3 THz of the ECOPS system, we achieve sub-micron repeatability for each layer.

Synthetic aperture radar (SAR) at the terahertz (THz) spectrum has emerging short-range applications. In comparison to the microwave spectrum, the THz spectrum is limited in propagation range but benefits from high spatial resolution. The THz SAR is of significant interest for several applications which necessitate the mapping of indoor environments to support various endeavors such as rescue missions, map-assisted wireless communications, and household robotics. This paper addresses the augmentation of the high-resolution indoor mapped environment for object recognition, which includes detection, localization, and classification. Indoor object recognition is currently dominated by the usage of optical and infrared (IR) systems. However, it is not widely explored by radar technologies due to the limited spatial resolution at the most commonly used microwave frequencies. However, the THz spectrum provides a new paradigm of possible adaptation of object recognition in the radar domain by providing image quality in good compliance to optical/IR systems. In this paper, a multi-object indoor environment is foremost mapped at the THz spectrum ranging from 325 to 500 GHz in order to investigate the imaging in highly scattered environments and accordingly create a foundation for detection, localization, and classification. Furthermore, the extraction and clustering of features of the mapped environment are conducted for object detection and localization. Finally, the classification of detected objects is addressed with a supervised machine learning-based support vector machine (SVM) model.

Terahertz (THz) imaging is a rapidly growing application motivated by industrial demands including harmless (non-ionizing) security imaging, multilayer paint quality control within the automotive industry, insulating foam non-invasive testing in aerospace, and biomedical diagnostics. One of the key components in the imaging system is the source and detector. This paper gives a brief overview of room temperature THz transceiver technology for imaging applications based on the emerging resonant tunneling diode (RTD) devices. The reported results demonstrate that RTD technology is a very promising candidate to realize compact, low-cost THz imaging systems.

We investigated the transmission characteristics of formalin fixed human liver samples in which normal liver tissue and malignant liver tumor were mixed using terahertz (THz) coherent synchrotron radiation at an infrared free-electron laser (FEL) facility at Nihon University. Infrared-FEL imaging has indicated that the amount of water molecules in the tumor tissue is not different from that in the normal tissue. However, the transmission of the incipient tumor tissue was lower than that of the normal tissue in THz imaging because the tumor tissue contained more water molecular clusters than the normal tissue. The tumor tissue became more permeable owing to the development of fibrous tissue around it. THz imaging will be more useful for discriminating liver tissues by increasing the spatial resolution.

In order to solve the problems of long-term image acquisition time and massive data processing in a terahertz time domain spectroscopy imaging system, a novel fast terahertz imaging model, combined with group sparsity and nonlocal self-similarity (GSNS), is proposed in this paper. In GSNS, the structure similarity and sparsity of image patches in both two-dimensional and three-dimensional space are utilized to obtain high-quality terahertz images. It has the advantages of detail clarity and edge preservation. Furthermore, to overcome the high computational costs of matrix inversion in traditional split Bregman iteration, an acceleration scheme based on conjugate gradient method is proposed to solve the terahertz imaging model more efficiently. Experiments results demonstrate that the proposed approach can lead to better terahertz image reconstruction performance at low sampling rates.

In this study, we developed a rapid nondestructive tool for testing rust spread in a metal covered by a paint layer by using a THz time-domain spectroscopy system at a speed of 100 Hz/pixel. Time-of-flight imaging helps identify rust formation by exclusively obtaining the reflection from the steel below the paint surface. The use of frequency-selective imaging allows us to manipulate the contrast in rust imaging. Higher contrast is generally obtained when monitoring using the higher frequency component. In addition, we monitored the spread of rust in a steel plate under the influence of two different chemical solutions: NaCl and acid. We found that in the early stages, the decrease in THz reflection was governed by the high-frequency components due to the formation of lepidocrocite, whereas the low-frequency component develops as the proportion of hematite increases with time.

Concealed objects detection in terahertz imaging is an urgent need for public security and counter-terrorism. So far, there is no public terahertz imaging dataset for the evaluation of objects detection algorithms. This paper provides a public dataset for evaluating multi-object detection algorithms in active terahertz imaging. Due to high sample similarity and poor imaging quality, object detection on this dataset is much more difficult than on those commonly used public object detection datasets in the computer vision field. Since the traditional hard example mining approach is designed based on the two-stage detector and cannot be directly applied to the one-stage detector, this paper designs an image-based Hard Example Mining (HEM) scheme based on RetinaNet. Several state-of-the-art detectors, including YOLOv3, YOLOv4, FRCN-OHEM, and RetinaNet, are evaluated on this dataset. Experimental results show that the RetinaNet achieves the best mAP and HEM further enhances the performance of the model. The parameters affecting the detection metrics of individual images are summarized and analyzed in the experiments.

Terahertz focal plane array imaging methods, direct camera imaging and conventional light field imaging methods are incapable of resolving and separating layers of multilayer objects. In this paper, for the purpose of fast, high-resolution and layer-resolving imaging of multilayer structures with different reflection characteristics, a novel angular intensity filtering (AIF) method based on terahertz light-field imaging is purposed. The method utilizes the extra dimensional information from the 4D light field and the reflection characteristics of the imaging object, and the method is capable to resolve and reconstruct layers individually. The feasibility of the method is validated by experiment on both “idealized” and “practical” multilayer samples, and the advantages in performance of the method are proven by quantitative comparison with conventional methods.

Despite predictions of the paperless office, global demand for printing and writing paper remains strong, and paper appears to be here to stay for some time. Not only firms, but also governments, libraries, and archives are in possession of large collections of legacy documents that still must be sorted and scanned. In this study, terahertz-based techniques are demonstrated to address several routine tasks related to the automated paper handling of unsorted legacy documents. Specifically, we demonstrate terahertz-based counting of the number of sheets in unconsolidated paper stacks, as well as locating stapled documents buried in paper stacks.

In order to shorten the long-term image acquisition time of the terahertz time domain spectroscopy imaging system while ensuring the imaging quality, a hybrid sparsity model (HSM) is proposed for fast terahertz imaging in this paper, which incorporates both intrinsic sparsity prior and nonlocal self-similarity constraints in a unified statistical model. In HSM, a weighted exponentiation shift-invariant wavelet transform is introduced to enhance the sparsity of the terahertz image. Simultaneously, the nonlocal self-similarity by means of the three-dimensional sparsity in the transform domain is exploited to ensure high-quality terahertz image reconstruction. Finally, a new split Bregman-based iteration algorithm is developed to solve the terahertz imaging model more efficiently. Experiments are presented to verify the effectiveness of the proposed approach.

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeve’s backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed.

Terahertz (THz) imaging has the potential to detect breast tumors during breast-conserving surgery accurately. Over the past decade, many research groups have extensively studied THz imaging and spectroscopy techniques for identifying breast tumors. This manuscript presents the recent development of THz imaging techniques for breast cancer detection. The dielectric properties of breast tissues in the THz range, THz imaging and spectroscopy systems, THz radiation sources, and THz breast imaging studies are discussed. In addition, numerous chemometrics methods applied to improve THz image resolution and data collection processing are summarized. Finally, challenges and future research directions of THz breast imaging are presented.

We report theoretical investigations performed in the terahertz G-band, in the 228–232 GHz spectral window for a piezoelectrically-responsive ring-cone element metasurface composed of polyvinylidene fluoride (PVDF)/Silicon and PVDF/Silica glass. The choosing of this spectral window is motivated by a multitude of applications in terahertz detection and terahertz imaging, that commonly make use of this band. The uniqueness of the envisioned architecture resides in the combination between the readily-available polyvinylidene fluoride polymer and silicon/silica glass substrates, together with the introduction of an extra degree of freedom, in the form of a ring-cone architecture, and the active control of the geometric sizes through the longitudinal piezoelectric effect exhibited by the polymer. The spectral response of the metasurface is dependent on the combination between the polymer elements and the substrate, and ranges from near-zero absorption switching to a resonant behavior and significant absorption. The interaction between the electromagnetic field and the polymer-based metasurface also modifies the phase of the reflected and transmitted waves over a full 2π range, permitting complete control of the electric field polarization. Moreover, we take advantage of the longitudinal piezoelectric effect of PVDF and analyze the spectrum shaping capability of the polymer-based metasurface. Our analysis highlights the capability of the proposed architecture to achieve complete electric field polarization control, near-zero optical switching and resonant behavior, depending on the geometries and sizes of the architecture elements resulting from construction considerations and from the externally applied voltages through the piezoelectric effect.

In this study, we developed a rapid three-dimensional (3D) time-of-flight imaging tool for inspection of packaged semiconductor chips, using terahertz (THz) time-domain spectroscopy techniques. A high-speed THz system based on the optical sampling by cavity tuning technique is incorporated with a 2-axis galvano scanner to deliver a scanning speed of more than 100 Hz/pixel with a signal-to-noise ratio larger than 20 dB. Through the use of the Hilbert transformation, we reconstruct the 3D structure of the packaged chip in a nondestructive manner. Additionally, the use of frequency-selective imaging allows us to manipulate image resolution; the higher resolution was obtained when monitored using the higher frequency component. Further, using phase information, we were able to detect and identify defects in the packaged chip, such as the delamination area and epoxy-rich regions.

In this paper, we propose a terahertz (THz) spiral spatial filtering (SSF) imaging method that can enable image contrast enhancement. The related theory includes three main steps: (1) the THz image of the target is Fourier transformed to the spatial spectrum distribution; (2) the spatial spectrum is modulated by a spiral phase at the Fourier plane; (3) the filtered spatial spectrum is inverse Fourier transformed to the desired THz image. Meanwhile, analytic expression of the final THz image is derived. Due to the unique nature of the spiral phase, THz image contrast enhancement can be achieved and verified by various simulated target images with different contrasts. In our designed THz SSF imaging system, Fourier transform is carried out by the lens, and the spiral phase is acquired by the spiral phase plate (SPP). Proof-of-principle experiments with three different types of targets (carved metal letters, a high-density polyethylene (HDPE) piece with a scratch, and a leaf) were carried out, and the effectiveness of contrast enhancement and edge extraction on the THz reconstruction images was validated.

Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in plants, it poses great challenges for practical identification. This study proposed a state-of-the-art method for the rapid identification of trace (10 mg·L−1) and multiple similar benzimidazole pesticide residues on the surface of Toona sinensis leaves, mainly including benzoyl (BNL), carbendazim (BCM), thiabendazole (TBZ), and their mixtures. The new method combines high-throughput terahertz (THz) imaging technology with a deep learning framework. To further improve the model reliability beyond the THz fingerprint peaks (BNL: 0.70, 1.07, 2.20 THz; BCM: 1.16, 1.35, 2.32 THz; TBZ: 0.92, 1.24, 1.66, 1.95, 2.58 THz), we extracted the absorption spectra in frequencies of 0.2–2.2 THz from images as the input to the deep convolution neural network (DCNN). Compared with fuzzy Sammon clustering and four back-propagation neural network (BPNN) models (TrainCGB, TrainCGF, TrainCGP, and TrainRP), DCNN achieved the highest prediction accuracies of 100%, 94.51%, 96.26%, 94.64%, 98.81%, 94.90%, 96.17%, and 96.99% for the control check group, BNL, BCM, TBZ, BNL + BCM, BNL + TBZ, BCM + TBZ, and BNL + BCM + TBZ, respectively. Taking advantage of THz imaging and DCNN, the image visualization of pesticide distribution and residue types on leaves was realized simultaneously. The results demonstrated that THz imaging and deep learning can be potentially adopted for rapid-sensing detection of trace multi-residues on leaf surfaces, which is of great significance for agriculture and food safety.

Terahertz (THz) imaging technology has received increased attention in recent years and has been widely applied, whereas the three-dimensional (3D) imaging for moving targets remains to be solved. In this paper, an adaptive 3D imaging scheme is proposed based on a single input and multi-output (SIMO) interferometric inverse synthetic aperture radar (InISAR) imaging system to achieve 3D images of moving targets in THz band. With a specially designed SIMO antenna array, the angular information of the targets can be determined using the phase response difference in different receiving channels, which then enables accurate tracking by adaptively adjusting the antenna beam direction. On the basis of stable tracking, the high-resolution imaging can be achieved. A combined motion compensation method is proposed to produce well-focused and coherent inverse synthetic aperture radar (ISAR) images from different channels, based on which the interferometric imaging is performed, thus forming the 3D imaging results. Lastly, proof-of-principle experiments were performed with a 0.2 THz SIMO imaging system, verifying the effectiveness of the proposed scheme. Non-cooperative moving targets were accurately tracked and the 3D images obtained clearly identify the targets. Moreover, the dynamic imaging results of the moving targets were achieved. The promising results demonstrate the superiority of the proposed scheme over the existing THz imaging systems in realizing 3D imaging for moving targets. The proposed scheme shows great potential in detecting and monitoring moving targets with non-cooperative movement, including unmanned military vehicles and space debris.

Terahertz imaging and time-domain spectroscopy have been widely used to characterize the properties of test samples in various biomedical and engineering fields. Many of these tasks require the analysis of acquired terahertz signals to extract embedded information, which can be achieved using machine learning. Recently, machine learning techniques have developed rapidly, and many new learning models and learning algorithms have been investigated. Therefore, combined with state-of-the-art machine learning techniques, terahertz applications can be performed with high performance that cannot be achieved using modeling techniques that precede the machine learning era. In this review, we introduce the concept of machine learning and basic machine learning techniques and examine the methods for performance evaluation. We then summarize representative examples of terahertz imaging and time-domain spectroscopy that are conducted using machine learning.

This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed.

In the past few decades, the applications of terahertz (THz) spectroscopy and imaging technology have seen significant developments in the fields of biology, medical diagnosis, food safety, and nondestructive testing. Label-free diagnosis of malignant tumours has been obtained and also achieved significant development in THz biomedical imaging. This review mainly presents the research status and prospects of several common continuous-wave (CW) THz medical imaging systems and applications of THz medical imaging in biological tissues. Here, we first introduce the properties of THz waves and how these properties play a role in biomedical imaging. Then, we analyse both the advantages and disadvantages of the CW THz imaging methods and the progress of these methods in THz biomedical imaging in recent ten years. Finally, we summarise the obstacles in the way of the application of THz bio-imaging application technology in clinical detection, which need to be investigated and overcome in the future.

The demand for internal nondestructive testing and inspection techniques is rapidly increasing. Using a continuous wave (CW) terahertz (THz) imaging system, we demonstrate that the internal defects in cross-linked polyethylene (XLPE) plates for power cable insulation can be detected. In a coherent detection scheme based on photomixers, which serve as the THz emitters and receivers, the change of phase occurring with the defects inside the XLPE plates is distinctly measured by the change in the amplitude of the transmitted THz waves. According to the two-dimensional images of THz waves transmitted through the XLPE plates, defects of up to 0.5 mm size located inside the XLPE plates can be detected by the internal nondestructive examination method based on CW−THz waves. This technique will be useful for internal nondestructive testing and inspection of insulation materials that require high resolution in various industries, including the automobiles, electronics, and electrical power industries.

Food quality monitoring, particularly foreign object detection, has recently become a critical issue for the food industry. In contrast to X-ray imaging, terahertz imaging can provide a safe and ionizing-radiation-free nondestructive inspection method for foreign object sensing. In this work, a quasi-Bessel beam (QBB) known to be nondiffracting was generated by a conical dielectric lens to detect foreign objects in food samples. Using numerical evaluation via the finite-difference time-domain (FDTD) method, the beam profiles of a QBB were evaluated and compared with the results obtained via analytical calculation and experimental characterization (knife edge method, point scanning method). The FDTD method enables a more precise estimation of the beam profile. Foreign objects in food samples, namely crickets, were then detected with the QBB, which had a deep focus and a high spatial resolution at 210 GHz. Transmitted images using a Gaussian beam obtained with a conventional lens were compared in the sub-terahertz frequency experimentally with those using a QBB generated using an axicon.

InGaAs-based bow-tie diodes for the terahertz (THz) range are found to be well suited for development of compact THz imaging systems. To further optimize design for sensitive and broadband THz detection, one of the major challenges remains: to understand the noise origin, influence of growth conditions and role of defects for device operation. We present a detailed study of photoreflectance, low-frequency noise characteristics and THz sensitivity of InGaAs bow-tie diodes. The diodes are fabricated from InGaAs wafers grown by molecular beam epitaxy (MBE) on semi-insulating InP substrate under different technological conditions. Photoreflectance spectra indicated the presence of strong built-in electric fields reaching up to 49 kV/cm. It was demonstrated that the spectral density of voltage fluctuations at room temperature was found to be proportional to 1/f, while at lower temperatures, 77⁻200 K, Lorentzian-type spectra dominate due to random telegraph signals caused by individual capture defects. Furthermore, varying bias voltage, we considered optimal conditions for device room temperature operation in the THz range with respect to signal-to-noise ratio. The THz detectors grown with beam equivalent pressure In/Ga ratio equal to 2.04 exhibit the minimal level of the low-frequency noise, while InGaAs layers grown with beam equivalent pressure In/Ga ratio equal to 2.06 are found to be well suited for fabrication of room temperature bow-tie THz detectors enabling sensitivity of 13 V/W and noise equivalent power (NEP) of 200 pW/√Hz at 0.6 THz due to strong built-in electric field effects.

There is a need for fast and reliable quality and authenticity control tools of pharmaceutical ingredients. Among others, hormone containing drugs and foods are subject to scrutiny. In this study, terahertz (THz) spectroscopy and THz imaging are applied for the first time to analyze melatonin and its pharmaceutical product Circadin. Melatonin is a hormone found naturally in the human body, which is responsible for the regulation of sleep-wake cycles. In the THz frequency region between 1.5 THz and 4.5 THz, characteristic melatonin spectral features at 3.21 THz, and a weaker one at 4.20 THz, are observed allowing for a quantitative analysis within the final products. Spectroscopic THz imaging of different concentrations of Circadin and melatonin as an active pharmaceutical ingredient in prepared pellets is also performed, which permits spatial recognition of these different substances. These results indicate that THz spectroscopy and imaging can be an indispensable tool, complementing Raman and Fourier transform infrared spectroscopies, in order to provide quality control of dietary supplements and other pharmaceutical products.

This paper presents the design, implementation and characterization results of a pixel-level readout chain integrated with a FET-based terahertz (THz) detector for imaging applications. The readout chain is fabricated in a standard 150-nm CMOS technology and contains a cascade of a preamplification and noise reduction stage based on a parametric chopper amplifier and a direct analog-to-digital conversion by means of an incremental ΣΔ converter, performing a lock-in operation with modulated sources. The FET detector is integrated with an on-chip antenna operating in the frequency range of 325–375 GHz and compliant with all process design rules. The cascade of the FET THz detector and readout chain is evaluated in terms of responsivity and Noise Equivalent Power (NEP) measurements. The measured readout input-referred noise of 1.6 μ V r m s allows preserving the FET detector sensitivity by achieving a minimum NEP of 376 pW/ Hz in the optimum bias condition, while directly providing a digital output. The integrated readout chain features 65-dB peak-SNR and 80-μ W power consumption from a 1.8-V supply. The area of the antenna-coupled FET detector and the readout chain fits a pixel pitch of 455 μm, which is suitable for pixel array implementation. The proposed THz pixel has been successfully applied for imaging of concealed objects in a paper envelope under continuous-wave illumination.

Liquid crystal (LC) is a promising candidate for terahertz (THz) devices. Recently, LC has been introduced to generate THz vortex beams. However, the efficiency is intensely dependent on the incident wavelength, and the transformed THz vortex beam is usually mixed with the residual component. Thus, a separating process is indispensable. Here, we introduce a gradient blazed phase, and propose a THz LC forked polarization grating that can simultaneously generate and separate pure THz vortices with opposite circular polarization. The specific LC gradient-rotation directors are implemented by a photoalignment technique. The generated THz vortex beams are characterized with a THz imaging system, verifying features of polarization controllability. This work may pave a practical road towards generating, separating and polarizing THz vortex beams, and may prompt applications in THz communications, sensing and imaging.

For fast and standoff personal screening, a novel terahertz imaging scheme using a sparse rotating array is developed in this paper. A linearly sparse array is designed to move along a circular path with respect to an axis perpendicular to the imaging scenario. For this new scheme, a modified imaging algorithm is proposed based on the frequency-domain reconstruction method in circular synthetic aperture radar. To achieve better imaging performance, an optimization method of the sparse array is also proposed, according to the distribution of the spectral support. Theoretical and numerical analysis of the point spread function (PSF) is provided to demonstrate the high-resolution imaging ability of the proposed scheme. Comprehensive simulations are carried out to validate the feasibility and effectiveness of the array optimization method. Finally, the imaging results of a human-scattering model are also obtained to further demonstrate the good performance of this new imaging scheme and the effectiveness of the array optimization approach. This work can facilitate the design and practice of terahertz imaging systems for security inspection.

Polymer matrix composites (PMC) play important roles in modern industry. Increasing the number of such structures in aerospace, construction, and automotive applications enforces continuous monitoring of their condition. Nondestructive inspection of layered composite materials is much more complicated process than evaluation of homogenous, (mostly metallic) structures. Several nondestructive methods are utilized in this case (ultrasonics, shearography, tap testing, acoustic emission, digital radiography, infrared imaging) but none of them gives full description of evaluated structures. Thus, further development of NDT techniques should be studied. A pulsed terahertz method seems to be a good candidate for layered PMC inspection. It is based on picosecond electromagnetic pulses interacting with the evaluated structure. Differences of dielectric parameters enables detection of a particular layer in a layered material. In the case of multilayered structures, only layers close to surface can be detected. The response of deeper ones is averaged because of multiple reflections. In this paper a novel inspection procedure with a data processing algorithm is introduced. It is based on a double-sided measurement, acquired signal deconvolution, and data combining. In order to verify the application of the algorithm stress-subjected glass fiber-reinforced polymer (GFRP) was evaluated. The obtained results enabled detection and detailed analysis of delaminations introduced by stress treatment and proved the applicability of the proposed algorithm.

An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime.

We propose a self-consistent method for the analysis of granular materials at terahertz (THz) frequencies using a quantum cascade laser. The method is designed for signals acquired from a laser feedback interferometer, and applied to non-contact reflection-mode sensing. Our technique is demonstrated using three plastic explosives, achieving good agreement with reference measurements obtained by THz time-domain spectroscopy in transmission geometry. The technique described in this study is readily scalable: replacing a single laser with a small laser array, with individual lasers operating at different frequencies will enable unambiguous identification of select materials. This paves the way towards non-contact, reflection-mode analysis and identification of granular materials at THz frequencies using quantum cascade lasers.

This paper presents the first low noise complementary metal oxide semiconductor (CMOS) terahertz (THz) imager based on source modulation and in-pixel high-Q filtering. The 31 × 31 focal plane array has been fully integrated in a 0 . 13 μ m standard CMOS process. The sensitivity has been improved significantly by modulating the active THz source that lights the scene and performing on-chip high-Q filtering. Each pixel encompass a broadband bow tie antenna coupled to an N-type metal-oxide-semiconductor (NMOS) detector that shifts the THz radiation, a low noise adjustable gain amplifier and a high-Q filter centered at the modulation frequency. The filter is based on a passive switched-capacitor (SC) N-path filter combined with a continuous-time broad-band Gm-C filter. A simplified analysis that helps in designing and tuning the passive SC N-path filter is provided. The characterization of the readout chain shows that a Q factor of 100 has been achieved for the filter with a good matching between the analytical calculation and the measurement results. An input-referred noise of 0 . 2 μ V RMS has been measured. Characterization of the chip with different THz wavelengths confirms the broadband feature of the antenna and shows that this THz imager reaches a total noise equivalent power of 0 . 6 nW at 270 GHz and 0 . 8 nW at 600 GHz.