Search Results (470)

Conventional terahertz (THz) radio frequency (RF) frontends struggle to simultaneously balance the high performance and miniaturization of monolithic integrated designs with the excellent testability of discrete modular architectures. This paper presents a detachable 183 GHz terahertz RF frontend and completes the module design and system integration of a low-noise amplifier (LNA) and a second-order subharmonic mixer. Through optimization of the waveguide-to-microstrip transition, parasitic compensation for pad bonding, and the structural design of the chip shielding cavity, combined with a high-precision alignment scheme using positioning pins and screws, the integrated module achieves detachability, testability, and ease of maintenance. Measurement results show that across the 160–200 GHz frequency band, the amplifier achieves an average gain of 16.51 dB; the mixer exhibits a minimum conversion loss of 8.62 dB; and the full-link noise figure of the system reaches 6.68 dB. The proposed scheme effectively addresses the engineering challenges of conventional integrated architectures and provides a practical implementation pathway for terahertz communication and remote sensing detection frontends. Full article

Non-Line-Of-Sight (NLOS) Terahertz (THz) radar 3D imaging leverages electromagnetic wave propagation characteristics such as reflection, diffraction, scattering, and penetration to detect, locate, and image hidden targets in occluded environments. It holds significant potential for applications in autonomous driving, disaster rescue, and urban warfare. However, uncertainties introduced by reflecting surfaces and occluding objects in practical NLOS scenarios, such as phase errors, aperture shadowing, and multipath effects, lead to issues like blurred imaging and increased artifacts in radar imaging. To address these challenges, this study proposes a 3D learning imaging method for NLOS THz radar based on a holographic imaging operator, leveraging the adaptive optimization properties of deep unfolding networks and prior environmental perception. First, a 3D imaging model for NLOS THz radar in the Looking Around Corner (LAC) scenario is established. A holographic imaging operator is introduced to enhance imaging efficiency and reduce computational complexity. Second, a high-precision NLOS 3D imaging network is constructed based on the Fast Iterative Shrinkage/Thresholding Algorithm (FISTA) framework. Utilizing features specific to NLOS scenes and designing algorithm parameters as functions of network weights, the method achieves high-precision and high-efficiency in the 3D reconstruction of NLOS targets. Finally, a near-field NLOS radar imaging platform operating at 121 GHz (within the sub-THz regime) is developed. Experimental validations in the LAC scenario are performed on targets, including metal letters “E”, a metal resolution chart, and a pair of scissors. The results demonstrate that the proposed method significantly improves 3D imaging precision, achieving a two-orders-of-magnitude increase in computational speed over traditional imaging algorithms. Full article

Terahertz radiation exhibits significant potential for communications, imaging, and spectroscopy. However, the development of efficient and low-cost THz detectors remains challenging due to limitations such as insufficient sensitivity, slow response speed, and poor room temperature stability. This work presents an innovative quasi-2D perovskite/Weyl semimetal (Co₃Sn₂S₂) heterojunction THz detector that combines complementary material properties via band engineering. The device achieves a remarkable responsivity of 374.15 A/W, a specific detectivity of 6.27 × 10¹¹ cm·Hz^1/2·W⁻¹, and a noise-equivalent power of 0.29 pW·Hz^−1/2 at 0.1 THz. This performance stems from the strong THz absorption of the perovskite layer combined with the high carrier mobility and topological surface states of the Co₃Sn₂S₂, which collectively enable ultrafast carrier extraction and suppressed interfacial recombination. This heterojunction design offers a novel strategy for high-performance terahertz detection and facilitates its integration into next-generation portable, integrated devices. Full article

Background: Terahertz (THz) waves exhibit both photon-like and electron-like properties, showing emerging potential in biomedical applications. Cutaneous squamous cell carcinoma (CSCC) is one of the most common skin tumors. Studies have reported that THz waves can induce apoptosis in cancer cells or ablate tumor tissues. Our previous studies also confirmed that 0.1 THz radiation could significantly promote apoptosis in cutaneous melanoma cells, while it had no apparent effect on fibroblast viability, proliferation, migration, and apoptosis. However, the effects of 0.1 THz radiation on CSCC cells have not yet been explored. Furthermore, there remains a lack of investigation into the structural and functional effects on fibroblasts. Therefore, it is necessary to conduct a systematic study to evaluate the influence of 0.1 THz radiation on both CSCC cells and fibroblasts in order to better understand its potential therapeutic applications in the treatment of skin cancer. Purpose: This study aims to explore the biological effects of 0.1 THz radiation on SCC-7 cells and to uncover the molecular mechanisms underlying THz-induced apoptosis, as well as its potential effect on L-929 cells. Methods: Cell viability was evaluated through the CCK-8 assay, while cell cycle distribution was analyzed with the DNA content detection kit. Wound healing assays were performed to assess cell migration, and Annexin V-FITC staining was used to detect apoptosis. Caspase-3 activity was measured using the caspase-3 activity assay kit. Cell morphology was observed using the Atomic Force Microscope (AFM) and the Transmission Electron Microscopy (TEM). Alterations in membrane potential were detected with the M09 membrane potential probe kit, and intracellular Ca²⁺ levels were quantified using the Fluo-8 AM fluorescent probe. Mitochondrial permeability transition pore (mPTP) opening was assessed with the MPTP detection kit, mitochondrial membrane potential changes were measured using the JC-1 probe kit, and cellular ATP levels were measured with the enhanced ATP assay kit. Subsequently, proteomic analysis was performed. Intracellular reactive oxygen species (ROS) levels were quantified with the ROS detection kit, and cytochrome c (Cyt c) release was quantified using the mouse Cyt c ELISA kit. Apoptosis-inducing factor (AIF) expression was analyzed at both mRNA and protein levels by quantitative real-time PCR (qPCR) and Western blot. AIF expression in CSCC tissues was further evaluated based on the GSE42677 and GSE45164 databases. Finally, cyclosporin A (CsA) was used to inhibit mPTP, and in combination with the iMAC inhibitor, the Aifm1 expression and Cyt c release were examined. Results: Our results showed that THz waves significantly disrupted the membrane integrity of SCC-7 cells and induced mitochondrial structural and functional damage. This resulted in a significant increase in ROS levels and the activation of mPTP and the mitochondrial apoptosis channel (MAC). THz radiation promoted the release of Cyt c and AIF from mitochondria, triggering a noncanonical caspase-3-dependent apoptosis pathway. Notably, L-929 cells did not show significant phenotypic or apoptotic changes under the same irradiation conditions. Bioinformatics analysis of the Gene Expression Omnibus (GEO) database revealed that AIF expression was significantly altered in CSCC tissues compared to normal skin tissues. Conclusions: These findings indicated that 0.1 THz radiation effectively induced apoptosis in SCC-7 cells by triggering mitochondrial dysfunction and ROS generation, which led to the release of AIF. Furthermore, the dysregulation of AIF in CSCC tissues suggested its potential as a promising biomarker. These results provided important molecular insights into the therapeutic potential of THz radiation, particularly for the treatment of cutaneous squamous cell carcinoma. Full article

We propose a terahertz (THz) antenna-coupled wire-channel field-effect transistor—modified EdgeFET (m-EdgeFET), formed by combining single-gate FinFET and dual-side-gate EdgeFET concepts, which is used for THz detection. The proposed hybrid design was implemented on AlGaN/GaN high-electron-mobility transistor (HEMT) structures, demonstrating distinct response characteristics under 150 GHz and 300 GHz radiation at room temperature. The responsivity dependence on the channel length was determined, revealing that the peak responsivity reached up to 6.5 V/W at a gate voltage of −3 V, i.e., at a gate bias that is an order lower in magnitude than that required for EdgeFET to reach the maximum response. Meanwhile, the gate leakage current decreased by an order of magnitude (to about 1 nA) compared to a FinFET with similar geometry. The proposed geometry was shown to operate in two regimes: source-drain coupling (SD) and gate coupling (GG) of THz radiation with the transistor wire channel. The results confirm that the m-EdgeFET design is suitable for electrically controlled and fast THz detection. Full article

Aiming to address the problems of low accuracy in coal–rock identification during coal mining, which lead to energy waste and safety hazards, a high-precision coal–rock medium identification method combining terahertz time-domain spectroscopy technology and multiple machine learning algorithms is proposed. By preparing coal–rock samples with a gradient change in coal content, terahertz time-domain spectroscopy data of coal–rock mixed media are collected, and optical parameters such as the refractive index and absorption coefficient are extracted. Principal component analysis is used to reduce the dimensionality of the terahertz data, and machine learning algorithms such as support vector machine, least squares support vector machine, artificial neural networks, and random forests are adopted for classification and identification. The study found that terahertz waves are more sensitive to coal–rock media in the 0.7–1.3 THz frequency band, and that the refractive index and absorption coefficient of coal–rock mixed media are significantly positively correlated with coal content within the range of 0–30%. After feature extraction and K-fold cross-validation, the random forest model achieved a coal–rock classification accuracy of over 96% on the test set, significantly outperforming other comparison algorithms. The research verifies the efficiency and practicality of terahertz technology combined with multiple machine learning algorithms in coal–rock identification, providing a new method for fields such as mineral separation. This method has, to a certain extent, broken through the accuracy bottleneck of traditional coal–rock identification technologies within its applicable range, providing a new solution for real-time detection of coal–rock interfaces and is expected to further reduce the risks of ineffective mining and roof accidents in the future. Full article

Biochemical detection is fundamental to various scientific disciplines, yet conventional methods still face inherent bottlenecks in achieving rapid, ultrasensitive, and simultaneous multi-target analysis. Terahertz (THz) waves, characterized by their unique spectral fingerprinting capabilities and non-destructive properties, have emerged as a compelling platform for advanced biochemical sensing. This review outlines the evolution of THz biochemical sensing over the past two decades, tracing its progression from passive identification toward intelligent perception. We structure this technological trajectory around four core themes: sensitivity enhancement, specific recognition, multi-target visualization, and system intelligence. We first evaluate the fundamental limitations of direct detection techniques, such as THz time-domain spectroscopy (THz-TDS). Building on this, we examine how metamaterial-assisted architectures utilize high-quality-factor resonances to achieve trace-level detection, pushing the limits of detection (LOD) down to the ng/mL or even pg/mL scale, and how surface chemical functionalization provides a molecular lock mechanism for selective targeting in complex samples. Furthermore, we highlight the paradigm shift from single-point spectral measurements to spatially resolved multi-target imaging using pixelated metasurfaces. Finally, the review addresses emerging directions, including dynamically tunable intelligent metasurfaces, multimodal on-chip integration platforms, and the growing integration of artificial intelligence (AI) in inverse design and data interpretation, which achieves classification accuracies exceeding 95% even in complex matrices. By synthesizing these developments, this review provides a comprehensive perspective on the future trajectory of THz sensing technologies. Full article

Composite materials are critical components in advanced equipment such as aerospace, however, delamination defects that readily arise during manufacturing and in service present serious risks to equipment safety. Terahertz non-destructive testing is highly effective for analyzing the internal structure of composite materials, making it an effective approach for precise identification of delamination defects. Current terahertz detection approaches mainly depend on single domain features, making it difficult to capture complementary information from both the time and frequency domains. To address this, a Time-Frequency Feature-fusion Network (TFFN) is proposed. In this network, a three-branch architecture is employed: local transient patterns and pulse-related structural features are extracted by the local time-frequency branch; damage-sensitive frequency bands are focused on by the frequency-domain branch through a channel-space-frequency band attention mechanism; and deep integration of time-frequency features is achieved by the time-frequency fusion branch using Manifold Mixup. Finally, the features extracted from the three branches are adaptively fused via a cross-branch attention mechanism, and defect identification is accomplished by the classifier. Experimental results show that this method achieves accuracies of 98.40% on the glass fiber reinforced polymer (GFRP) dataset and 98.63% on the quartz fiber reinforced polymer (QFRP) dataset, surpassing the best existing method by 2% and 1.25%, respectively. A substantial improvement in both defect identification accuracy and the model’s generalization ability for layered structures is thereby achieved. Full article

High-precision detection of hazardous gases with low refractive indices ranging from 1.000 to 1.100, specifically including methane, carbon monoxide, and sulfur dioxide, is critical for industrial safety, yet conventional sensors often suffer from limited sensitivity and severe thermal cross-sensitivity. This work presents a Magneto-Optical Differential Photonic Crystals Sensor (MO-DPCS) utilizing indium antimonide (InSb) to address these constraints. Employing the Multi-Objective Dragonfly Algorithm (MODA), the system was inversely optimized to maximize magneto-optical polarization splitting while rigorously maintaining an ultra-high transmission efficiency. Crucially, an angular interrogation architecture operating under oblique incidence was established to maximize the magneto-optical non-reciprocity, where the detection was realized by fixing the terahertz source frequency and monitoring the precise angular displacements of the steep spectral edges. A differential detection technique was employed to utilize the non-reciprocal phase changes wherein Transverse Electric (TE) and Transverse Magnetic (TM) modes display contrasting kinematic characteristics in the presence of an external magnetic field. The findings indicate that with an adjusted magnetic field of 0.033 T, the MO-DPCS attains an exceptional differential sensitivity of 30.8°/RIU, much above the 0.8°/RIU seen in the unmagnetized condition. The differential approach efficiently eliminates common-mode thermal noise, minimizing temperature-induced drift to below 0.35° across a 1 K range. The suggested MO-DPCS offers a robust, self-referencing solution for stable and high-sensitivity gas sensing applications with a detection limit of 4.18 × 10⁻⁴ RIU. Full article

We present an investigation of the thermal damage threshold of passivated Bi₂Se₃ films upon laser illumination, with a focus on their employment in terahertz (THz) spectroscopic applications. Passivation was achieved by depositing a thin 3 nm Al capping layer which, exposed to the ambient, forms a natural oxide. In THz transient emission experiments, the samples were exposed to a train of 100 fs wide laser pulses with 800 nm wavelength at 78 MHz repetition rate and peak power density up to 295 mW/µm². For the sake of comparison, the films were also exposed to continuous wave laser light with a wavelength of 532 nm in the average optical power density range from 5 × 10⁻² mW/µm² to 50 mW/µm². In both cases, changes in film appearance, detected by optical microscopy, or even film removal in a small area close to the center of the illuminated spot could be induced. Raman spectroscopy provided evidence that the crystalline phase of Bi₂Se₃ films is present in areas that have been exposed but not damaged. Conversely, in the film region illuminated with the highest peak power density no Raman signal was detected in the range under investigation which we ascribe to material removal. At the perimeter of this ablated area, we observed a dominant Raman mode at approximately 255 cm⁻¹ that we can attribute to selenium and indicates partial Bi₂Se₃ decomposition. In contrast, we observed Raman spectra corresponding to as-deposited Bi₂Se₃ only a few micrometers away from the laser-damaged area. Hence, the observed THz radiation originates from this illuminated but undamaged region. This detailed knowledge is expected to serve as a guide for designing the emitter’s thermal management and choosing laser parameters for optimal operation. Full article

During the harvesting and storage of wheat, various impurities are often mixed in, which adversely affect the processing quality and food safety of wheat. Therefore, developing an efficient and accurate impurity detection method is of great importance. Terahertz (THz) imaging technology can acquire time-domain spectral transmission images of wheat impurities, providing more features and facilitating detection. However, due to the limitations of THz imaging system hardware and environmental factors, the acquired THz images are often contaminated with noise, resulting in blurred details and indistinct edges, which severely hinder the accurate identification of impurities. To improve the quality of THz images of wheat impurities, this study proposes an Edge-Enhanced and Feature-Fused Image Denoising Network (EEFDNet). The proposed network employs a dual-branch architecture: a denoising branch utilizing dilated convolutions to strengthen feature representation, and an edge enhancement branch designed to emphasize impurity contour information. The outputs of the two branches are integrated through a feature fusion module to effectively remove noise while preserving and enhancing structural details. Experimental results on a self-established THz image dataset of wheat impurities demonstrate that EEFDNet exhibits superior performance, with the PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index) reaching 32.59 dB and 0.9180, respectively, outperforming several mainstream denoising models. Moreover, the proposed method exhibits strong robustness under high-noise conditions. This study provides an effective image preprocessing approach for wheat impurity detection and establishes a solid foundation for subsequent high-precision impurity identification. Full article

Ceramic Matrix Composites (CMC) are widely used in critical applications such as leading edges of aircraft wings and thermal insulation layers of thermal protection systems due to their advantages of being lightweight, high-temperature resistant, and impact-resistant. However, influenced by manufacturing processes and service environments, internal defects such as pores and delamination are prone to occur, significantly compromising the mechanical properties and service reliability of the material. This paper primarily evaluates the feasibility and applicability of using Terahertz Frequency Modulated Continuous Wave (FMCW) technology for the non-contact detection of CMC. First, the measurement principle of FMCW is introduced, and the structure of the detection system, including a two-dimensional mechanical scanning platform, optical lenses, a control platform, and a data acquisition unit, is outlined. Subsequently, scanning imaging was performed on CMC specimens and their bonded thermal protection structure (TPS) specimens, demonstrating the feasibility of Terahertz FMCW technology as an advanced non-destructive testing tool for CMC inspection. The issues of diffraction and the Rayleigh limit inherent in real-aperture terahertz imaging were analyzed and discussed. A multi-scale fusion defect detection method incorporating background estimation is proposed to enable precise delineation of defect regions. Experimental results show that, after processing with the proposed algorithm, the minimum detectable pore diameter at the focal plane is 1 mm, with a regional error of approximately 3%. The detection error for pores and debonding areas in CMC is maintained within 6.44%. Analysis indicates that combining terahertz imaging technology with image processing algorithms enables the quantitative analysis of internal defects in composite materials, offering a new technical approach for defect detection in composite materials. Full article

Video synthetic aperture radar (SAR) enables observation of moving targets by leveraging temporal information across successive frames. In particular, dynamic shadows in video SAR image sequences provide critical cues for detecting moving objects whose energy is smeared or Doppler-shifted. To achieve high-resolution imaging at a high frame rate for effective dynamic scene monitoring, video SAR systems typically operate at extremely high frequencies or even in the terahertz band, rather than the microwave band. However, terahertz video SAR suffers from significant signal attenuation due to atmospheric absorption. We present a deep learning framework to achieve high-frame-rate and high-resolution imaging for microwave video SAR systems. In this framework, the problem of microwave video SAR imaging is formulated as an image super-resolution reconstruction task for low-resolution yet high-frame-rate image sequences from microwave video SAR. We develop a simple yet effective image super-resolution reconstruction network that is completely built upon convolutional neural networks. The designed network takes a low-resolution image sequence and the corresponding high-resolution image with blurred shadows as input, and then produces a high-resolution image sequence where shadows are clearly visible. Furthermore, the network is trained in a self-supervised manner and thus does not require high-resolution image sequences with unblurred shadows as ground truth, which is appealing to practical applications. Processing results of real data from two different video SAR systems have shown good performance of the proposed approach with convincing generalization ability. Full article

Limited by the material response characteristics and structural design, the development of dynamically tunable terahertz absorbers with multi-functional properties remains a major challenge. In this study, a dual-tunable terahertz absorber based on the synergistic integration of strontium titanate (STO) and Dirac semimetal (BDS) is proposed. By utilizing the temperature-sensitive dielectric constant of STO and the electrically tunable conductivity of BDS, the device can realize on-demand switching between a broadband absorption mode (absorptivity >90% in the 1.347~2.1271 THz band) and a dual-narrowband absorption mode under external field excitation. Notably, the centrosymmetric cross-patterned structure on the top layer ensures the polarization insensitivity of the device, and this single structure can also serve as a high-sensitivity temperature sensor. Simulation results verify that the device exhibits stable performance under different incident angles and environmental variations. This study constructs a compact multi-functional device platform integrating dynamic absorption regulation and in situ sensing, which provides a new technical route for the development of intelligent terahertz systems in the fields of terahertz imaging, communication, detection and other related areas. Full article

Terahertz waves are located in the “transition zone” between millimeter waves and infrared light. Terahertz video synthetic aperture radar (THz-ViSAR) utilizes the high operating frequency, strong radar cross-section intensity, and high azimuth repetition frequency of terahertz waves to detect and track ground moving targets. The conventional methods for detecting moving targets do not take into account the imaging characteristics of moving targets in THz-ViSAR. The constant false alarm rate (CFAR) detection method is used together with other methods to detect moving targets, resulting in unsatisfactory detection performance. This article proposes a new detection method for single channel slow-moving targets in THz-ViSAR based on shadows and light spots, which extracts the features of the shadow and spot areas of the moving target, and determines the position and direction of the moving target through the identification of the shadow and spot areas. The progressiveness of this method is verified by simulation and experimental tests. Full article