Search Results (260)

In future 6G systems, integrated sensing and communication (ISAC) in the terahertz (THz) band are emerging as a key technology. Photomixing-based approaches offer advantages for the generation and control of THz waves due to their wide bandwidth and frequency tunability. This paper proposes and experimentally demonstrates a THz-band ISAC system that employs high-speed wavelength tunable lasers. Leveraging the rapid wavelength tunability of the laser, the system simultaneously generates a frequency-modulated continuous-wave (FMCW) radar signal and a frequency-shift keying (FSK) communication signal. Experimental results show successful ranging with a centimeter-level distance measurement error using a 7.9 GHz sweep-bandwidth THz-FMCW signal. The system achieves a short repetition period of 800 ns, significantly enhancing real-time performance in dynamic environments. Moreover, 2FSK communication at 2 Gbit/s was demonstrated without the use of an external modulator, achieving a BER below the HD-FEC threshold. These results confirm that radar and communication functionalities can be integrated into a single transmitter. The proposed system contributes to reducing system complexity and cost and offers a promising solution for 6G applications. Full article

Modern healthcare systems are under growing strain from aging populations, urbanization, and rising chronic disease burdens, creating an urgent need for real-time monitoring and informed decision-making. This survey examines how the convergence of Integrated Sensing and Communication (ISAC) and digital-twin technologies can meet that need by analyzing how ISAC unifies sensing and communication to gather and transmit data with high timeliness and reliability and how digital-twin platforms use these streams to maintain continuously updated virtual replicas of patients, devices, and care environments. Our synthesis compares ISAC frequency options across sub-6 GHz, millimeter-wave, and terahertz bandswith respect to resolution, penetration depth, exposure compliance, maturity, and cost, and it discusses joint waveform design and emerging 6G architectures. It also presents reference architecture patterns that connect heterogeneous clinical sensors to ISAC links, data ingestion, semantic interoperability pipelines using Fast Healthcare Interoperability Resources (FHIR) and IEEE 11073, and digital-twin synchronization, and it catalogs clinical and operational applications, together with validation and integration requirements. We conduct a targeted scoping review of peer-reviewed literature indexed in major scholarly databases between January 2015 and July 2025, with inclusion restricted to English-language, peer-reviewed studies already cited by this survey, and we apply a transparent screening and data extraction procedure to support reproducibility. The survey further reviews clinical opportunities enabled by data-synchronized twins, including personalized therapy planning, proactive early-warning systems, and virtual intervention testing, while outlining the technical, clinical, and organizational hurdles that must be addressed. Finally, we examine workflow adaptation; governance and ethics; provider training; and outcome measurement frameworks such as length of stay, complication rates, and patient satisfaction, and we conclude that by highlighting both the integration challenges and the operational upside, this survey offers a foundation for the development of safe, ethical, and scalable data-driven healthcare models. Full article

The emergence of 6G wireless systems marks a paradigm shift toward intelligent, context-aware networks that can adapt in real-time to their environment. Within this landscape, Sensing-Assisted Communication (SAC) emerges as a key enabler, integrating perception into the communication control loop to enhance reliability, beamforming accuracy, and system responsiveness. Unlike prior surveys that treat SAC as a subfunction of Integrated Sensing and Communication (ISAC), this work offers the first dedicated review of SAC in Millimeter-Wave (mmWave) and Sub-Terahertz (Sub-THz) systems, where directional links and channel variability present core challenges. SAC encompasses a diverse set of methods that enable wireless systems to dynamically adapt to environmental changes and channel conditions in real time. Recent studies demonstrate up to 80% reduction in beam training overhead and significant gains in latency and mobility resilience. Applications include predictive beamforming, blockage mitigation, and low-latency Unmanned Aerial Vehicle (UAV) and vehicular communication. This review unifies the SAC landscape and outlines future directions in standardization, Artificial Intelligence (AI) integration, and cooperative sensing for next-generation wireless networks. Full article

This study presents a theoretical investigation of a terahertz (THz) surface plasmon resonance (SPR) optical biosensor utilizing a graphene-integrated Otto configuration. Through systematic numerical simulations, we demonstrate that actively modulating graphene’s conductivity via an external magnetic field enables tunable SPR behavior with high phase sensitivity. The proposed sensor achieves a phase sensitivity of up to $3.1043\times {10}^5$ deg RIU⁻¹ in liquid sensing and $2.5854\times {10}^4$ deg RIU⁻¹ in gas sensing. This simulation-based work establishes a foundational framework for the development of highly sensitive, magneto-optically tunable optical sensors, highlighting their potential in chemical detection and medical diagnostics. Full article

The structural integrity of poultry eggs is essential for food safety, economic value, and hatchability. External eggshell quality—measured by thickness, strength, cracks, color, and cleanliness—is a key criterion for grading and sorting. Traditional assessment methods, although simple, suffer from subjectivity, low efficiency, and destructive nature. In contrast, recent developments in nondestructive testing (NDT) technologies have enabled precise, automated, and real-time evaluation of eggshell characteristics. This review systematically summarizes state-of-the-art NDT techniques including acoustic resonance, ultrasonic imaging, terahertz spectroscopy, machine vision, and electrical property sensing. Deep learning and sensor fusion methods are highlighted for their superior accuracy in microcrack detection (up to 99.4%) and shell strength prediction. We further discuss emerging challenges such as noise interference, signal variability, and scalability for industrial deployment. The integration of explainable AI, multimodal data acquisition, and edge computing is proposed as a future direction to develop intelligent, scalable, and cost-effective eggshell inspection systems. This comprehensive analysis provides a valuable reference for advancing nondestructive quality control in poultry product supply chains. Full article

Optical biosensors play a crucial role in the field of biological detection by converting biological signals into optical signals for detection. Among them, Surface Plasmon Resonance (SPR) optical biosensors have become a research hotspot in this field due to their significant advantage of high sensitivity. Weyl Semimetals (WSMs), as a type of three-dimensional topological material with unique electronic structures and other properties, exhibit potential applications in the field of SPR sensing. Against this background, we designed a terahertz (THz) high-sensitivity SPR phase biosensor with a KR structure based on WSMs. When applied in gas sensing scenarios, the phase detection sensitivity of this sensor can reach 22,402$°$/RIU, showing a significant improvement compared to traditional SPR biosensors. Moreover, we found that the Weyl node separation distance and twist angle of WSMs have obvious effects on sensitivity regulation. Additionally, we optimized the sensitivity and structural parameters of this structure using a neural network-based deep learning algorithm. We expect that this proposed scheme can provide a feasible reference for the field of biological sensing. Full article

The terahertz (THz) frequency range holds critical importance for next-generation, wireless communications and biomedical sensing applications. However, conventional metamaterial design approaches suffer from computationally intensive simulations and optimization processes that can extend over several months. This work presents an intelligent inverse design framework integrating deep neural network (DNN) surrogate modeling with success-history-based adaptive differential evolution (SHADE) for tunable graphene-based THz metasurfaces. Our DNN surrogate model achieves an exceptional coefficient of determination (R² = 0.9984) while providing a four-order-of-magnitude acceleration compared with conventional electromagnetic solvers. The SHADE-integrated framework demonstrates 96.7% accuracy in inverse design tasks with an average convergence time of 10.2 s. The optimized configurations exhibit significant tunability through graphene Fermi level modulation, as validated by comprehensive electromagnetic field analysis. This framework represents a significant advancement in automated electromagnetic design and establishes a robust foundation for intelligent photonic systems across diverse frequency regimes. Full article

The unique molecular fingerprint spectral characteristics in the terahertz (THz) band provide distinct advantages for non-destructive and rapid biomolecular detection. However, conventional THz metasurface biosensors still face significant challenges in achieving highly sensitive and precise detection. This study proposes a sensing platform based on quasi-bound states in the continuum (Quasi-BIC), which enhances molecular fingerprint recognition through resonance amplification. We designed a symmetric graphene double-split square ring metasurface structure. By modulating the Fermi level of graphene, this system generated continuously tunable Quasi-BIC resonance peaks across a broad THz spectral range, achieving precise spectral overlap with the characteristic absorption lines of lactose (1.19 THz and 1.37 THz) and tyrosine (0.958 THz). The results demonstrated a remarkable 763-fold enhancement in absorption peak intensity through envelope analysis for analytes with 0.1 μm thickness, compared to conventional bare substrate detection. This terahertz BIC metasurface sensor demonstrates high detection sensitivity, holding significant application value in fields such as biomedical diagnosis, food safety, and pharmaceutical testing. Full article

Pesticide residues in fruits and vegetables pose a serious threat to food safety. Traditional detection methods have defects such as complex operation, high cost, and long detection time. Therefore, it is of great significance to develop rapid, non-destructive, and efficient detection technologies and equipment. In recent years, the combination of spectroscopic techniques and imaging technologies with machine learning algorithms has developed rapidly, providing a new attempt to solve this problem. This review focuses on the research progress of the combination of spectroscopic techniques (near-infrared spectroscopy (NIRS), hyperspectral imaging technology (HSI), surface-enhanced Raman scattering (SERS), laser-induced breakdown spectroscopy (LIBS), and imaging techniques (visible light (VIS) imaging, NIRS imaging, HSI technology, terahertz imaging) with machine learning algorithms in the detection of pesticide residues in fruits and vegetables. It also explores the huge challenges faced by the application of spectroscopic and imaging technologies combined with machine learning algorithms in the intelligent perception of pesticide residues in fruits and vegetables: the performance of machine learning models requires further enhancement, the fusion of imaging and spectral data presents technical difficulties, and the commercialization of hardware devices remains underdeveloped. This review has proposed an innovative method that integrates spectral and image data, enhancing the accuracy of pesticide residue detection through the construction of interpretable machine learning algorithms, and providing support for the intelligent sensing and analysis of agricultural and food products. Full article

Terahertz (THz) communications and simultaneous wireless information and power transfer (SWIPT) hold the potential to energize battery-less Internet-of-Things (IoT) devices while enabling multi-gigabit data transmission. However, severe path loss, blockages, and rectifier nonlinearity significantly hinder both throughput and harvested energy. Additionally, high-power THz beams pose safety concerns by potentially exceeding specific absorption rate (SAR) limits. We propose a sensing-adaptive power-focusing (APF) framework in which a reconfigurable intelligent surface (RIS) embeds low-rate THz sensors. Real-time backscatter measurements construct a spatial map used for the joint optimisation of (i) RIS phase configurations, (ii) multi-tone SWIPT waveforms, and (iii) nonlinear power-splitting ratios. A weighted MMSE inner loop maximizes the data rate, while an outer alternating optimisation applies semidefinite relaxation to enforce passive-element constraints and SAR compliance. Full-stack simulations at 0.3 THz with 20 GHz bandwidth and up to 256 RIS elements show that APF (i) improves the rate–energy Pareto frontier by 30–75% over recent adaptive baselines; (ii) achieves a 150% gain in harvested energy and a 440 Mbps peak per-user rate; (iii) reduces energy-efficiency variance by half while maintaining a Jain fairness index of 0.999;; and (iv) caps SAR at 1.6 W/kg, which is 20% below the IEEE C95.1 safety threshold. The algorithm converges in seven iterations and executes within <3 ms on a Cortex-A78 processor, ensuring compliance with real-time 6G control budgets. The proposed architecture supports sustainable THz-powered networks for smart factories, digital-twin logistics, wire-free extended reality (XR), and low-maintenance structural health monitors, combining high-capacity communication, safe wireless power transfer, and carbon-aware operation for future 6G cyber–physical systems. Full article

In this study, a terahertz microfluidic multi-band sensor was designed. Unlike previous microfluidic absorption sensors that rely on dipole resonance, the proposed sensor uses a physical mechanism for absorption by exciting higher-order lattice resonances in microfluidic structures. With a Fabry–Perot cavity, the sensor can form an absorption peak with a high quality factor (Q) and narrow full width at half maximum (FWHM). A high Q value and a narrow FWHM are valuable in the field of sensing and provide strong support for high-precision sensing. On this basis, the sensing performance of the device was investigated. The simulation results clearly show that the absorption sensor has ultra-high sensitivity, which reaches 400 GHz/Refractive Index Unit (RIU). In addition, the sensor generates three absorption peaks, overcoming the limitations of a single frequency band in a composite resonance mode and multidimensional frequency response, which has potential application value in the field of volatile organic compound (VOC) sensing. Full article

In this paper, a novel type of polarization-insensitive terahertz metal metasurface with cross-shaped holes is presented, which is designed based on the theory of bound states in continuous media. The fundamental unit of the metasurface comprises a metal tungsten sheet with a cross-shaped hole structure. A thorough analysis of the optical properties and the quasi-BIC response is conducted using the finite element method. Utilizing the symmetry-breaking theory, the symmetry of the metal metasurface is broken, allowing the excitation of double quasi-BIC resonance modes with a high quality factor and high sensitivity to be achieved. Analysis of the multipole power distribution diagram and the spatial distribution of the electric field at the two quasi-BIC resonances verifies that the two quasi-BIC resonances of the metasurface are excited by electric dipoles and electric quadrupoles, respectively. Further simulation analysis demonstrates that the refractive index sensitivities of the two quasi-BIC modes of the metasurface reach $404.5 \mathrm{G}\mathrm{H}\mathrm{z}/\mathrm{R}\mathrm{I}\mathrm{U}$ and $578.6 \mathrm{G}\mathrm{H}\mathrm{z}/\mathrm{R}\mathrm{I}\mathrm{U}$, respectively. Finally, the functional material PHMB is introduced into the metasurface to achieve highly sensitive sensing and detection of CO₂ gas concentrations. The proposed metallic metasurface structure exhibits significant advantages, including high sensitivity, ease of preparation, and a high Q-value, which renders it highly promising for a broad range of applications in the domains of terahertz biosensing and highly sensitive gas sensing. Full article

Millimeter-wave (mmWave) antennas and antenna arrays have gained significant attention due to their pivotal role in emerging wireless communication, sensing, and imaging technologies. With the rapid deployment of 5G and the transition toward 6G networks, the demand for compact, high-gain, and reconfigurable mmWave antennas has intensified. This article highlights recent advancements in mmWave antenna technologies, including hybrid beamforming using phased arrays, dynamic beam-steering enabled by liquid crystal and MEMS-based structures, and high-capacity MIMO architectures. We also examine the integration of metamaterials and metasurfaces for miniaturization and gain enhancement. Applications covered include wearable antennas with low-SAR textile substrates, conformal antennas for UAV-based mmWave relays, and high-resolution radar arrays for autonomous vehicles. The study further analyzes innovative fabrication methods such as inkjet and aerosol jet printing, micromachining, and laser direct structuring, along with advanced materials like Kapton, PDMS, and graphene. Numerical modeling techniques such as full-wave EM simulation and machine learning-based optimization are discussed alongside experimental validation approaches. Beyond communications, we assess mmWave systems for biomedical imaging, security screening, and industrial sensing. Key challenges addressed include efficiency degradation at high frequencies, interference mitigation in dense environments, and system-level integration. Finally, future directions, including AI-driven design automation, intelligent reconfigurable surfaces, and integration with quantum and terahertz technologies, are outlined. This comprehensive synthesis aims to serve as a valuable reference for advancing next-generation mmWave antenna systems. Full article

Terahertz metamaterial dual-band absorbers are used for multi-target detection and high-sensitivity sensing in complex environments by enhancing information that reflects differences in the measured substances. Traditional design processes are complex and time-consuming. Machine learning-based methods, such as neural networks and deep learning, require a large number of simulations to gather training samples. Existing design methods based on single-objective optimization often result in uneven multi-objective optimization, which restricts practical applications. In this study, we developed a metamaterial absorber featuring a circular split-ring resonator with four gaps nested in a “卍” structure and used the Multi-Objective Firefly Algorithm based on Multiple Cooperative Strategies to achieve fast optimization of the absorber’s structural parameters. A comparison revealed that our approach requires fewer iterations than the Multi-Objective Particle Swarm Optimization and reduces design time by nearly half. The absorber designed using this method exhibited two resonant peaks at 0.607 THz and 0.936 THz, with absorptivity exceeding 99%, indicating near-perfect absorption and quality factors of 31.42 and 30.08, respectively. Additionally, we validated the absorber’s wave-absorbing mechanism by applying impedance-matching theory. Finally, we elucidated the resonance-peak formation mechanism of the absorber based on the surface current and electric-field distribution at the resonance frequencies. These results confirmed that the proposed dual-band metamaterial absorber design is efficient, representing a significant step toward the development of metamaterial devices. Full article

In this work, we propose and analyze a thermally tunable metasurface based on indium antimonide (InSb), designed to operate in the terahertz (THz) frequency range. The metasurface exhibits dual functionalities: single-band perfect absorption and efficient polarization conversion, enabled by the temperature-dependent permittivity of InSb. At approximately 280 K, InSb transitions into a metallic state, enabling the metasurface to achieve near-unity absorptance (100%) at 0.408 THz under normal incidence, independent of polarization. Conversely, when InSb behaves as a dielectric at 200 K, the metasurface operates as an efficient polarization converter. By exploiting structural anisotropy, it achieves a polarization conversion ratio exceeding 85% over the frequency range from 0.56 to 0.93 THz, while maintaining stable performance for incident angles up to 45°. Parametric analyses show that the resonance frequency and absorption intensity can be effectively tuned by varying the InSb square size and the silica (SiO₂) layer thickness, achieving maximum absorptance at a SiO₂ thickness of 16 μm. The proposed tunable metasurface offers significant potential for applications in THz sensing, imaging, filtering, and wavefront engineering. Full article