In this talk, I will give an overview of the unique applications of terahertz waves for communication, chemical identification, material characterization, biomedical sensing and diagnostics and describe the state of the existing terahertz imaging and sensing technologies and their limitations. I will introduce a game changing technology that enables high performance, low cost, and compact terahertz spectroscopy and imaging systems for various applications. More specifically, I will introduce plasmonic terahertz imaging and spectroscopy systems, which offer several orders of magnitude higher signal-to-noise ratio levels compared to the state of the art.

The detection of buried objects with GPR poses a significant challenge in many sectors, including utilities, non-destructive testing, archaeology, military operations and humanitarian efforts. It is a difficult task partly due to the presence of clutter and the strong signal attenuation presented by many soil types. This paper seeks to improve the detection of buried objects using the combination of Synthetic Aperture Radar (SAR) and Polarimetry (PolSAR). In this study a Stepped Frequency Continuous Wave (SFCW) air-coupled radar is used to acquire polarimetric measurements of buried metallic and dielectric objects between the frequency range of 1 - 6.5 GHz. A 3D Synthetic Aperture Radar (SAR) algorithm is developed and following a polarimetric calibration procedure the SAR algorithm is used to create sub-surface images of each polarization channel. Using polarimetric decompositions, the dominant scattering mechanisms are identified and are used to synthesize polarization signatures of the buried objects. Analysis is conducted to determine the optimal polarization state for sub-surface detection, enhancing target identification and discrimination capabilities.

Current methods of production line compatible moisture content detection are too costly to allow for full process monitoring. Other key drawbacks of current methods include sensitivity to changes in sample color, poor sample penetration, and limited moisture content measurement range. Sensors operating in the THz range could provide a solution to these problems and by carefully picking the frequency, a low-cost sensor could be developed. This work covers the development of a low-cost volumetric moisture content sensor based on commercial off-the-shelf hardware, a TI IWR1642 76 GHz automotive radar module, coupled with a sample specific calibration based on effective medium theory. The resulting sensor is orders of magnitude less expensive than competing sensors while providing measurements of volumetric moisture content accurate to within 5% dry-basis moisture content. This work includes a study of two effective medium models, the Bruggeman method and the Looyenga method, and their applicability to the moisture sensing problem as well as a detailed description of the methodology used to build these models and assess their accuracy. These effective medium models utilize known microscopic material properties to describe the macroscopic properties of mixtures. The application space that this study explored was industrial pulp and paper production where precise measurement and fast measurement of volumetric water content is crucial for ensuring product quality and consistency. Using electromagnetic radiation in the THz band to measure the water content of paper is not completely novel but previous approaches have made use of empirical calibration models which require significant time to acquire and can be sensitive to changes in calibration and application environment.

Conventional microwave imaging can provide high-quality reconstructed images, but is also limited by the increased hardware complexity and a slow data acquisition speed. Although computational imaging (CI)-based systems are developed to be alternatives, they may require substantial computational power and time. To reduce the hardware complexity and computational burden associated with scene reconstructions of CI applications, in this paper, a conditional generative adversarial network (cGAN) is presented to achieve image reconstruction, where the back-scattered measurement is regarded as both the condition and the input of the proposed network. With testing dataset, the average values of the normalized mean squared error (NMSE) and the normalized mean absolute error (NMAE) are 0.0474 and 0.2267, respectively. In addition, a noise analysis is conducted, showing the reliability of the proposed network in noisy settings.

Recent developments in the design of the epitaxial structure of an asymmetrical spacer layer tunnel (ASPAT) diode have included a quantum well next to the barrier. This leads to a substantially improved curvature coefficient due to a reduction in the leakage current, introducing yet further advantages over the standard ASPAT diode, which has temperature independence, zero bias operations, and a high dynamic range. This work has developed these diodes into a fully integrated miniature rectenna solution, which integrates an antenna, rectifier, and RC filter. This device targets an operating frequency of 26 GHz, where such a solution could see applications in wireless power transfer, energy harvesting, or signal detection. The current design uses a loop antenna, where the trace has been meandered to increase the electrical length whilst enabling the die size of the device to be reduced to 2x0.8 mm². This size, whilst at mm-scale, enables an efficient antenna to be designed with a simulated gain of 2 dBi. Integrated into this design is a general voltage doubler circuit, consisting of a series capacitor, a shunt diode, and a series diode, with this circuit followed by an RC filter, a shunt capacitor and a resistor, integrated on-chip. The design includes bond pads allowing the device to be packaged in standard QFN packages or onto PCBs for testing. Measurements confirmed that these devices can detect a K-band signal, with a peak reading of 55.2 mV detected at 23.5 GHz.

Conventional microwave imaging-based approaches can produce high quality image reconstructions. At the same time, these techniques typically suffer from increased hardware complexity, cost and slow data acquisition speeds. Although computational imaging (CI)-based systems have been developed as an alternative, they may demand significant computational power and time, especially in the calculation and the storage of the transfer function (or the sensing matrix) of the CI system. However, the previous method considers the scenario where the transmitter and receiver share the same set of aperture distribution fields. To address this challenge, this paper presents a new technique, where the sensing matrix is calculated directly from the aperture fields of the antennas in a CI system. Here, the transmitter and the receiver apertures can be different and they do not necessarily need to have the same field distributions. With the testing dataset, the average value of the normalized mean squared error (NMSE) is 0.0243. In addition, compared to the traditional method, the proposed network reduces the computation time for the sensing matrix by approximately 67%. The proposed network can predict the sensing matrix from two different sets of aperture distribution fields with high accuracy while significantly saving the computation time.

The recently unveiled in-plane photoelectric effect is a quantum phenomenon that opens the doors to a new type of photonic terahertz detectors which utilize quantum transitions within a well-conducting, degenerate 2D electron system (2DES). This effect describes the absorption of photons by electrons at an artificially created, gate-voltage- tunable potential step within the plane of a 2DES, which leads to an electron flow from the high to the low density region of a much higher magnitude than expected from previously known, classical mechanisms. Detectors exploiting this effect were called photoelectric tunable step (PETS) terahertz detectors. The features of the in-plane photoelectric effect are pointed out and compared with the conventional three-dimensional photoelectric effect. The implications of the existence of the in-plane photoelectric effect on the understanding of light-matter interaction within the traditional pictures of classical and quantum physics are discussed. Current trends in the area of PETS detector development are reviewed and opportunities for new photonic terahertz detectors are highlighted, with a focus on practical applications in terahertz technology.

A GaAs/AlGaAs-based photoelectric tunable-step (PETS) terahertz (THz) detector with a symmetric dipole antenna is demonstrated in this work as a model system to carry out a systematic study of the in-plane photoelectric effect. We derive the optimal values for the antenna gap, depth of the 2DEG, and other geometrical parameters from numerical simulations, and fabricate a detector with optimized dimensions. It shows a high responsivity (˜2.5 kV/W) to 1.9-THz radiation with a short response time (˜2 μs). The temperature dependence of the photoresponse of the PETS detector shows a capability of operating up to 75 K. The results of this work deepen the understanding of the in-plane photoelectric effect and provide a universal reference for the design of future high responsivity, fast PETS THz detectors operating at high temperatures.

We introduce a novel method for ultrafast selective multispectral terahertz (THz) spectroscopy, combining broadband THz pulses, Frequency Selective Surfaces (FSS), and a Schottky diode energy sensor. Traditional THz spectroscopy is costly time-consuming and expert-operated. Our system answers to these challenges by not requiring to obtaining the time trace of the electric field of the THz signal thus essentially simplifying the system. Our system efficiently identifies samples by analyzing distinct spectral signatures. Experimental results demonstrate the method's ability to distinguish samples with similar THz absorption coefficients and refractive indices, even without clear fingerprint features. Validation on paper samples with closely matched THz properties confirmed successful differentiation through data averaging and normalization. We also applied k-fold cross-validation with a neural network for multi-class classification, achieving a training accuracy of 94.5% and an average testing accuracy of 94%. This approach offers robust real-time spectroscopic identification and potential for industrial applications and predictive modelling of THz signals.

Terahertz radiation, which lies between the microwave and infrared regions of the electromagnetic spectrum, is being explored as a possible solution to meet the ever-growing demand for high data transfer rates. However, at these frequencies, strong absorption peaks due to water vapour in the air impose strict limitations on wireless communication. Here, we use a detector relying on a nonlinear optical upconversion technique to characterize spectral transmission of specific bands between 0.5 THz and 3 THz under normal atmospheric conditions. We classify these bands into two categories aiming at different applications: short-range secured communication and long-range high data transfer rates.

In this communication, we consider principles of design and assembling of nonparaxial THz imaging systems based on silicon diffractive optics components. The investigation is dedicated to lensless photonic setups comprising high-resistivity silicon-based DOEs such as Fresnel zone plates, Fibonacci lenses, Bessel axicons, and Airy zone plates, all fabricated from a high-resistance 500 μm thick silicon substrate by femtosecond laser ablation. The exploration underlines the significance of structuring both the illumination and light-collection schemes as well as assembly principles of silicon diffractive optical elements in compact THz imaging.

Next-generation communication systems require rapid and efficient control of terahertz (THz) signals to encode data streams. Graphene-based metamaterials emerge as a promising candidate for effective THz modulation as a result of graphene’s large electrically controllable conductivity. However, a significant challenge arises from the inability of graphene to achieve full depletion at the Dirac point, limiting the modulation depth in most LC-resonant metamaterial modulators in transmission. To overcome this limitation, we exploit the destructive interference of Fresnel reflection components. Our study shows single-layer, solid-state graphene-based modulators operating in the terahertz range with several orders of magnitude modulation depth, validated through terahertz time-domain spectroscopy measurements. These findings underscore the potential of graphene-based metamaterials in advancing THz communication technologies.

Due to its ability to meet requirements such as e.g. telemetry, millimeter-wave transceiver technology has gained research interest for various sensor applications, including the automotive and consumer sector. This work presents a resonant metamaterial for millimeter-waves that enables telemetric position sensing. The concept is based on a resonant unit cell that can be tuned to enable position encoding. A 2D metamaterial design was developed to parametrize the resonance frequency via a geometric parameter of the structure. The tuneable range of the metamaterial was estimated using a finite element method (FEM) simulation. This allowed for a bijective mapping of resonance frequency and the geometric parameter, where a linear range for the sensor effect was selected. The resonance frequency shift encodes the absolute position via the geometry parameter of the metamaterial. A linear position encoded bar was fabricated using well-known PCB manufacturing techniques for position determination. The position encoded metamaterial was successfully tested with a vector network analyser under lab conditions. This telemetric position sensor concept offers a compact and contactless readout without mechanical interference with the moving object. The metamaterial is completely passive, resulting in low maintenance and failure issues. The overall sensor concept includes a state-of-the-art radar chip as millimeter-wave transceiver which is currently under development.

We report a THz detector that uses the in-plane photoelectric effect (IPPE) through the integration of a metamaterial with a dual-gated field-effect transistor (FET) array. In this study, we experimentally demonstrate coupling of the IPPE detection mechanism with a metamaterial antenna array, which results in substantial performance enhancement for THz detectors. We design, simulate, and optimise a brickwork array to efficiently confine incident radiation to the 2DEG layer, adapting these arrays to work as THz detectors. Under excitation with quantum cascade laser radiation at a frequency of 1.9 THz, our detector exhibits a photocurrent of 5.8 nA. This achievement surpasses the previously recorded maximum for single-antenna PETS detectors under identical experimental conditions, while simultaneously achieving significantly lower output impedance compared to any previously reported detector utilising the IPPE mechanism. This highly efficient metasurface-based detector with low output impedance holds the potential for developing high-throughput THz communication systems.

Traditional non-destructive test methods utilise acoustic techniques such as ultrasound, while electromagnetic techniques include eddy current and microwave techniques. Radiography and ultrasound are used to perform most volumetric inspections on both metallic and non-metallic materials, even though they may not be best suited for them in some cases. Microwave inspection, by comparison, is a relatively new method although the concepts have been around since the 1950s, microwave, millimetre-wave and THz NDT has had little industrial use mainly being confined to academic labs to date. In this paper we will describe recent advances in mNDT and describe inspection applications which are hopefully gaining traction for commercial use. The presentation will include recent inspections of wind turbine blades and GFRP composites.

The ultra wideband (UWB) antenna is one of the essential part of vital sign detection radar systems. The antenna characteristics of high gain and reduced side lobe level have a contribution to improve the detection capability of the UWB radar. In this work Antipodal Vivaldi antenna backed with frequency-selective surface (FSS) is developed for UWB pulsed radar system in the frequency range of 3.1 to 4.8 GHz. The frequency-selective surface reflector is used to improve the gain of the antenna and reduces the side lobe level of the antenna. Substrate used for Vivaldi antenna and FSS is low cost material, FR-4 with a relative permittivity (ε_r) of 4.3 and a thickness of 1.52 mm. The air gap between the antenna and the FSS and the unit cell number of the FSS were optimized for high gain. The proposed FSS integrated antenna provides a maximum gain of 9.58 dBi. The prototype the antipodal Vivaldi antenna is fabricated and tested and the simulation results are verified using experimental measurements.

The field of THz imaging continues to rapidly develop with ever more variety and sensitivity in both methods of sensing as well as detectors in array imaging formats. Nevertheless, comparatively the techniques developed in the shorter wavelength regions, such as in the IR, are better developed and far exceed in performance compared to the state of the art in THz imaging components. To that end using passive or active devices that can upconvert the THz radiation into the IR band can be advantageous for development of remote sensing applications such as low-IR visibility target detection as well as naturally radiant THz sources. To achieve such a feat the fundamental approach is to design and THz absorber that can emit in the IR so that in turn can be detected. Using a novel metasurface absorber the THz to IR radiation conversion can be optimized to detect incoherent radiation. Here we show how effective such a method is towards detection of incoherent THz radiation.

This paper proposes a novel approach to 3-D microwave imaging using dynamic metasurface antennas in a multistatic configuration. By introducing a panel-to-panel model and a preprocessing technique, raw measurements are converted into the space-frequency domain for efficient data acquisition and reconstruction. Adapting the range migration algorithm in this work enables fast Fourier-based image reconstruction. Simulation results showcase the effectiveness of the proposed method, highlighting its potential for real-world applications.

This paper introduces a 3-D near-field microwave imaging approach, combining a special 2-D multiple-input multiple-output (MIMO) structure with orthogonal coding and Fourier domain processing. The proposed MIMO coded generalized reduced dimension Fourier algorithm effectively reduces data dimensionality while preserving valuable information, streamlining image reconstruction. Through mathematical derivations, we show how the proposed approach includes phase and amplitude compensators and reduces the computational complexity while mitigating propagation loss effects. Numerical simulations confirm the approach’s satisfactory performance in terms of information retrieval and processing speed.