Search Results (125)

When driving a partially automated vehicle, maintaining situation awareness is essential for users to be better prepared to take over. A primary challenge is maintaining awareness while the user is occupied with another task without tunneling attention towards individual elements. To investigate this, we conducted an experimental study in our driving simulator (n = 20) comparing an indirect LED (light-emitting diode) visualization of relevant objects in the driver’s field of view with a combined condition of an indirect LED + direct HUD (head-up display) visualization. The participants’ situation awareness scores were higher under the combined condition. However, the scores dropped significantly for objects outside the LED + HUD visualization. We conclude that the indirect object indication is not effective in countering tunneling effects from the HUD, and neither does it provide a satisfactory trade-off when deployed on its own, i.e., without direct indication in addition. Full article

Autonomous driving in underground mines faces significant challenges due to Global Navigation Satellite System (GNSS) denial and harsh environmental conditions. Mainstream multi-sensor fusion and Simultaneous Localization and Mapping (SLAM) schemes have achieved substantial progress in underground navigation, but their deployment in feature-sparse tunnels may still face challenges related to computational burden and perception robustness. This study explores an infrastructure-assisted navigation architecture that transforms the roadway into a structured luminous guidance channel by deploying programmable Light Emitting Diode (LED) strips along the tunnel roof. The proposed system simplifies complex three-dimensional pose estimation into a two-dimensional visual servoing task targeting optical signals. Central to this approach is a robust data fusion strategy that utilizes a topology matching algorithm to map noisy Ultra-Wide-band (UWB) coordinates onto a discrete LED index space, thereby providing a reliable global positioning reference. Furthermore, a hierarchical fault-tolerant controller based on a Finite State Machine (FSM) is designed to facilitate seamless degradation to a UWB-assisted ultrasonic wall-following mode in the event of visual degradation, supporting fault-tolerant operation under controlled laboratory conditions. Experimental results in a laboratory simulation environment demonstrate that the system achieves millimeter-level static initialization accuracy, a dynamic tracking Root Mean Square Error of approximately 4 cm, and a 100% autonomous recovery rate from visual failures in straight tunnels. These results demonstrate the feasibility of the proposed infrastructure-assisted route under controlled laboratory conditions and suggest its potential as an engineering reference for structured underground transport scenarios with acceptable infrastructure modification. Full article

Despite the success of artificial neural networks in solving numerous tasks, they face significant challenges, including difficulties in online adaptation and rapidly increasing energy consumption. As a biologically plausible alternative, spiking neural networks offer promising capabilities for efficient cognitive computing. Recently, a three-element spiking neuron model consisting of a threshold selector, a tunnel diode, and a capacitor was proposed. In this work, we experimentally validate this model using a threshold selector hardware emulator and demonstrate its dynamical equivalence to the biologically plausible Izhikevich neuron model. To evaluate the novel neuron’s applicability for cognitive computing, we implement a liquid state machine (LSM) reservoir architecture with spatially dependent random topology for synaptic weight distribution. Our simulations on the MNIST and Fashion-MNIST benchmarks demonstrate competitive classification accuracy (97.9% and 89.5%, respectively) while offering estimated energy efficiency and processing speed enhancements compared to existing FPGA-based and memristor-based spiking reservoir implementations. The developed reservoir is feasible for processing neuromorphic sensors output, including visual perception tasks. Full article

Dark current represents a fundamental limiting factor in photodiode performance, establishing the noise floor and constraining detectivity in low-light applications. This comprehensive literature review examines publications covering the physical mechanisms underlying dark current generation and diverse techniques employed for its reduction. Covered mechanisms include diffusion current, Shockley–Read–Hall (SRH) generation–recombination, trap-assisted tunneling, band-to-band tunneling, and surface leakage, each examined with respect to its physical origin and characteristic signatures. Reduction strategies are categorized into thermal management approaches, surface passivation techniques including atomic-layer-deposited aluminum oxide (ALD Al₂O₃), guard ring architectures (attached, floating, and combined configurations), gettering and defect engineering methods, doping profile optimization, bias voltage management, and advanced device architectures such as pinned photodiodes and black silicon structures. A classification table organizes all the reviewed literature by material system, reduction technique, and key findings. Special emphasis is placed on silicon, germanium, III–V compounds, and emerging material photodiodes relevant to near-infrared detection, CMOS imaging, single-photon avalanche diodes (SPADs), and Time-of-Flight (ToF) applications. Full article

This study focuses on the zonotope-based set-membership estimation issue for switched Takagi–Sugeno (T-S) fuzzy systems with application to tunnel diode circuits. Given the practical importance of tunnel diodes in radio-frequency, microwave, and high-speed electronic systems, we first model the tunnel diode circuit as a switched T-S fuzzy system to characterize its inherent dynamics. To address the state estimation issue, we propose a zonotopic set-membership estimation framework for the system under mode-dependent average dwell-time (MDADT) switching, which enables tighter state bounding while ensuring $H_{\infty }$ robustness. A mode-dependent observer is designed to attenuate the effects of external disturbances and measurement noise, and the stability of the estimation error system is analyzed based on an appropriate Lyapunov function. Numerical simulations are conducted and the corresponding results show that the estimated boundary can accurately encompass the true state of the system, and the volume of the estimated set is reduced by approximately 28.99% compared with the interval observer method, thus demonstrating the effectiveness and potential of the proposed approach. Full article

RTD photodetectors have been widely applied in fields such as gas detection, weak signal detection, and single-photon detection. However, during further device design and optimization, it has been found that existing theoretical models cannot fully capture the diverse practical behaviors of RTD photodetectors. In this work, we analyze the influence of optical illumination on the band structure of RTDs and, based on the model proposed by Schulman et al., develop a relatively comprehensive theoretical model for RTD photodetectors. By comparing the model predictions with experimental data reported in the literature, we demonstrate that the proposed model can accurately describe the various physical effects in RTD photodetectors and faithfully reproduce the actual evolution of the I-V characteristics. This model provides a solid foundation for the design and optimization of RTD photodetector devices. Full article

Advanced solar energy-harvesting devices, such as optical rectennas, typically use metal–insulator–metal diodes because of the ultrafast response of these diodes at high frequencies. However, the diode performance is limited by weak current–voltage (I–V) asymmetry and optical losses in metallic electrodes. Graphene offers a promising alternative electrode material owing to its high carrier mobility, broadband optical transparency, and compatibility with nanoscale device architectures. Nevertheless, graphene-based optical rectennas face challenges associated with insufficient diode nonlinearity. In this study, we developed a vertically stacked graphene–double-insulator–graphene (GI²G) tunnel diode. Devices with various junction sizes were fabricated to investigate size-dependent rectifying behavior. A reduced graphene overlap area was defined by electron-beam lithography to introduce asymmetry and increase nonlinear conduction. An Al₂O₃/SiO₂ tunnel barrier composed of dielectrics with different band gaps and electron affinities improved the asymmetric I–V characteristics. Photoresponse measurements under AM1.5G illumination revealed a clear photocurrent, indicating rectification-related photoresponse. The photoresponse increased with decreasing junction area, which is consistent with enhanced rectification performance in smaller junctions. These results demonstrate that the GI²G tunnel diode provides a promising platform for next-generation energy harvesting and optical sensing applications. Full article

In this paper, we theoretically investigate nonlinearly tunable Fano resonance by employing a light tunneling heterostructure with one-dimensional defective photonic crystals and a lossy metallic film. We find that the phenomenon of Fano resonance can be created by coupling the Fabry–Pérot cavity mode with the topological optical Tamm state. We emphasize that the local field confinement induced by Fano resonance can ensure that the large nonlinear permittivity of metal can be utilized sufficiently. We show that the Fano-type transmission spectrum can be actively modulated by altering the input power intensity of light. We also illustrate that the hysteresis effects and nonreciprocal transmission behaviors can be obtained directly by using the Fano resonant heterostructure, allowing for the realization of high-performance all-optical switches and diodes. Our findings may open up new prospects for the nonlinear topological photonic systems with classical analogue–quantum phenomena. Full article

Multiband solar cells offer a promising route to surpass the Shockley-Queisser limit by harnessing sub-bandgap photons through three active energy band transitions. However, realizing their full potential requires overcoming key challenges in material design and device architecture. Here, we propose a novel multiband stacked anti-parallel junction solar cell structure based on highly mismatched alloys (HMAs), in particular dilute GaAsN with ~1–4% N. An anti-parallel junction consists of two semiconductor junctions connected with opposite polarity, enabling bidirectional current control. The structures of the proposed devices are based on dilute GaAsN with anti-parallel junctions, which allow the elimination of tunneling junctions—a critical yet complex component in conventional multijunction solar cells. Semiconductors with three active energy bands have demonstrated the unique properties of carrier transport through the stacked anti-parallel junctions via tunnel currents. By leveraging highly mismatched alloys with tailored electronic properties, our design enables bidirectional carrier generation through forward- and reverse-biased diodes in series, significantly enhancing photocurrent extraction. Through detailed SCAPS-1D simulations, we demonstrate that strategically placed blocking layers prevent carrier recombination at contacts while preserving the three regions of photon absorption in a single multiband semiconductor p/n junction. Remarkably, our optimized five-stacked anti-parallel junctions structure achieves a maximum theoretical conversion efficiency of 70% under 100 suns illumination, rivaling the performance of state-of-the-art six-junctions III-V solar cells—but without the fabrication complexity of multijunction solar cells associated with tunnel junctions. This work establishes that highly mismatched alloys are a viable platform for high efficiency solar cells with simplified structures. Full article

A Si/SiC heterojunction double-trench MOSFET with improved conduction characteristics is proposed. By replacing the N+ source and P-ch regions with silicon, the device forms a Si/SiC heterojunction that exhibits Schottky-like characteristics, effectively deactivating the parasitic PiN body diode and improving third-quadrant performance. A high-k gate dielectric is incorporated to induce a strong electron accumulation layer at the heterointerface, thinning the energy barrier and enabling tunneling-dominated current transport, thereby significantly enhancing the first-quadrant performance. TCAD simulation results demonstrate that the proposed device achieves a specific on-resistance (R_on,sp) of 1.78 mΩ·cm², representing a 20.5% reduction compared to the conventional SiC DTMOS, while maintaining a comparable breakdown voltage (BV) of approximately 1380 V. A significant reduction in the third-quadrant turn-on voltage (V_on) is achieved with the proposed structure, from 2.74 V to 1.53 V. Meanwhile, the unipolar conduction mechanism similar to that of Schottky effectively suppresses bipolar degradation. To enhance device reliability, the design incorporates a trenched source and heavily doped P-well, which collectively mitigate high electric field concentrations at the trench corners. The proposed device offers an integration strategy enhancing both forward conduction and reverse conduction in high-voltage power electronics. Full article

As artificial intelligence continues to push into real-time, edge-based and resource-constrained environments, there is an urgent need for novel, hardware-efficient computational models. In this study, we present and validate a neuromorphic computing architecture based on resonant-tunnelling diodes (RTDs), which exhibit the nonlinear characteristics ideal for physical reservoir computing (RC). We theoretically formulate and numerically implement an RTD-based RC system and demonstrate its effectiveness on two image recognition benchmarks: handwritten digit classification and object recognition using the Fruit-360 dataset. Our results show that this circuit-level architecture delivers promising performance while adhering to the principles of next-generation RC, eliminating random connectivity in favour of a deterministic nonlinear transformation of input signals. Full article

Many types of exact solutions to the truncated M-fractional classical Lonngren wave model are explored in this paper. The classical Lonngren wave model is a significant electronics equation. This model is used to explain the electronic signals within semiconductor materials, especially tunnel diodes. Through the application of a modified $(G^{\prime }/G^2)$-expansion technique and an extended sinh-Gordon equation expansion (EShGEE) method, we obtained various wave solutions, including periodic, kink, singular, dark, bright, and dark–bright types, among others. To ensure that the solutions in question are stable, linear stability analysis is also carried out. Moreover, the stationary solutions of the concerning equation are studied through modulation instability. The obtained results are useful in various areas, including electronic physics, soliton physics, plasma physics, nonlinear optics, acoustics, etc. Both techniques are useful for solving nonlinear partial fractional differential equations. Both techniques provide exact solutions, which can be important for understanding complex phenomena. Both techniques are reliable and yield distinct types of exact soliton solutions. Full article

Although epsilon-near-zero (ENZ) media have emerged as a promising platform for power dividers, the majority of existing designs are confined to fixed power splitting. In this work, two dynamically tunable power dividers using waveguide ENZ media are proposed by precisely modulating the internal magnetic field and the widths of the output waveguides. The first approach features a mechanically reconfigurable ring-shaped ENZ waveguide. By continuously re-distributing the magnetic field within the ENZ tunneling channels utilizing rotatable copper plates, arbitrary power division among multiple output ports is constructed. The second design integrates a rectangular-loop ENZ cavity into a substrate-integrated waveguide, with four positive–intrinsic–negative diodes embedded to dynamically activate specific output ports. This configuration steers electromagnetic energy toward output ports with varying cross-sectional areas, enabling on-demand control over both the power division and the number of output ports. Both analytical and full-wave simulation results confirm dynamic power division, with transmission efficiencies exceeding 93%. Despite differences in structure and actuation mechanisms, both designs exhibit flexible field control, high reconfigurability, and excellent transmission performance, highlighting their potential in advanced applications such as real-time wireless communications, multi-input–multi-output systems, and reconfigurable antennas. Full article

Tunnel construction poses significant safety challenges due to confined spaces, limited visibility, and the dynamic movement of labourers and machinery. This study addresses a critical gap in real-time, bidirectional proximity monitoring by developing and validating a prototype early-warning system that integrates real-time location systems (RTLS) with long-range (LoRa) wireless communication and ultra-wideband (UWB) positioning. The system comprises Arduino nano microcontrollers, organic light-emitting diode (OLED) displays, and piezo buzzers to detect and signal proximity breaches between workers and equipment. Using an action research approach, three pilot case studies were conducted in a simulated tunnel environment to test the system’s effectiveness in both static and dynamic risk scenarios. The results showed that the system accurately tracked proximity and generated timely alerts when safety thresholds were crossed, although minor delays of 5–8 s and slight positional inaccuracies were noted. These findings confirm the system’s capacity to enhance situational awareness and reduce reliance on manual safety protocols. The study contributes to the tunnel safety literature by demonstrating the feasibility of low-cost, real-time monitoring solutions that simultaneously track labour and machinery. The proposed RTLS framework offers practical value for safety managers and informs future research into automated safety systems in complex construction environments. Full article

The transport properties of one-dimensional van der Waals nanodevices composed of carbon nanotubes (CNTs), hexagonal boron nitride (hBN) nanotubes, and molybdenum dichalcogenide (MoX₂) nanotubes were investigated within the framework of density functional theory (DFT). It was found that in nanodevices based on MoS₂(24,24) and MoTe₂(24,24), the effect of resonant tunneling is suppressed due to electron–phonon scattering. This suppression arises from the fact that these materials are semiconductors with an indirect band gap, where phonon participation is required to conserve momentum during transitions between the valence and conduction bands. In contrast, nanodevices incorporating MoSe₂(24,24), which possesses a direct band gap, exhibit resonant tunneling, as quasiparticles can tunnel between the valence and conduction bands without a change in momentum. It was demonstrated that the presence of vacancy defects in the CNT segment significantly degrades quasiparticle transport compared to Stone–Wales (SW) defects. Furthermore, it was revealed that resonant interactions between SW defects in MoTe₂(24,24)–hBN(27,27)–CNT(24,24) nanodevices can enhance the differential conductance under certain voltages. These findings may be beneficial for the design and development of nanoscale diodes, back nanodiodes, and tunneling nanodiodes. Full article