Search Results (105)

This study, for the first time, investigates and simulates ballistic-transport-induced avalanche behavior in two-dimensional materials. Using a technology computer-aided design simulation platform, a device model for ballistic avalanche transport is systematically established. By accurately calibrating the material parameters of two-dimensional materials and selecting appropriate physical models, the key features of the ballistic avalanche effect are successfully reproduced, including low threshold voltage and high gain. The simulation results show good agreement with experimental data. Furthermore, mechanism-based analysis is performed to clarify the influence of critical design parameters on the avalanche threshold and multiplication gain. Finally, based on the same physical models and mechanistic understanding, the operational paradigm and performance of ballistic-transport avalanche photodetectors based on two-dimensional materials are predicted. This work provides a reliable theoretical foundation and a robust simulation framework for the optimized design of high-performance and low-power avalanche photon devices. Full article

This work presents the simulation and design of 3C-SiC power MOSFETs, focusing on critical parameters including avalanche impact ionization, breakdown voltage, bulk and channel mobilities, and the trade-off between on-resistance and breakdown voltage. The device design is carried out by evaluating the blocking voltage of scaled structures as a function of the blocking layer’s doping concentration. To mitigate edge-effect breakdown at the p-well/n-drift interface, a step-profile doping strategy is employed. Multiple transistor layouts with varying pitches are developed using a commercially available device simulator. Results are benchmarked against a one-dimensional analytical model, validating the on-state resistance, current–voltage behavior, and overall accuracy of the simulation approach. For the selected material properties, simulations predict that a 600 V 3C-SiC MOSFET achieves an on-state resistance of 0.8 mΩ·cm², corresponding to a 7 μm drift layer with a doping concentration of 1 × 10¹⁶ cm⁻³. Full article

This study proposes a complete data-processing framework for Geiger-mode avalanche photodiode (GM-APD) light detection and ranging (LiDAR) echo signals. It investigates the feasibility of classifying target and background noise using machine learning. Four feature processing schemes were first compared, among which the PNT strategy (Principal Component Analysis without tail features) was identified as the most effective and adopted for subsequent analysis. Based on this framework, nine models derived from six baseline algorithms—Decision Trees (DTs), Support Vector Machines (SVMs), Backpropagation Neural Networks (NN-BPs), Linear Discriminant Analysis (LDA), Logistic Regression (LR), and k-Nearest Neighbors (KNN)—were systematically assessed under Monte Carlo simulations with varying echo signal-to-noise ratio (ESNR) and statistical frame number (SFN) conditions. Model performance was evaluated using eight metrics: accuracy, precision, recall, FPR, FNR, F1-score, Kappa coefficient, and relative change percentage (RCP). Monte Carlo simulations were employed to generate datasets, and Principal Component Analysis (PCA) was applied for feature extraction in the machine learning training process. The results show that LDA achieves the shortest training time (0.38 s at SFN = 20,000), DT maintains stable accuracy (0.7171–0.8247) across different SFNs, and NN-BP models perform optimally under low-SNR conditions. Specifically, NN-BP-3 achieves the highest test accuracy of 0.9213 at SFN = 20,000, while NN-BP-2 records the highest training accuracy of 0.9137. Regarding stability, NN-BP-3 exhibits the smallest RCP value (0.0111), whereas SVM-3 yields the largest (0.1937) at the same frame count. In conclusion, NN-BP-based models demonstrate clear advantages in classifying sky-background noise. Building on this, we design a ResNet based on NN-BP, which achieves further accuracy gains over the best baseline at 400, 2000, and 20,000 frames—12.5% (400), 9.16% (2000), and 2.79% (20,000)—clearly demonstrating the advantage of NN-BP for GM-APD LiDAR signal classification. This research thus establishes a novel framework for GM-APD LiDAR signal classification, provides the first systematic comparison of multiple machine learning models, and highlights the trade-off between accuracy and computational efficiency. The findings confirm the feasibility of applying machine learning to GM-APD data and offer practical guidance for balancing detection performance with real-time requirements in field applications. Full article

Silicon–germanium (Si-Ge) avalanche photodiodes (APDs), fully compatible with complementary metal–oxide–semiconductor (CMOS) processes, are critical devices for high-speed optical communication. In this work, we propose a three-terminal Si-Ge APD on a silicon-on-insulator (SOI) substrate based on device simulation studies. The proposed APD employs a separate absorption and multiplication structure, achieving an ultra-low breakdown voltage of 6.8 V. The device operates in the O-band, with optical signals laterally coupled into the Ge absorption layer via a silicon nitride (Si₃N₄) waveguide. At a bias of 2 V, the APD exhibits a responsivity of 0.85 A/W; under a bias of 6.6 V, it achieves a 3-dB optoelectronic (OE) bandwidth of 51 GHz, a direct current gain of 27, and a maximum gain–bandwidth product (GBP) of 1377 GHz. High-speed performance is further confirmed through eye-diagram simulations at 100 Gbps non-return-to-zero (NRZ) and 200 Gbps four-level pulse amplitude modulation (PAM4). These results clearly show the strong potential of the proposed APD for optical communication and interconnect applications under stringent power and supply voltage constraints. Full article

Sensor fusion is crucial in numerous imaging and sensing applications. Integrating data from multiple sensors with different field-of-view, resolution, and frame timing poses substantial computational overhead. Time-gated single-photon avalanche diode (SPAD) image sensors have been developed to support multiple sensing modalities and mitigate this issue, but mismatched frame timing remains a challenge. Dual-time-gated SPAD image sensors, which can capture dual images simultaneously, have also been developed. However, the reported sensors suffered from medium-to-large pixel pitch, limited resolution, and inability to independently control the exposure time of the dual images, which restricts their applicability. In this paper, we introduce a 5 µm-pitch, 3D-backside-illuminated (BSI) 1Megapixel dual-time-gated SPAD image sensor enabling a simultaneous output of dual images. The developed SPAD image sensor is verified to operate as an RGB-Depth (RGB-D) sensor without complex image alignment. In addition, a novel high dynamic range (HDR) technique, utilizing pileup effect with two parallel in-pixel memories, is validated for dynamic range extension in 2D imaging, achieving a dynamic range of 119.5 dB. The proposed architecture provides dual image output with the same field-of-view, resolution, and frame timing, and is promising for efficient sensor fusion. Full article

The study presents a spectral assessment and analysis of various data and methods for snow cover analysis in different ranges of the electromagnetic spectrum through a differentiated approach applied to the territory of Bansko, Pirin Mountain. The aim of the presented research is to assess the effectiveness and accuracy of satellite observations together with field (in situ) measurements and to create a model of an integrated methodology. To achieve this goal, several indices, such as land surface temperature (LST), optical indices, Tasseled Cap Transformation (TCT) with wetness component (TCW), High-Resolution (HR) imagery, and Synthetic Aperture Radar (SAR) measurements, were analyzed. The results of the analysis proved that combining satellite and field data through a mobile thermal camera provides an accurate and comprehensive picture of snow conditions in high mountain regions for powder, hard-packed and wet snow. As the most important, there is the verification and validation of the results through the so-called regression analysis of the different data types, through which multiple correlations (over 10) were established, both in data from Sentinel 1SAR, Sentinel 2MSI, Sentinel 3 SLSTR, and PlanetScope. The results showed the effectiveness of optical indices for hard and fresh snow and radar and LST data for wet snow. The results can be used to improve snow surveys, event prediction (e.g., avalanches), and the interpretation of spectral analysis of snow. The study does not aim to perform a temporal analysis; all satellite data is from the temporal period 30 December 2024–5 January 2025. Full article

Over the past few years, Low-Gain Avalanche Detectors (LGADs) have demonstrated excellent timing performance, showing great potential for use in 4D tracking of high-energy charged particles. Carbon co-doping is a key factor for enhancing LGAD performance, which are detectors with intrinsic amplification, in harsh radiation environments. This work presents a broad pre-irradiation characterization of the latest carbon-co-implanted (or carbonated) LGADs fabricated at IMB-CNM. The results indicate that the addition of carbon reduces the nominal gain of the devices compared with non-carbonated detectors. Furthermore, a comprehensive study is presented on how carbon co-implantation can either enhance or suppress the diffusion of the multiplication layer during LGAD fabrication, depending on the device structure and fabrication parameters. Full article

Quantum sensing based on NV-centers in diamonds has been demonstrated many times in multiple publications. The majority of publications use lasers in free space or lasers with fiber optics, expensive optical components such as dichroic mirrors, or beam splitters with dichroic filters and expensive detectors, such as Avalanche photodiodes or single photon detectors, overall, leading to custom and expensive setups. In order to provide an inexpensive NV-based magnetometer setup for educational use in schools, to teach the three topics, fluorescence, optically detected magnetic resonance, and Zeeman splitting, inexpensive, miniaturized, off-the-shelf components with high reliability have to be used. The cheaper such a setup, the more setups a school can afford. Hence, in this work, we investigated LEDs as light sources, considered different diamonds for our setup, tested different color filters, proposed an inexpensive microwave resonator, and used a cheap photodiode with an appropriate transimpedance amplifier as the basis for our quantum magnetometer. As a result, we identified cheap and functional components and present a setup and show that it can demonstrate the three topics mentioned at a hardware cost <EUR 100. Full article

High-frequency (h. f.) harmonic distortion (HD) of advanced SiGe heterojunction bipolar transistor (HBT)-based power cells (PwCs), featuring optimized metallization interconnections between individual HBTs, was investigated. Single tone input power (P_in) excitations at 1, 2, 5, and 10 GHz frequencies were employed. The output power (P_out) of the fundamental tone and its harmonics were analyzed in both the frequency and time domains. A rapid increase in the third harmonic of P_out was observed at input powers exceeding −8 dBm for a fundamental frequency of 10 GHz in two different PwC technologies. This increase in the third harmonic was analyzed in terms of nonlinear current waveforms, the nonlinearity of the HBT p-n junction diffusion capacitances, substrate current behavior versus P_in, and avalanche multiplication current. To assess the RF power performance of the PwCs, scalar and vectorial load-pull (LP) measurements were conducted and analyzed. Under matched conditions, the SiGe PwCs demonstrated good linearity, particularly at high frequencies. The key power performance of the PwCs was measured and simulated as follows: input power 1 dB compression point (P_{in_1dB}) of −3 dBm, transducer power gain (G_T) of 15 dB, and power added efficiency (PAE) of 50% at 30 GHz. All measured data were corroborated with simulations using the compact model HiCuM L2. Full article

Investigating avalanche hazards is a fundamental preliminary task in avalanche research. This work is critically important for establishing avalanche warning systems and designing mitigation measures. Primary research data originated from field investigations and UAV aerial surveys, with avalanche counts and timing identified through image interpretation. Snowpack properties were primarily acquired via in situ field testing within the study area. Methodologically, statistical modeling and RAMMS::AVALANCHE simulations revealed spatiotemporal and dynamic characteristics of avalanches. Subsequent application of the Certainty Factor (CF) model and sensitivity analysis determined dominant controlling factors and quantified zonal influence intensity for each parameter. This study, utilizing field reconnaissance and drone aerial photography, identified 86 avalanche points in the study area. We used field tests and weather data to run the RAMMS::AVALANCHE model. Then, we categorized and summarized regional avalanche characteristics using both field surveys and simulation results. Furthermore, the Certainty Factor Model (CFM) and the parameter Sensitivity Index (Sa) were applied to assess the influence of elevation, slope gradient, aspect, and maximum snow depth on the severity of avalanche disasters. The results indicate the following: (1) Avalanches exhibit pronounced spatiotemporal concentration: temporally, they cluster between February and March and during 13:00–18:00 daily; spatially, they concentrate within the 2100–3000 m elevation zone. Chute-confined avalanches dominate the region, comprising 73.26% of total events; most chute-confined avalanches feature multiple release areas; therefore the number of release areas exceeds avalanche points; in terms of scale, medium-to-large-scale avalanches dominate, accounting for 86.5% of total avalanches. (2) RAMMS::AVALANCHE simulations yielded the following maximum values for the region: flow height = 15.43 m, flow velocity = 47.6 m/s, flow pressure = 679.79 kPa, and deposition height = 10.3 m. Compared to chute-confined avalanches, unconfined slope avalanches exhibit higher flow velocities and pressures, posing greater hazard potential. (3) The Certainty Factor Model and Sensitivity Index identify elevation, slope gradient, and maximum snow depth as the key drivers of avalanches in the study area. Their relative impact ranks as follows: maximum snow depth > elevation > slope gradient > aspect. The sensitivity index values were 1.536, 1.476, 1.362, and 0.996, respectively. The findings of this study provide a scientific basis for further research on avalanche hazards, the development of avalanche warning systems, and the design of avalanche mitigation projects in the study area. Full article

The impact-ionization-enhanced mechanism is introduced into a SiC light-triggered thyristor (LTT) to improve its switching speed under weak UV illumination. The effects of impact ionization on photogenerated carrier multiplication and the dynamic switching performance of the SiC LTT are investigated through TCAD simulation. The relationships between bias voltage, UV light intensity, and key dynamic parameters are analyzed. Simulation results indicate that when the bias voltage exceeds 14 kV, the device enters the avalanche multiplication regime, leading to a significant increase in photocurrent under a given UV intensity. As the bias voltage increases, the turn-on time of the thyristor first decreases, then saturates, and finally drops rapidly. Under UV illumination of 100 mW/cm², the turn-on time decreases from 10.1 μs at 1 kV to 0.85 μs at 18 kV, while the switching energy dissipation at 18 kV is only 1292.3 mJ/cm². These results demonstrate that the impact-ionization-enhanced effect substantially improves the switching performance of SiC LTTs. Full article

The laser pulse detection probability of a scanning direct time-of-flight light detection and ranging (LiDAR) measurement is evaluated based on the optical signal distribution on a multipixel single photon avalanche diode (SPAD) array. These detectors intrinsically suffer from dead-times after the successful detection of a single photon and, thus, allow only for limited counting statistics when multiple returning laser photons are imaged on a single pixel. By blurring the imaged laser spot, the transition from single-pixel statistics with high signal intensity to multipixel statistics with less signal intensity is examined. Specifically, a comparison is made between the boundary cases in which (i) the returning LiDAR signal is focused through optics onto a single pixel and (ii) the detection is performed without lenses using all available pixels on the sensor matrix. The omission of imaging optics reduces the overall system size and minimizes optical transfer losses, which is crucial given the limited laser emission power due to safety standards. The investigation relies on a photon rate model for interfering (background) and signal light, applied to a simulated first-photon sensor architecture. For single-shot scenarios that reflect the optimal use of the time budget in scanning LiDAR systems, the lens-less and blurred approaches can achieve comparable or even superior results to the focusing system. This highlights the potential of fully solid-state scanning LiDAR systems utilizing optical phase arrays or multidirectional laser chips. Full article

In this contribution, we explored the interplay of guard ring (GR) configuration and isolation structures, as well as irradiation effects, which all together create a rich landscape of phenomena such as self-induced signals (“ghosts”) in trench-isolated Low-Gain Avalanche Diodes (TI-LGADs). The ghost effect is related to the increased surface current due to presence of SiO₂ trenches (and defects) in studied diodes, but it is also affected by interplay between the guard ring(s) and the n⁺ bias ring, implanted in inter-pixel region of these devices. In double-trenched sensors, the n⁺ bias ring is inserted in between the two trenches. We present the investigation on the role of these structures on the self-induced signals in trench-isolated sensors from two different productions (RD50 and AIDAinnova). The sensors from the first production have multiple guard rings, whereas the second type of devices feature only one. Detailed examination of the ghost effect and leak current was performed when guard rings were left floating or connected to the pixels (brought to the same potential). The results show that guard ring configuration in trenched sensors can be critical for the leak current and the presence of a ghost signal. To our best knowledge, the latter problem has not been investigated yet. Full article

Southeast Tibet is characterized by extensive alpine glaciers and deep valleys, making it highly prone to cryospheric disasters such as avalanches, ice/ice–rock avalanches, glacial lake outburst floods, debris flows, and barrier lakes, which pose severe threats to infrastructure and human safety. Understanding how cryospheric disasters respond to climate warming remains a critical challenge. Using 3.3 km resolution meteorological downscaling data, this study analyzes the spatiotemporal evolution of multiple climate indicators from 1979 to 2022 and assesses their impacts on cryospheric disaster occurrence. The results reveal a significant warming trend across Southeast Tibet, with faster warming in glacier-covered regions. Precipitation generally decreases, though the semi-arid northwest experiences localized increases. Snowfall declines, with the steepest decrease observed around the lower reaches of the Yarlung Zangbo River. In the moisture corridor of the lower reaches of the Yarlung Zangbo River, warming intensifies freeze–thaw cycles, combined with high baseline extreme daily precipitation, which increases the likelihood of glacial disaster chains. In northwestern Southeast Tibet, accelerated glacier melting due to warming, coupled with increasing extreme precipitation, heightens glacial disaster probabilities. While long-term snowfall decline may reduce avalanches, high baseline extreme snowfall suggests short-term threats remain. Finally, this study establishes meteorological indicators for predicting changes in cryospheric disaster risks under climate change. Full article

The avalanche multiplication effect, capable of significantly amplifying weak optical or electrical signals, plays a pivotal role in enhancing the performance of electronic and optoelectronic devices. This effect has been widely employed in devices such as avalanche photodiodes, impact ionization avalanche transit time diode, and impact ionization field-effect transistors, enabling diverse applications in biomedical imaging, 3D LIDAR, high-frequency microwave circuits, and optical fiber communications. However, the evolving demands in these fields require avalanche devices with superior performance, including lower power consumption, reduced avalanche threshold energy, higher efficiency, and improved sensitivity. Over the years, significant efforts have been directed towards exploring novel device architectures and multiplication mechanisms. The emergence of two-dimensional (2D) materials, characterized by their exceptional light-matter interaction, tunable bandgaps, and ease of forming junctions, has opened up new avenues for developing high-performance avalanche devices. This review provides an overview of carrier multiplication mechanisms and key performance metrics for avalanche devices. We discuss several device structures leveraging the avalanche multiplication effect, along with their electrical and optoelectronic properties. Furthermore, we highlight representative applications of avalanche devices in logic circuits, optoelectronic components, and neuromorphic computing systems. By synthesizing the principles and applications of the avalanche multiplication effect, this review aims to offer insightful perspectives on future research directions for 2D material-based avalanche devices. Full article