This work investigated single-event burnout (SEB) and single-event leakage current from drain to source in SiC MOSFETs under femtosecond laser irradiation based on two-photon absorption (TPA), with the aim of investigating how laser-induced carrier generation and distribution affect SEE responses. The devices were irradiated from the front side under controlled laser irradiation conditions, including different laser pulse energies and relative displacements (RD) of the focal plane, to vary the amount and spatial location of laser-induced carriers. No irradiation-relevant gate damage was observed, indicating that the TPA laser irradiation induced specific SEE responses without introducing observable gate degradation. Results showed that the SEB threshold voltage depended on laser-induced carrier generation conditions and device voltage ratings (1.2 kV, 1.7 kV, and 3.3 kV). The SEB threshold voltage of 1.2 kV SiC MOSFETs exhibited a non-monotonic dependence on RD , with the highest sensitivity observed at RD = 3 μm, decreasing from 550 V (RD = 0 μm) to 450 V (RD = 3 μm) and then increasing to 1050 V (RD = 6 μm). These behaviors were interpreted in terms of the effective carrier population within the depletion region, which was influenced by the amount and spatial distribution of laser-generated carriers under different laser energies and focal-plane positions. The observed trends were consistent with reported single-event behavior under low-LET heavy-ion irradiation, highlighting the role of carrier density in understanding the relationship between laser-induced and low-LET heavy-ion-induced SEE responses.
High-energy heavy-ion induced single-event burnout (SEB) in p-GaN High Electron Mobility Transistors (HEMTs) under zero and negative gate bias were investigated. Under negative gate bias, simultaneous transient surges occur in both drain and gate currents during irradiation, whereas only drain current surge manifests in zero gate bias condition. This distinct behavior indicates bias-dependent SEB mechanisms. Through Technology Computer Aided Design (TCAD) simulations, we reveal that the redistribution of heavy-ion-induced charge critically governs post-strike electric field evolution. Electron cluster accumulation combined with back-channel effect caused the high electric field near the drain, resulting in the SEB under zero gate bias. Furthermore, analysis of the p-GaN gate energy band structure demonstrates that partial turn-on of the metal/p-GaN Schottky diode caused the high electric field within the p-GaN layer. Negative gate bias intensifies this electric field, thereby promoting breakdown beneath the gate electrode. Simulation results align with the experiment observations. This study provides new physical insights into SEB mechanisms in p-GaN HEMTs.
The multi-channel beam signal acquisition and processing system is a core component of beam position monitoring (BPM) systems and their related diagnostics in particle accelerators. Its channel mismatches directly affect the measurement accuracy of key parameters such as beam position, bunch length, and charge. To address the challenge that existing calibration methods struggle to achieve calibration results consistent with online operation, this paper proposes a quasi-in-situ calibration method for multi-channel mismatches based on the beam signal itself. Using the quasi-periodic characteristic of the beam signal, this method employs equivalent-time sampling combined with a waveform reconstruction algorithm to reconstruct the complete waveform for each channel with sufficient time resolution. It precisely calibrates the amplitude gains, time delays and DC offsets between channels, enabling a correction for the entire analog signal processing chain, including the beam pickups, the signal cables and the analog front-end electronics. Numerical simulations are performed to systematically analyze the influence of channel mismatches on the measured beam parameters, and an experimental verification is conducted at the Hefei Light Source II (HLS-II) storage ring. The results demonstrate that this method significantly enhances the channel matching of the BPM signal processors in the time and frequency domains, providing a practical and reliable quasi-in-situ calibration method for high-accuracy beam measurements.
CMOS Monolithic Active Pixel Sensors (MAPS) are widely used as vertex detectors in high energy physics experiments. In future high luminosity experiments, the high hit rate leads to large volumes of output data and poses challenges to MAPS. To address these issues, we propose a SMART MAPS architecture that integrates neural networks on-chip. The architecture enables the classification of particle incident angles and the rejection of hits generated by the beam background, thereby reducing the data volume. We design and optimize the algorithms targeted at on-chip implementation, including clustering, feature extraction, and a multilayer perceptron. These algorithms are implemented in Python and tested on hit data captured by the TaichuPix-3 at four different incident angles. Results demonstrate that the proposed design achieves 76.6% accuracy in incident angle classification, which reaches the same level of accuracy as that of the convolutional neural network architecture discussed in the paper. Moreover, the proposed algorithm requires only 184 weight parameters, a reduction of over 99.8% in storage and computation resources. These algorithms provide the possibility to integrate such smart classification capabilities into a monolithic active pixel sensor.
This paper investigates the influence of synchronous damage induced by heavy ions along the ion track on single-event burnout (SEB) in fast recovery diodes (FRDs). Experimental results show that heavy ions with a higher linear energy transfer (LET) do not exhibit a significantly lower single-event burnout voltage (VSEB), contradicting the traditional prediction that VSEB decreases with increasing LET. To clarify this phenomenon, an SEB experiment of a sample with protection against thermal failure is carried out, and the leakage current increased significantly (by 680 times) after irradiation, suggesting possible local synchronous damage along the ion track, which may introduce recombination centers and reduce the effective equivalent carrier lifetime during ion incidence. Based on this observation, the role of local synchronous damage in SEB is analyzed by combining experiments with 3D TCAD simulations. The results suggest that synchronous damage with a reduced local carrier lifetime may enhance recombination of excess carriers during ion incidence, thereby weakening avalanche multiplication and electrothermal positive feedback. Under high-LET irradiation, stronger synchronous damage may enhance local carrier removal and partially compensate for increased transient carrier generation, leading to weak LET dependence of VSEB in the tested FRDs. These results indicate that localized damage induced by heavy ions should be considered in SEB analysis of FRDs, particularly under high-LET irradiation. This mechanism may also affect SEB of other power semiconductor devices, but its relevance requires further verification.
In the development of Compton cameras, traditional pixelated scintillator designs face escalating complexity and cost as detector size increases. To address this, a side-readout monolithic planar scintillator scheme is proposed, where Silicon Photomultiplier (SiPM) arrays are coupled to the four edges. This configuration maximizes the sensitive detection volume while significantly reduces the photodetector requirement from N2 to 4N. A prototype utilizing a 96 × 96 × 6 mm3 CsI(Tl) monolithic scintillator was constructed to achieve 2D position sensing using only four electronic channels. To optimize performance, a geometric mean method was employed to correct energy peak drift caused by position-dependent signal variations. Furthermore, a neural network model was introduced to further improve position resolution. Experimental results with 662 keV gamma rays demonstrate a 2D position resolution of approximately 4.5 mm and an average energy resolution of 7.1%. These findings confirm that the proposed design significantly reduces readout complexity without compromising the position and energy resolutions required for Compton imaging, offering a cost-effective solution for large-area gamma-ray imaging and radiation monitoring.
This study systematically investigates the effects of low-energy proton irradiation (70 keV and 100 keV) on the performance and reliability of AlGaN/GaN high-electron mobility transistors (HEMTs). Low-frequency 1/f noise analysis was employed to quantitatively assess the radiation-induced defect density. Temperature-dependent low-frequency noise measurements revealed a feature at 345–350 K, corresponding to an effective activation energy of approximately 0.63 ± 0.05 eV. Combined with photoluminescence results, this energy level signature is associated with Ga-related substitutional impurities or vacancy defects. Post-irradiation annealing at 600 °C enables the recovery of up to 75% of the initial transconductance, demonstrating partial annihilation of the radiation-induced defects. These findings provide crucial insights into the proton irradiation damage mechanisms of AlGaN/GaN HEMTs.
Optimization of the prompt gamma-ray neutron activation analysis (PGNAA) experimental setup can enhance isotopic elemental detection and provide more reliable non-destructive assays across diverse sample compositions. However, this problem involves a high-dimensional parameter space encompassing moderator material, configuration dimensions, and sample positioning, and is coupled with computationally intensive Monte Carlo neutron transport simulations. As a result, it has commonly relied on manual design iterations and grid search. To address this challenge, this study introduces a novel simulation-driven reinforcement learning (RL) methodology using deep Q-learning (DQL) and online Monte Carlo simulations to optimize PGNAA geometry for industrially relevant materials. The approach is applied to two neutron source configurations: a high-energy D-T source (14.1 MeV) and a low-energy D-D source (2.45 MeV). For comparison, performance is evaluated against stochastic optimization algorithms, namely genetic algorithms (GA) and particle swarm optimization (PSO), each maximizing a reward function that reflects both neutron thermalization efficiency at the sample position and gamma-ray detection performance at the detector. In the D-T case, DQL achieves the highest mean gamma-ray peak flux among the three algorithms, while PSO attains the highest mean reward and GA converges fastest, with no single algorithm consistently outperforming the others across all metrics; physical validation confirms DQL’s superior detection enhancement across representative PGNAA samples. In the D-D case, DQL and PSO reach statistically indistinguishable detection performance, confirmed by physical validation, while DQL completes training significantly faster than both alternatives. Taken together, these results position simulation-driven reinforcement learning as a competitive framework for autonomous PGNAA geometry optimization across different neutron source energies.
Ultrathin semiconductor photodiodes are of particular interest for beam monitoring and position detection in X‑ray synchrotron beamlines and particle‑therapy medical applications. For X‑ray beam position monitors (XBPMs) operating in transmission mode, and considering the absorption properties of silicon, device thicknesses must be kept below 10 μm to achieve transmission levels above 90% for typical photon energies around 10 keV. Although wide‑bandgap semiconductors such as diamond, and more recently even silicon carbide (SiC), offer notable advantages, silicon can remain as a cost‑effective and attractive option for some beam‑positioning and monitoring applications. In this work, single‑element and four‑quadrant photodiodes have been fabricated on ultrathin silicon layers with thicknesses of 5 μm and 3 μm using silicon‑on‑insulator (SOI) substrates. Additionally, 1–2 μm‑thick membrane devices have been produced through chemical back‑etching of high‑resistivity Float‑Zone (FZ) silicon wafers and they have been included as control structures to evaluate the limitations of processing in the absence of a buried oxide (BOX) etch‑stop layer. These devices have been characterized through physical and electrical measurements and they have been tested under X‑ray beam conditions at the BL13‑XALOC beamline of the ALBA Synchrotron. Particular attention has been devoted to assessing their position‑sensing capabilities, including two‑dimensional spatial uniformity and one‑dimensional spatial resolution, along with beam linearity, energy response, and X‑ray transmission characteristics. The devices fabricated on SOI substrates exhibit good functional detector performance, with the ones having a nominal thickness of 3 μm (corresponding to an effective active depth of approximately 2.75 m), representing, to our knowledge, the thinnest segmented transmissive silicon XBPMs reported to date.
In this article, the high temperature (HT) and the high temperature gate bias (HTGB), including positive bias (PBTS) and negative bias (NBTS), annealing experiments, are performed to comprehensively investigate their recovery effects on the electrical characteristics of SiC MOSFETs after the total ionizing dose (TID) effect. Based on the electrical characteristics’ results before and after the experiments, both of the HT annealing and the PBTS annealing effectively release the holes captured by the oxide traps during the irradiation. They make the threshold voltage shift to the positive direction, mitigating the degradation induced by the irradiation. In particular, the PBTS annealing completely recovers the irradiated device, which is resulted from the combined effects of the holes releasing and the electrons tunneling. However, the NBTS annealing shows contradictory results at varying irradiation doses, leading to a severe deterioration of the devices exposed to a low-dose irradiation and a significant recovery of the ones subjected to a high-dose irradiation. These phenomena suggest the recovery effect varies with the temperature, the gate bias, and the cumulative dose. The energy band views and the TCAD simulations successfully reveal the underlying mechanism. Finally, the net charge density (ΔDot) shift calculated from the Cg-Vg curves are used to verify the experimental results and the recovery efficiency is compared. Such experiments provide good guidance for the annealing response of SiC MOSFETs under the TID effect.
The reliability requirements for on-chip electrostatic discharge (ESD) protection in high-voltage communication buses for space applications are extremely stringent. Traditional ESD solutions do not effectively meet the requirements for high holding voltage (Vh) and total-ionizing-dose (TID) tolerance in these applications. Therefore, this paper proposes a TID tolerant dual-direction silicon-controlled rectifier (DDSCR) based on a 0.18-μm BCD process, which is suitable for high-voltage radiation environments. At the same size, the Vh (15.3 V) of the embedded BJT shunt DDSCR (EBSDDSCR) is higher than that of the embedded MOS shunt DDSCR (EMSDDSCR). Furthermore, when the TID reaches 300 krad(Si), the EBSDDSCR effectively blocks the sidewall leakage path, maintains a low leakage current, and does not significantly degrade ESD performance. The results indicate that, compared to other high-voltage ESD structures, the EBSDDSCR exhibits superior characteristics, including higher Vh, improved human body model (HBM) protection level, higher TID tolerance, and lower leakage current. It can serve as a promising candidate for on-chip ESD protection in aerospace high-voltage communication buses.
The effects of neutron irradiation on the static and dynamic electrical characteristics of 4H-SiC MOSFETs are investigated. Devices were irradiated with an equivalent 1 MeV neutron fluence of 2×1013 n/cm². Static characteristics were evaluated using transfer and output characteristics. Dynamic switching and body-diode reverse-recovery characteristics were also evaluated. Gate–source capacitance (Cgs) and drain–source capacitance (CDS) measurements, together with charge-pumping (CP) and deep-level transient spectroscopy (DLTS), were employed to analyze irradiation-induced traps and their impact on device performance. Neutron irradiation degrades the static performance of the devices, characterized by reduced transconductance, increased subthreshold leakage current, and an increased on-state resistance. Cgs and CP results indicate enhanced interface-related traps in the channel region, which weaken gate control. CDS and DLTS analyses reveal the introduction of deep-level traps in the body and drift regions, mainly related to carbon vacancies, leading to reduced carrier concentration and conductivity and contributing to the increase in on-state resistance. In addition, neutron-induced traps modify the dynamic characteristics of the devices, including reduced voltage and current ringing with faster damping during switching and a suppressed peak reverse-recovery current of the body diode, while the switching energy loss remains nearly unchanged. Overall, these results show that neutron-induced traps affect both static and dynamic characteristics mainly through enhanced carrier trapping and increased equivalent resistance.
Silicon on insulator (SOI) technology is extensively employed in radiation-resistant integrated circuits due to its inherent robustness against single event effects (SEE). However, charge accumulation in oxide layers under ionizing radiation induces a total ionizing dose (TID) effect, leading to threshold voltage (Vth) drift and increased leakage current. To address this issue fundamentally, this study proposes and fabricates a novel void-embedded SOI (VESOI) planar MOSFET. By locally replacing the buried oxide beneath the channel with a vacuum void, the TID-sensitive volume is dramatically reduced. This structural innovation, combined with an H-gate layout and active back gate modulation, results in outstanding radiation hardness. The device exhibits an ultra-low subthreshold swing (SS) of 62.5 mV/dec prior to irradiation. After 4 Mrad(Si) irradiation, the SS variation remains below 1.5 mV/dec, and the switching characteristics show exceptional stability. The back gate voltage effectively compensates for radiation-induced Vth drift. The co-design of structural optimization and electrical compensation presented here offers a promising approach for realizing robust radiation-resistant SOI devices with excellent switching performance.
She et al. in [IEEE Trans. Nucl. Sci. 59(1), p. 205-210, 2012] presented an SEU-tolerant memory using an error-correction code capable of correcting single errors, double-adjacent errors, triple-adjacent errors, and double-almost-adjacent errors. This correction capability rests on the condition that every correctable error pattern is associated with a unique syndrome. After careful analysis of the check matrix presented in Eq. (4) and the associated syndrome table (Table I) of the above work, we have found that the proposed error-correction code yields duplicate syndromes for distinct error patterns. Consequently, the decoder cannot distinguish certain error classes claimed to be correctable, and the implemented memory would fail to correct them. We propose a valid 16-data-bit, 7-check-bit matrix in which all correctable syndromes are strictly unique both within and across error categories.
This paper presents a GPU-accelerated simulation package, TRED, for next-generation neutrino detectors with pixelated charge readout, leveraging community-driven software ecosystems to ensure adaptability and extensibility. We introduce two generic contributions: (i) an effective-charge representation based on Gaussian quadrature rules, in which the linear-interpolation factors for the field response inside each voxel are absorbed into the effective charge, and (ii) a sparse, block-binned tensor representation that enables efficient FFT-based computation of induced signals on readout electrodes for sparsely activated detector volumes. The former captures structure inside a voxel without dense sampling, while the latter achieves low memory usage and scalable runtime, as demonstrated in benchmark studies. The underlying data representation is applicable to large-scale detectors and to other computational problems involving sparse activity.
Securing metropolitan areas against nuclear threats has been a central objective of nuclear security since 9/11. A key defense strategy is source search, where radiation spectrometers are used to identify anomalies - sources that may pose potential threats - within consecutively acquired spectra. This paper presents a novel framework for real-time anomaly detection in gamma spectra collected at short intervals with a mobile detector. The framework integrates three components: dynamic data-driven application systems (DDDAS), matrix profile (MP), and fuzzy inference. This combination enables efficient spectral processing and timely decision-making regarding the presence of anomalies. At its core, DDDAS maintains and continuously updates an MP-based model of background radiation as new spectra are acquired. Anomaly detection is then carried out by a fuzzy inference system that uses four features derived from the stored MP model, the MP itself, and the Kolmogorov-Smirnov distance of the most recent spectra. Performance is evaluated by introducing source spectra as anomalies at random points in background datasets. Results show that the framework achieves high detection accuracy with very low false alarm rates, while delivering decisions in under one second, making it suitable for real-time applications. Furthermore, comparison with the conventional spectral ratio method based on the Kolmogorov-Smirnov test and sequential Bayesian detection highlights a substantially lower false alarm rate - about an order of magnitude reduction. Notably, in several test scenarios the framework yielded zero false alarms per 1,000 spectra, underscoring its effectiveness and robustness for nuclear security operations.
To address the lack of research on the propagation characteristics of low-altitude nuclear electromagnetic pulse (NEMP) in the day–night transition region of the Earth–ionosphere waveguide, this paper establishes a waveguide model incorporating a non-uniform day–night transitional structure and investigates the propagation behavior of low-altitude NEMP within this environment. An efficient computation of the source-region fields for low-altitude NEMP is achieved by employing a prolate spheroidal–hyperbolic coordinate system, with further acceleration of computational performance through OpenMP parallelization. Due to the absence of a standardized waveform representation for low-altitude NEMP—unlike lightning electromagnetic pulse, which can be analytically modeled using a simple double-exponential function—this paper incorporates the source-region contribution into the Earth-ionosphere propagation model containing a day–night transitional structure by means of the equivalence principle. Using the finite-difference time-domain (FDTD) method, the effects of diurnal environment, propagation direction, ground medium, and explosion yield on signal propagation are analyzed. This study provides a certain reference for analyzing the propagation of low-altitude NEMP in the ionospheric transition region.
