The SALSA chip will be a versatile ASIC designed for various MPGD applications, including TPCs, trackers, and photon detection. It will feature 64 channels with tunable front-ends and fast ADCs, and a configurable DSP for data correction and feature extraction. The front-end includes a high open loop gain Charge Sensitive Amplifier (CSA), a pole-zero cancellation circuit, and a shaper, with four dynamic ranges and eight peaking times. The ADC is based on a Hybrid RC 12-bit 50 MS/s Successive Approximation Architecture (SAR). The SALSA chip is intended to equip the ePIC MPGD trackers of the Electron Ion Collider (EIC) experiment currently under construction at Brookhaven National Lab (BNL). Several ASIC prototypes have already been designed and tested to validate the main analog building blocks of the future SALSA chip such as analog channel, ADC, PLL, embedded analog and digital probes, I2C and others.

Superconducting cavities constitute essential components within cryomodules of high-repetition-rate free-electron laser facilities, including Shenzhen Superconducting Soft X-ray FEL (S3FEL). Their operation imposes demanding of vacuum specifications, as ultra-high vacuum (UHV) and particulate-free (PF) conditions. To achieve the vacuum integrity between the cryogenic superconducting section (∼2 K, vacuum better than 1.3 × 10-8 Pa) and the warm-temperature section (vacuum better than 1.3×10-6 Pa), a dedicated UHV differential pumping (DP) system has been designed and optimized with theoretical modeling and numerical simulations, to attain pressure differential of three orders of magnitude with total length less than 1.5 m. The prototype DP was assembled following UHV compitable, particle-free procedures under critically controlled clean conditions. In validation tests, with the set pressure of 10-5 Pa range at the warm side, the cryo-sideconsistently sustained UHV conditions at pressure of ×10-8Pa level. Residual gas analysis (RGA) has been performed to confirm that the hydrogen component could be effectively pumped by sputter ion pumps and non-evaporable getter (NEG) pumps set in DP, which benefit the reducing of hydrogen partial pressure and mitigating of hydrogen migration and condensation in the superconducting radio-frequency (SRF) cavities. This differential pumping system could offer robust technical reference for the design and engineering of beamline vacuum interconnects in future superconducting accelerator projects.

The High Luminosity LHC upgrade demands enhanced tracking, prompting a complete replacement of ATLAS's Inner Detector with the all-silicon Inner Tracker (ITk). Spanning 33–291 mm from the beam pipe, ITk will use hybrid pixel detectors with 65 nm CMOS chips. The inner region, facing extreme radiation, will feature 3D pixel sensors due to their superior radiation tolerance, while the outer regions will use planar sensors. The production of 3D sensors is distributed among two vendors, FBK and SINTEF. The ITk linear triplet module consists of three hybrids (readout chip bump-bonded to a 3D pixel sensor) mounted on a flexible PCB. Extensive testing has been carried out on a linear triplet module in 2025 at CERN's test beam facilities, using 120 GeV pion beams to validate its performance under HL-LHC conditions. The most recent results of the module studied after irradiation will be presented here.

During the Long Shutdown 3 (LS3) of the Large Hadron Collider (LHC), the base layer quench detectors for the LHC main dipoles will be upgraded to a new type. The new FPGA-based quench detectors are equipped with two galvanically isolated, high-resolution input stages that digitise the two dipole aperture coil voltages. This new digital design allows the quench detection settings to be changed remotely. As the detectors are installed below the dipole magnets, they have to withstand the radiation present during LHC operation, which can exceed 100 Gy/y at certain locations. This paper discusses the design, testing, component selection and implementation of the new detector boards.

Accurate localization and tracking of mobile radioactive source in dynamic environments (e.g., border crossings an transportation hubs) remain challenging due to the high cost and static-scene limitations of directional radiation detectors. We propose a cost-effective system fusing a monocular optical camera and a radiation detector to track mobile gamma sources. The system employs YOLOv3 and Kalman filtering for pedestrian path detection, computes distance variations between pedestrians and the detector, and correlates radiation count rates with distance using the inverse-square law. Additionally, by calibrating the detector's absolute efficiency against distance, the system is able to estimate source activity. Experimental results demonstrate effective localization of mobile sources (90% accuracy) and activity estimation (<80% error), validating the method's feasibility for real-world nuclear security applications.

Resistive Plate Chambers (RPCs) are widely used as tracking detectors in many high-energy physics experiments. It has been observed that low-resistive bakelite RPC prototypes frequently exhibit a secondary hit component, appearing as a long tail or an additional peak in the time-correlation spectra relative to the trigger detector. These secondary hits, which affect both the time and spatial resolution, are difficult to distinguish from genuine signals in high-rate environments without an external trigger. As a result, they can significantly degrade track reconstruction efficiency and increase processing time. We present a machine-learning-based strategy to separate signal and background hit clusters using fifteen cluster-level descriptors that encode both statistical properties (histogram mean, width, cluster size) and fit-based parameters (Gaussian-fit mean, width, amplitude, χ2, NDF) of the time and ADC distributions. Using laboratory data collected from a single-gap low resistive RPC with a three-scintillator master trigger, we trained and evaluated three classifiers-DNN, 1D-CNN, and XGBoost-on balanced signal/background samples. All models demonstrate strong discrimination capability, with XGBoost showing the most robust generalization performance. Feature-importance analysis indicates that cluster size and temporal-shape descriptors are the dominant discriminants. These results highlight that compact, interpretable cluster-level features combined with machine-learning classifiers offer a practical and effective approach to suppress background in self-triggering low resistive RPC detectors.

The next-generation of neutrinoless double beta decay (0νββ) searches are targeting half-life sensitivities towards 1027–1028 years. Gaseous xenon time projection chamber (GXeTPC) detectors may be able to meet this challenge due to their excellent energy resolution and background rejection power through event visualization. This paper explores how the design choices of a next-generation GXeTPC time projection chamber can impact the overall performance of the experiment. We study the performance of systems using xenon enriched in the isotope 136Xe or natural xenon, focusing on scenarios that incorporate one tonne of 136Xe isotope. The detector size, copper shielding mass, energy resolution, density (using pressure at 293 K for convenience), and corresponding levels of diffusion are surveyed to evaluate the overall performance dependencies on these parameters. A detector optimized for using enriched xenon is preferred over natural, due primarily to a factor of 10 lower background rate driven by the large intrinsic backgrounds introduced by the copper shielding used in the detector. The performance of three types of gas TPC technologies was also explored based on different gas additives used to reduce diffusion to different levels. For all TPC technologies, we find background rates of a fraction of a count per tonne year in the region of interest are achievable. These performance levels are contingent on suitable energy resolution and event position placement in the drift direction being achieved for the specific detector technology. Performance for enriched xenon TPCs varies mildly with pressure in the range 5 to 25 bars, reaching background levels below 0.2 events/tonne-year. Performance at one bar is worse by approximately a factor of four. When considerations for the construction of the detector in addition to the selection performance are included, there may be no clearly optimum pressure.

This project presents a specialized gamma radiation detector electronics system optimized for aerial mapping, surveillance, and radiation safety applications. The drone-mounted design effectively addresses radiation safety requirements across challenging terrains and sensitive locations. We discuss the main features of the detector electronics, starting from powering the detector up to data output to the onboard computer (OBC).The detector integrates four high-resolution scintillation crystals read out by photomultiplier tubes (PMTs) and surrounded by a plastic scintillator veto system employing silicon photomultipliers (SiPMs). The custom electronics architecture emphasizes compactness, miniaturization, and low power consumption. It features analog front-end processing, digitally-controlled high-voltage bias modules, high-speed analog to digital converter (ADC: 50 MHz, 16-bit), and advanced field programmable gate array (FPGA) based digital signal processing (DSP), including trapezoidal finite impulse response (FIR) filtering, precise peak detection, and robust coincidence/anticoincidence trigger logic. Processed data are stored in onboard histogram memories, providing detailed gamma-ray spectra with adjustable resolution and dynamic range, complemented by integrated temperature andhumiditysensors for environmental corrections. An STMicroelectronics (STM32) microcontroller interfaces these subsystems with a Raspberry Pi acting as the onboard computer, facilitating data acquisition, storage, analysis, and real-time control using a long-term evolution (LTE) cellular modem kit, which also provides GPS tagging capabilities.

The detection and characterization of lunar water are critical for enabling sustainable human and robotic exploration of the Moon. Orbital neutron spectrometers, such as instruments on Lunar Prospector and the Lunar Reconnaissance Orbiter, have revealed hydrogen-rich regions near the poles but are limited by coarse spatial resolution and low counting efficiency. We present a compact, lightweight, and low-power epithermal neutron detector based on boron-coated silicon imagers, designed to probe subsurface hydrogen at decimeter scales from mobile platforms such as lunar rovers. This instrument leverages the high neutron capture cross-section of 10B to convert epithermal neutrons into detectable α and 7Li ions in a fully-depleted silicon imager, providing a unique event topology to identify neutrons while suppressing backgrounds. Monte Carlo simulations demonstrate that a 3 μm boron layer achieves optimal neutron detection efficiency, further enhanced with polyethylene moderation to improve sensitivity to the 0.4 eV–500 keV epithermal energy range. For a 10 cm2 active area, the detector achieves sensitivity to H2O weight fractions as low as 0.01 wt% in a 15 minute measurement. This scalable, portable, low-mass design is well-suited for integration into upcoming Artemis and commercial lunar rovers, providing a transformative capability for in-situ resource prospecting and ground-truth validation of orbital measurements.

For a proposed upgrade of the Belle II experiment an R&D program has been established to develop a new vertex detector (VTX) made from a single type of depleted active monolithic pixel detector named OBELIX. The chip will provide two low voltage differential signaling (LVDS) data links with a transmission speed of about 339 MHz. To read out the OBELIX data it is foreseen to utilize optical links based on the lpGBT chip and the VTRx+ transceiver module, both developed at CERN. We will present a first concept of the VTX readout system and discuss its technical requirements.