Marcilei Aparecida Guazzelli da Silveira

This work proposes a methodology to evaluate the robustness of commercial Field-Programmable Gate Arrays (FPGAs) against radiation effects induced by fast neutrons. The automated data acquisition system implemented in this study enables monitoring and characterization of neutron-induced er- rors in the devices. The results allowed us to observe consistently that irradiation with fast neutrons at CNA HiSPANoS produced errors in the FPGA, including Single Event Upsets (SEUs), which affect the implemented control logic, and Single Event Functional Interrupts (SEFIs), leading to a complete loss of data. The proposed approach provides a framework for as- sessing the susceptibility of commercial FPGAs to neutron-in- duced faults and serves as a foundation for future investigations in this field.

Lifetimes of several excited states in the mirror nuclei Cr 47 − V 47 and Mn 49 − Cr 49 , located at the center of the f 7 / 2 shell, were measured using the advanced γ -ray tracking array AGATA. The Doppler shift attenuation method was employed to determine such lifetimes in the subpicosecond range. The reduced transition probabilities obtained from the lifetimes are compared to shell-model calculations in the full f p space. The shell-model-calculated B ( E 2 ) values were underestimated in comparison with experimental data. In particular, large discrepancies are obtained in Mn 49 at low spin. These results suggest an incomplete understanding of low-energy states in the studied nuclei and call for further refinement of the existing nuclear structure theories.

Editor’s notes: This article evaluates partial and full triple modulator redundancy (TMR) strategies in a RISC-V softcore processor on SRAM-based FPGAs, showing that selectively inserting voters can significantly improve radiation reliability while reducing area overhead compared to full TMR. —José Augusto Nacif, Federal University of Viçosa, Brazil —Omar Paranaiba Vilela Neto, Federal University of Minas Gerais (UFMG), Brazil

This study examines the performance of two Convolutional Neural Networks (CNNs) designed for aerial image classification in the presence of radiation-induced bit-flips. We modify these CNNs by adjusting parameters such as quantization and parallelism to facilitate their implementation using the FINN inference engine, which is optimized for the AMD/Xilinx FPGAs. The aim is to evaluate the impact of different quantization levels, network topologies, and architectural parallelism on area, computational performance, and reliability in the presence of soft-errors. Emulated fault injection and heavy ion irradiation were performed. The results indicate that the same CNN topology can exhibit up to a 2.7× difference in Mean Fluence to Failure (MΦTF) by altering quantization and architectural parallelism. The findings demonstrate that higher dependability can be obtained by carefully combining a suitable CNN topology with optimized quantization and architectural parallelism.

The U-shaped Metal-Oxide-Semiconductor Field-Effect Transistor (UMOS or trench FET) is one of the most widely used semiconductor power devices worldwide, increasingly replacing the traditional vertical double-diffused MOSFET (DMOSFET) in various applications due to its superior electrical performance. However, a detailed experimental comparison of ion-induced Single-Event Burnout (SEB) in similarly rated silicon (Si) UMOS and DMOS devices remains lacking. This study presents a comprehensive experimental comparison of ion-induced charge collection mechanisms and SEB susceptibility in similarly rated Si UMOS and DMOS devices. Charge collection mechanisms due to alpha particles from ²⁴¹Am radiation source are analyzed, and SEB cross sections induced by heavy ions from particle accelerators are directly compared. The implications of the unique gate structure of Si UMOSFETs on their reliability in harsh radiation environments are discussed based on technology computer-aided design (TCAD) simulations.

The trench gate or U-groove MOSFET (UMOSFET) has become widely adopted as a semiconductor device globally, gradually replacing the traditional vertical double-diffused MOSFET (DMOSFET) in many applications. Evaluating the reliability of UMOSFETs regarding neutron-induced radiation effects is crucial for understanding their response to ubiquitous atmospheric neutrons. This study presents comparative experimental and computational results of Single-Event Effects induced by monoenergetic fast neutrons in UMOS and DMOS power transistors. Experiments demonstrate that UMOSFETs exhibit premature particle-induced avalanche multiplication effects compared to similarly rated DMOSFETs, which may favor destructive radiation effects, such as Single-Event Burnout, when operating in the terrestrial radiation environment.

Charge funneling is a widely used description of charge collection dynamics in semiconductor devices struck by ion irradiation, but it still relies on semiempirical parameters heavily dependent upon available data, which impacts its use for device or circuit-level simulations. The objective of this article is to analyze a comprehensive dataset from low-energy heavy-ion irradiations on a p-MOSFET, varying both the linear energy transfer (LET) and ion penetration depth within the device. A novel methodology is proposed to achieve this goal by analyzing devices without prior knowledge of their parameters, using data from light ion irradiations. Statistical analysis of the data and comparisons to simulated values showed that a LET-dependent funnel length is a more accurate description of the phenomenon than the conventional constant-length approach. A new, lower value for the funnel model’s shielding parameter k was identified, and the method also allowed for determining the metal and passivation layer thicknesses of the device. These results strengthen the reliability of the funnel model, making it a more robust tool for simulation applications.