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Record W7105295578 · doi:10.1109/tns.2025.3632154

Design and Testing of a 32-bit Radiation-Tolerant RISC-V Microcontroller at the 22-nm FD SOI Node

2025· article· W7105295578 on OpenAlexafffund

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2025
Typearticle
Language
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyCisco Systems
KeywordsMicrocontrollerApplication-specific integrated circuitSilicon on insulatorRedundancy (engineering)Node (physics)SoftwareDevice under testFault toleranceCMOS

Abstract

fetched live from OpenAlex

This work presents StarRISC, which is a radiation-tolerant RISC-V ASIC microcontroller fabricated at the 22-nm FD SOI node. This device is a complete SoC which includes a 4-stage 32-bit core, a variety of peripherals, various I/Os, as well as 512 kB of on-chip SRAM. The device is hardened through several measures which include the use of ECC memory, automatic memory scrubbing, as well as the usage of custom designed radiation-hardened buffer and storage cells. Neither TMR nor software-level redundancy approaches are used in the design. Broad-beam testing results of the device show remarkable resilience to single event effects under alpha particles, protons, and heavy ions. As well, the results clearly show that the failure rate of the device is also dependent on the type of software that is running on the device during irradiation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.661
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.222
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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