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Record W1763499344 · doi:10.1504/ijspacese.2015.069357

Characterisation of operational amplifier performance as a function of total ionising dose at both room and cryogenic operating temperatures for space applications

2015· article· en· W1763499344 on OpenAlexaff
J. H. Johnson, M. G. Daly, David M. Hiemstra

Bibliographic record

VenueInternational Journal of Space Science and Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsYork University
Fundersnot available
KeywordsAmplifierInput offset voltageAbsorbed doseTransistorSpace environmentVoltageOffset (computer science)CryogenicsOptoelectronicsOperational amplifierMaterials scienceIonizing radiationRadiationElectrical engineeringNuclear engineeringComputer sciencePhysicsIrradiationOpticsEngineering

Abstract

fetched live from OpenAlex

Commercial off the shelf operational amplifiers based on junction field-effect transistors and bipolar transistors were tested under gamma radiation at both room temperature and 77 K in parallel to determine their suitability for space applications. The irradiation while under cryogenic conditions simulates the environment that these devices would experience on small planetary missions where environmental control is not possible due to lack of energy generation capacity. The performance characteristics studied were: offset voltage, total harmonic distortion, change in open loop gain, and noise voltage. A single amplifier remained in specification through 100 krad(Si) and at 77 K. Differences in radiation tolerance were found between room temperature and cryogenic operation for the operational amplifiers under test. In some cases, the best performance was obtained at low temperatures while for others it was obtained at room temperature. The results highlight the need to perform these tests under operational conditions when extreme environment operation is required.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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