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Record W2007873086 · doi:10.1109/memsys.2015.7051140

Biocompatible circuit-breaker chip for temperature regulation of electrothermally driven smart implants

2015· article· en· W2007873086 on OpenAlexafffund
Yi Luo, Masoud Dahmardeh, Kenichi Takahata

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCircuit breakerOverheating (electricity)MiniaturizationChipMaterials scienceElectrical engineeringMicrosystemBiocompatible materialActuatorComputer scienceNanotechnologyEngineeringBiomedical engineering

Abstract

fetched live from OpenAlex

This paper presents a thermoresponsive micro circuit breaker for biomedical applications specifically targeted at implantable microsystems. The circuit breaker is micromachined to have a shape-memory-alloy cantilever actuator as a normally closed temperature-sensitive switch to protect the device of interest from overheating, a critical safety feature for smart implants including those that are electrothermally driven. The micro breaker is constructed using biocompatible materials in a form of 1.5×2.0×0.46 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> Ti-packaged chip and exhibits a cold-state resistance of 14 Ω. The chip functionality is tested in combination with a wireless resonant heater powered by radio-frequency electromagnetic radiation, demonstrating self-regulation of heater temperature. The developed breaker chip operates in a fully passive manner, contributing to the miniaturization of smart implants in which thermal management is essential.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.004
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.062
GPT teacher head0.270
Teacher spread0.209 · 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.

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 routes2
Has abstractyes

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