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Record W4322762923 · doi:10.35848/1882-0786/acc0d2

Demonstration of electronic synapses using a sericin-based bio-memristor

2023· article· en· W4322762923 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Physics Express · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNeuromorphic engineeringMemristorSericinMaterials scienceConductanceVoltageSynaptic plasticityPlasticitySpike-timing-dependent plasticityOptoelectronicsNeuroscienceComputer scienceBiological systemElectronic engineeringArtificial neural networkElectrical engineeringSILKChemistryPhysicsArtificial intelligenceEngineeringBiologyComposite material

Abstract

fetched live from OpenAlex

Abstract The bio-memristor based on biomaterial has ushered in enthusiasm and optimism in brain-inspired computing systems. Here, the bio-memristor based on sericin has been fabricated with the structure of Ag/sericin/W. The sericin-based bio-memristors demonstrated threshold-switching behavior with low set voltage (∼0.25 V), good cycle-to-cycle uniformity (∼400 cycles), and a large switching window (>100). Interestingly, the device conductance was tuned gradually by the modulation of voltage pulses (amplitude, number, and frequency). The synaptic behaviors can be mimicked, i.e., short-term plasticity, spike-rate-dependent plasticity, and spike-timing-dependent plasticity. This work may open new avenues of bio-memristors in brain-inspired neuromorphic systems.

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.

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 score0.215
Threshold uncertainty score0.533

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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