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Record W4394683235 · doi:10.2351/7.0001345

Laser writing of memristive logic gates and crossbar arrays

2024· article· en· W4394683235 on OpenAlexafffund
Joshua Jones, Ningyue Mao, Peng Peng

Bibliographic record

VenueJournal of Laser Applications · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCrossbar switchMemristorLaserLogic gateOptoelectronicsElectronic engineeringOpticsPhysicsEngineering

Abstract

fetched live from OpenAlex

Memristor-based logic circuits are gaining a lot of attention due to the potential for high logic density hardware and novel in-memory computing applications. Readily available methods for fabricating of memristor logic structures that are suitable for integration with conventional computer hardware are a growing need. This work presents a direct laser writing process capable of rapidly fabricating memristor logic circuits by laser irradiation of metal salt precursor solutions. Planar memristor patterns are fabricated, and their I–V response is characterized. Boolean logic gates are fabricated from planar memristor pairs that exhibit low programming voltages and rapid switching. Cu/Cu2O/Cu and Ag/Cu2O/Cu memristors are also fabricated in crossbar arrays, showing the ability to be programmed to multiple resistance states through ultrashort voltage pulses. The devices also show the potential to have high endurance and nonvolatile resistance state retention.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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