MétaCan
Menu
Back to cohort
Record W3003725703 · doi:10.1063/1.5140994

Investigation of resistive switching and transport mechanisms of Al2O3/TiO2−<i>x</i> memristors under cryogenic conditions (1.5 K)

2020· article· en· W3003725703 on OpenAlexafffund

Bibliographic record

VenueAIP Advances · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueInstitut quantiqueUniversité de Sherbrooke
FundersH2020 Excellent ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsMemristorThermal conductionQuantum tunnellingDiodeResistive touchscreenElectrical conductorConductanceCommutationNegative resistance

Abstract

fetched live from OpenAlex

Resistive switching and transport mechanisms of Al2O3/TiO2−x memristor crosspoint devices have been investigated at cryogenic temperatures down to 1.5 K, for the future development of memristor-based cryogenic electronics. We report successful resistive switching of our devices in the temperature range of 300–1.5 K. The current–voltage curves exhibit negative differential resistance effects between 130 K and 1.5 K, attributed to a metal–insulator transition of the Ti4O7 conductive filament. The resulting highly nonlinear behavior is associated with an ION/IOFF diode ratio of 84 at 1.5 K, paving the way for selector-free cryogenic passive crossbars. Temperature-dependent thermal activation energies related to the conductance at low bias (20 mV) are extracted for memristors in a low resistance state, suggesting hopping-type conduction mechanisms. Finally, the transport mechanism analysis at 1.5 K indicates that for all resistance states, the conduction follows the space-charge limited current model in low fields, whereas trap-assisted tunneling dominates in higher fields.

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 score0.003

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 head0.020
GPT teacher head0.226
Teacher spread0.206 · 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

Citations27
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAIP AdvancesSame topicAdvanced Memory and Neural ComputingFrench-language works237,207