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Analog Resistance Switching in Single Tungsten Oxide Nanoparticle Devices

2022· article· en· W4312328889 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

Venue2022 IEEE 22nd International Conference on Nanotechnology (NANO) · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Alberta
FundersDeutsche Forschungsgemeinschaft
KeywordsMaterials scienceNeuromorphic engineeringTungstenElectrodeNanoparticleNanotechnologyOptoelectronicsSputteringOxideNanolithographyThin filmFabricationComputer scienceChemistryArtificial neural networkMetallurgy

Abstract

fetched live from OpenAlex

Analog resistance switching in single tungsten oxide (WOx) nanoplatelets (NPs) with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sim 100\ \text{nm}$</tex> edge length sandwiched in-between a tungsten (W) and a palladium (Pd) electrode is reported. The top contact, individually aligned to each NP, was fabricated using a combination of tailored planarization techniques, nanolithography and sputter deposition. Electrical characterization revealed pronounced analog resistive switching behavior of this material composition, with gradually increasing or decreasing maximum currents for a sequence of positive or negative voltage sweeps, respectively. The switching can be assigned to a formed oxygen vacancy path in the WOx layer. Chemically synthesized NPs with analog switching behavior are promising nanoscale building blocks for the bottom-up formation of 3D memristive structures, which may eventually self-assemble into complex neuromorphic computing circuitry.

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 categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.254
Teacher spread0.227 · 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