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Record W4283510959 · doi:10.1002/aelm.202200353

Hydrogen Atom Doping—A Versatile Method for Modulated Interface Resistive Switching

2022· article· en· W4283510959 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

VenueAdvanced Electronic Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceDopingOxideSchottky barrierOptoelectronicsHydrogenResistive touchscreenMemristorLayer (electronics)Atom (system on chip)MetalInterface (matter)Schottky diodeNanotechnologyElectronic engineeringElectrical engineeringComposite materialDiodeComputer science

Abstract

fetched live from OpenAlex

Abstract Interface kinetics plays a crucial role in modulating the resistive switching mechanism for memristor devices with a Schottky junction. This study introduces H atoms by catalytic doping and examines the interfacial electrical transfer characteristics of the Pd/Nb‐doped SrTiO 3 (Nb‐STO). The I–V measurements show that H + doping at the Pd/Nb‐STO interface reduces the barrier height by 300 mV compared to the sample before H + doping. This reduction in barrier height is further correlated with the decrease in built‐in potential by 300 mV and depletion layer thickness from C–V measurements. The underlying reason for such a drastic change in resistive switching characteristics is the reduction of interface layer thickness. The work highlights the easy use of Pd metal to introduce H atoms to oxide materials and provides insight into their effects on switching mechanisms.

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 score0.312
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
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.269
Teacher spread0.261 · 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