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Record W2517284405 · doi:10.1021/acs.nanolett.6b01800

Surface Properties from Transconductance in Nanoscale Systems

2016· article· en· W2517284405 on OpenAlexaff
David Lynall, Kristopher Byrne, A. Shik, Selvakumar V. Nair, Harry E. Ruda

Bibliographic record

VenueNano Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNanowireTransconductanceMaterials scienceConductanceNanoscopic scaleOptoelectronicsField-effect transistorTransistorCondensed matter physicsScalingSurface statesNanotechnologyVoltageSurface (topology)Physics

Abstract

fetched live from OpenAlex

Because of the continued scaling of transistor dimensions and incorporation of nanostructured materials into modern electronic and optoelectronic devices, surfaces and interfaces have become a dominant factor dictating material properties and device performance. In this study, we investigate the temperature-dependent electronic transport properties of InAs nanowire field-effect transistors. A point where the nanowire conductance becomes independent of temperature is observed, known as the zero-temperature-coefficient. The distribution of surface states is determined by a spectral analysis of the conductance activation energy and used to develop a carrier transport model that explains the existence and gate voltage dependence of this point. We determine that the position of this point in gate voltage is directly related to the fixed oxide charge on the nanowire surface and demonstrate the utility of this method for studying surface passivations in nanoscale systems by characterizing (NH 4 ) 2 S x and H 2 plasma surface treatments on InAs nanowires.

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 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 score0.045
Threshold uncertainty score0.436

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 head0.023
GPT teacher head0.197
Teacher spread0.174 · 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 teacher head, 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

Citations11
Published2016
Admission routes1
Has abstractyes

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