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Record W3008577912 · doi:10.1039/d0nr00037j

Spin-polarized quantum transport in Si dangling bond wires

2020· article· en· W3008577912 on OpenAlexafffund
Qi An, Chen Hu, Guanghua Yu, Hong Guo

Bibliographic record

VenueNanoscale · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsMcGill University
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDangling bondSpin (aerodynamics)Condensed matter physicsQuantumMaterials scienceSiliconPhysicsOptoelectronicsQuantum mechanics

Abstract

fetched live from OpenAlex

We report theoretical modeling of spin-dependent quantum transport properties of dangling bond wires (DBWs) on the Si(100)-2 × 1:H surface. A single spin-polarized dangling bond center (DBC) near the DBW may strongly affect transport as characterized by anti-resonances or dips in the transmission spectra. Such spin-dependent gating can be effective up to a distance of 1.5 nanometer between the DBW and the DBC. At the energies where anti-resonances occur, the scattering states of the system are found to be "attracted" to the DBC - rather than moving forward to the existing electrode. The variety of gating effects can be well organized by a physical picture, i.e. a strong hybridization or interaction between the spin-polarized DBW and DBC occurs with the same spin polarization (at DBW and DBC) and at similar energy. The sharp spin-resolved anti-resonance in the DBW gives rise to a spin-filtering effect up to 100% efficiency.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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 designSimulation or modeling
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

Citations4
Published2020
Admission routes2
Has abstractyes

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