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Surface and near surface defects in<i>δ</i>-doped Si(1 1 1)

2015· article· en· W2078303563 on OpenAlexafffund
Daiane Silva de Andrade, R. H. Miwa, Benedict Drevniok, P Drage, A. B. McLean

Bibliographic record

VenueJournal of Physics Condensed Matter · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSurface and Thin Film Phenomena
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaAkademie Věd České RepublikyConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsScanning tunneling microscopeDangling bondAtomic orbitalDopingEquilateral triangleSurface (topology)Surface reconstructionCondensed matter physicsQuantum tunnellingAb initioMaterials scienceMolecular physicsSiliconCrystallographyMicroscopyChemistryNanotechnologyPhysicsGeometryOptoelectronicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

The B/Si(1 1 1)- (√3 x √3)R30° surface reconstruction has recently been used as a platform for supramolecular assembly. However, our understanding of the native defects in this delta-doped system and their corresponding scanning tunnelling microscopy (STM) signatures is incomplete. So we have studied this system using ab initio total energy calculations and scanning tunneling microscopy. We find that although perturbations to the equilibrium geometry of the surface are in general weak, the perturbations to the electronic structure can be quite strong due to the presence of dangling bonds composed of Si-3p(z) orbitals. Additionally, we propose a possible structure for a previously unidentified defect that appears in positive bias constant-current STM images as an equilateral triangular arrangement of Si adatoms with attenuated intensity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.714

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 head0.022
GPT teacher head0.249
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

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 designObservational
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

Citations6
Published2015
Admission routes2
Has abstractyes

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