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Record W2089494610 · doi:10.1063/1.4795262

The formation of Ti–O tetrahedra and band gap reduction in SiO2 via pulsed ion implantation

2013· article· en· W2089494610 on OpenAlexaff
R. J. Green, D. A. Zatsepin, Adrian Hunt, E.Z. Kurmaev, Н. В. Гаврилов, A. Moewes

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsUniversity of Saskatchewan
FundersU.S. Department of Energy
KeywordsMaterials scienceIonBand gapIon implantationFluenceAbsorption spectroscopyCrystal (programming language)Absorption edgeAmorphous solidValence (chemistry)DopingCrystal field theoryAtomic physicsCrystallographyChemistryOptoelectronicsOpticsPhysics

Abstract

fetched live from OpenAlex

Titanium ions are implanted into amorphous SiO2 at two different fluences using pulsed ion implantation, and the resulting samples are annealed. Bulk sensitive soft X-ray absorption spectroscopy of the Ti L2,3 edge reveal strikingly different spectra for the two fluences. Spectral simulations using multiplet crystal field theory show clearly that for low fluence the Ti ions have a local octahedral coordination, while at higher fluence the formation of Ti4+–O tetrahedra dominates. Using O K-edge X-ray absorption and emission, the effect of the Ti states on the valence and conduction bands of the host SiO2 is revealed. With the introduction of Ti tetrahedra, the band gap reduces from about 8 eV to just over 4 eV, due entirely to the Ti 3d conduction band states. These results demonstrate the possibility to obtain Ti–O tetrahedra in silica by Ti ion implantation and a suitable thermal treatment, clarify the mechanism of band gap reduction with Ti doping in SiO2, and demonstrate the sensitivity of L-edge X-ray absorption with a multiplet crystal field theory analysis to the Ti coordination of novel materials.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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 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

Citations12
Published2013
Admission routes1
Has abstractyes

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