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Record W1995171978 · doi:10.1063/1.4868297

Electronic band gap reduction and intense luminescence in Co and Mn ion-implanted SiO2

2014· article· en· W1995171978 on OpenAlexafffund
R. J. Green, D. A. Zatsepin, D. J. St. Onge, E.Z. Kurmaev, Н. В. Гаврилов, A. F. Zatsepin, A. Moewes

Bibliographic record

VenueJournal of Applied Physics · 2014
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsUniversity of Saskatchewan
FundersBasic Energy SciencesRussian Academy of SciencesNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchLawrence Berkeley National LaboratoryWestern Economic Diversification CanadaRussian Science FoundationNational Science CouncilOffice of ScienceCanadian Light SourceU.S. Department of Energy
KeywordsLuminescenceIonIon implantationImpurityManganeseBand gapCobaltMaterials scienceValence (chemistry)OxygenAnalytical Chemistry (journal)Electronic structureAtomic physicsChemistryInorganic chemistryOptoelectronicsComputational chemistryMetallurgyPhysics

Abstract

fetched live from OpenAlex

Cobalt and manganese ions are implanted into SiO2 over a wide range of concentrations. For low concentrations, the Co atoms occupy interstitial locations, coordinated with oxygen, while metallic Co clusters form at higher implantation concentrations. For all concentrations studied here, Mn ions remain in interstitial locations and do not cluster. Using resonant x-ray emission spectroscopy and Anderson impurity model calculations, we determine the strength of the covalent interaction between the interstitial ions and the SiO2 valence band, finding it comparable to Mn and Co monoxides. Further, we find an increasing reduction in the SiO2 electronic band gap for increasing implantation concentration, due primarily to the introduction of Mn- and Co-derived conduction band states. We also observe a strong increase in a band of x-ray stimulated luminescence at 2.75 eV after implantation, attributed to oxygen deficient centers formed during implantation.

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 score0.023
Threshold uncertainty score0.243

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 head0.014
GPT teacher head0.231
Teacher spread0.218 · 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

Citations18
Published2014
Admission routes2
Has abstractyes

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