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Record W2075038616 · doi:10.1063/1.2841419

The effect of the surface of SnO2 nanoribbons on their luminescence using x-ray absorption and luminescence spectroscopy

2008· article· en· W2075038616 on OpenAlexaff
X. T. Zhou, Jigang Zhou, Michael W. Murphy, J. Y. Peter Ko, F. Heigl, Tom Regier, R. I. R. Blyth, Tsun‐Kong Sham

Bibliographic record

VenueThe Journal of Chemical Physics · 2008
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsCanadian Light Source (Canada)University of SaskatchewanWestern University
Fundersnot available
KeywordsLuminescenceExcited statePhotoluminescenceIonMaterials scienceExcitationAnalytical Chemistry (journal)Absorption (acoustics)ChemistryAtomic physicsOptoelectronics

Abstract

fetched live from OpenAlex

X-ray excited optical luminescence (XEOL) and x-ray absorption near-edge structure in total electron, x-ray fluorescence, and photoluminescence yields at Sn M5,4-, O K-, and Sn K-edges have been used to study the luminescence from SnO2 nanoribbons. The effect of the surface on the luminescence from SnO2 nanoribbons was studied by preferential excitation of the ions in the near-surface region and at the normal lattice positions, respectively. No noticeable change of luminescence from SnO2 nanoribbons was observed if the Sn ions in the near-surface region were excited selectively, while the luminescence intensity changes markedly when Sn or O ions at the normal lattice positions were excited across the corresponding edges. Based on the experimental results, we show that the luminescence from SnO2 nanoribbons is dominated by energy transfer from the excitation of the whole SnO2 lattice to the surface states. Surface site specificity is not observable due to its low concentration and weak absorption coefficient although the surface plays an important role in the emission as a luminescence center. The energy transfer and site specificity of the XEOL or the lack of the site specificity from a single-phase sample is discussed.

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)0.001
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 score0.001
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.238
Teacher spread0.224 · 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

Citations16
Published2008
Admission routes1
Has abstractyes

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