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Record W2510680706 · doi:10.1021/acs.jpcc.6b07613

Unfolding the Anatase-to-Rutile Phase Transition in TiO<sub>2</sub> Nanotubes Using X-ray Spectroscopy and Spectromicroscopy

2016· article· en· W2510680706 on OpenAlexafffund
Jun Li, Zhiqiang Wang, Jian Wang, Tsun‐Kong Sham

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2016
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsCanadian Light Source (Canada)University of SaskatchewanWestern University
FundersWestern UniversityNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsAnataseMaterials scienceRutileLuminescenceNanotechnologyNanocrystalSpectroscopyChemical engineeringPhase (matter)Phase transitionOptoelectronicsPhotocatalysisChemistry

Abstract

fetched live from OpenAlex

This work reports a study of the anatase-to-rutile phase transition (ART) in a highly ordered TiO 2 nanotube (NT) specimen fabricated using an electrochemical process followed by thermal annealing at 750 °C (NT750). Two-dimensional X-ray absorption near-edge structure–X-ray excited optical luminescence spectroscopy reveals the hierarchically two-layered structure of NT750 by resolving the surface anatase luminescence and bulk rutile optical emission. Scanning transmission X-ray microscopy analysis of a sliced NT750 lamella spatially differentiates the top nanotubular anatase structure from the denser rutile bottom layer with a gradual ART interface layer. On the basis of these results together with the known behavior of size and anisotropy dependence of ART in TiO 2 nanocrystal, we propose the “bottom-up” mechanism for ART in anodic TiO 2 NTs. This result is particularly relevant to the fundamental understanding of phase transition in nanostructures as well as the fabrication of desired TiO 2 NT mixed-phase composite with an excellent control of the anatase/rutile phase ratio.

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 score0.004
Threshold uncertainty score0.412

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 head0.009
GPT teacher head0.284
Teacher spread0.275 · 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

Citations25
Published2016
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicAdvanced Photocatalysis TechniquesFrench-language works237,207