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Record W2604940478 · doi:10.1039/c7nr00201g

Phase transformation of TiO<sub>2</sub>nanoparticles by femtosecond laser ablation in aqueous solutions and deposition on conductive substrates

2017· article· en· W2604940478 on OpenAlex
Paola Russo, Robert Liang, Rui He, Y. Zhou

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanoscale · 2017
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsMaterials scienceSemiconductorPhotocatalysisLaser ablationTitanium dioxideBand gapChemical engineeringTin oxideFemtosecondSubstrate (aquarium)OptoelectronicsLaserNanoparticleLaser ablation synthesis in solutionNanotechnologyTin dioxideDopingLaser power scalingOpticsComposite materialMetallurgyChemistryX-ray laser

Abstract

fetched live from OpenAlex

Titanium dioxide (TiO2) is a wide bandgap semiconductor that is chemically stable, non-toxic, and economical compared to other semiconductors and has been implemented in a wide range of applications such as photocatalysis, photovoltaics, and memristors. In this work we studied the femtosecond laser ablation of titanium dioxide powders (P25) dispersed either in water or deposited onto a fluoride-doped tin oxide (FTO) substrate. The process was used as a route to induce the phase-transformation of TiO2 nanoparticles which was governed by laser parameters such as ablation time and power. It was observed that upon increase of the ablation time of TiO2 dispersion in water a bandgap widening occurred, leading to the possibility of bandgap engineering of TiO2 using controlled laser parameter profiles.

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.

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 score0.013
Threshold uncertainty score0.568

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 communication0.0000.001
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 head0.019
GPT teacher head0.243
Teacher spread0.223 · 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