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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 OpenAlexafffund
Paola Russo, Robert Liang, Rui He, Y. Zhou

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.

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 score0.002

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 head0.019
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

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

Citations27
Published2017
Admission routes2
Has abstractyes

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