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Record W2596785910 · doi:10.1166/jnn.2017.13310

The Morphology of TiO<sub>2</sub> Nanotube Arrays Grown from Atomically Peened and Non-Atomically Peened Ti Films

2017· article· en· W2596785910 on OpenAlexaff
Samira Farsinezhad, Arash Mohammadpour, Mourad Benlamri, Ashley N Dalrymple, Karthik Shankar

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceThin filmSubstrate (aquarium)NanotechnologySputteringTitaniumChemical engineeringNanotubeAnodizingComposite materialCarbon nanotubeMetallurgy

Abstract

fetched live from OpenAlex

The growth of TiO2 nanotube arrays (TNTAs) on non-native substrates is essential for exploiting the full potential of this nanoarchitecture in applications such as gas sensing, biosensing, antifouling coatings, low-cost solar cells, drug-eluting bimedical implants and stem-cell differentiators. The direct formation of anodic TNTAs on non-native substrates requires the vacuum deposition of a thin film of titanium on the substrate followed by subsequent electrochemical anodization of the film. In this report, we studied the effect of atomic peening on the formation of Ti thin films on technologically important non-native substrates. We compared the structure and morphology of evaporated and sputtered Ti films, and correlated them to the morphology of the vertically oriented TiO2 nanostructures that resulted subsequent to anodization of those films. We calculated a minimum value of 1.33 eV/atom for the energy of refkected neutral Ar species arriving at the substrate when a chamber pressure of 1 mTorr is used during the sputter deposition of Ti. Previous approaches relied on substrate heating to elevated temperatures during Ti thin film deposition or ion-beam assisted Ti thin film deposition as a prerequisite to form TiO2 nanotube arrays (TNTAs). We demonstrated TNTAs on a variety of substrates at room temperature using both evaporated and sputtered Ti films without recourse to ion-beam sources. Evaporated Ti films were found to possess small grain size and high local surface roughness, which resulted in nanotubes with extremely rough sidewalls. Ti thin films formed by Ar+ ion sputtering at commonly used chamber pressures of 7–20 mTorr at substrate temperatures ranging from room-temperature to 250 °C possessed a highly rough surface and three-dimensional grains, which precluded the formation of ordered nanotubes upon anodization due to highly non-uniform pore nucleation processes. In contrast, Ti thin films sputtered at low chamber pressures of 0.8–2 mTorr had a low surface roughness due to the atomic peening process. Such films, even when deposited at room temperature, resulted in ordered nanotube arrays upon anodization.

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 score0.003

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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