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Growth conditions effects on the H<sub>2</sub>and CO<sub>2</sub>gas sensing properties of Indium Tin Oxide

2016· article· en· W2347202393 on OpenAlexaff
Sadna Isik, Ömer Çoban, Cyrus Shafai, S. Tüzemen, Emre Gür

Bibliographic record

VenueJournal of Physics Conference Series · 2016
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndiumIndium tin oxideTinMaterials scienceOxideInorganic chemistryChemical engineeringEngineering physicsMetallurgyNanotechnologyChemistryPhysicsThin filmEngineering

Abstract

fetched live from OpenAlex

Indium Tin Oxide (ITO) thin films are transparent conducting wide bandgap oxide. In this study investigated optical, structural and morphological properties of sputtered ITO thin films using X-ray diffraction spectroscopy (XRD), Scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDX) and optical absorption techniques. These measurements revealed that the oxygen gas percentage present in the ITO film deposited by RF magnetron sputter deposition showed systematic variation of its band gap, crystal orientation, growth rate, figure of merit (FOM) and dominant XRD peaks. All the thin films deposited at room temperature (RT). Once characterization of the films carried out, H 2 and CO 2 resistive gas sensors fabricated by depositing the ITO film on top of aluminium interdigitated contacts/electrode (IDE), that fabricated following lithography and etching processes. These devices showed reasonable sensitivity for pure H 2 and CO 2 at elevated temperature. A correlation found between the thin film properties of the ITO and its sensing capability for H 2 and CO 2 , which these gases are important in many fields such as automotive, energy, biological and health-related applications.

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 head0.014
GPT teacher head0.188
Teacher spread0.175 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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