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Record W4308527409 · doi:10.3390/ma15217849

Effect of Substrate Temperature on the Structural, Optical and Electrical Properties of DC Magnetron Sputtered VO2 Thin Films

2022· article· en· W4308527409 on OpenAlexafffund
Chunzi Zhang, Ozan Güneş, Shi-Jie Wen, Q. Yang, Safa Kasap

Bibliographic record

VenueMaterials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCisco SystemsSilicon Valley Community Foundation
KeywordsMaterials scienceElectrical resistivity and conductivityThin filmMicrostructureSputter depositionSubstrate (aquarium)TransmittanceHysteresisConductivitySputteringAnalytical Chemistry (journal)OptoelectronicsComposite materialCondensed matter physicsNanotechnologyChemistryElectrical engineering

Abstract

fetched live from OpenAlex

This study focuses on the effect of the substrate temperature (TS) on the quality of VO2 thin films prepared by DC magnetron sputtering. TS was varied from 350 to 600 °C and the effects on the surface morphology, microstructure, optical and electrical properties of the films were investigated. The results show that TS below 500 °C favors the growth of V2O5 phase, whereas higher TS (≥500 °C) facilitates the formation of the VO2 phase. Optical characterization of the as-prepared VO2 films displayed a reduced optical transmittance (T˜) across the near-infrared region (NIR), reduced phase transition temperature (Tt), and broadened hysteresis width (ΔH) through the phase transition region. In addition, a decline of the luminous modulation (ΔT˜lum) and solar modulation (ΔT˜sol) efficiencies of the as-prepared films have been determined. Furthermore, compared with the high-quality films reported previously, the electrical conductivity (σ) as a function of temperature (T) reveals reduced conductivity contrast (Δσ) between the insulating and metallic phases of the VO2 films, which was of the order of 2. These outcomes indicated the presence of defects and unrelaxed lattice strain in the films. Further, the comparison of present results with those in the literature from similar works show that the preparation of high-quality films at TS lower than 650 °C presents significant challenges.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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.

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

Citations16
Published2022
Admission routes2
Has abstractyes

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