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Record W4415387752 · doi:10.1002/cjce.70128

Unveiling the evolution of microstructural and optoelectronic properties of spray‐pyrolyzed <scp>ZnO</scp> thin films via tailoring the aerosol deposition time

2025· article· en· W4415387752 on OpenAlexvenueno aff
Chandrashekhar M. Mahajan, Sarang P. Gumfekar

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2025
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsnot available
FundersIndian Space Research Organisation
KeywordsThin filmCrystalliteCrystallinityBand gapDeposition (geology)NanorodSubstrate (aquarium)

Abstract

fetched live from OpenAlex

Abstract ZnO thin films with diverse thicknesses were deposited via the spray pyrolysis technique by varying the deposition time ( τ ). The XRD analysis shows an increase in polycrystallinity for films with an increase in τ ; however, all films exhibit predominant growth along the c ‐axis [002] direction. The FE‐SEM analysis shows the growth of well‐aligned ZnO nanorods upright on the substrate at τ = 20 min. EDS analysis confirms the high quality ZnO film formation with a slightly rich oxygen concentration. The films exhibit optical transmittance &gt;90%, with the highest of 95% when deposited for 24 min. There is a rise in crystallite size along with film thickness; however, bandgap energy ( E g ) declines with a rise in τ . The inverse relation of E g with Urbach energy ( E u ) is attributed to superior crystallinity at lower E u . Under optimal deposition time τ = 20 min, the film shows the highest dark conductivity 108.2 S/cm, free electron concentration η = 3.76 × 10 19 /cm 3 , and mobility μ = 17.98 cm 2 V −1 s −1 . For τ = 20 min, the film exhibits the best figure of merit, Φ TC‐H = 2.03 × 10 −3 Ω −1 , Φ TC‐H‐HR = 4.11 × 10 −2 Ω −1/12 , and the least sheet resistance, R s = 275 Ω/□.

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 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 score0.006
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.005
GPT teacher head0.168
Teacher spread0.164 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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