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Record W2287729434 · doi:10.14447/jnmes.v13i1.192

Characterization of Electrodeposited Copper Sulphide Thin Films

2010· article· en· W2287729434 on OpenAlexvenueno aff
S. Thanikaikarasan, T. Mahalingam, A. Kathalingam, Hosun Moon, Yong Deak Kim

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2010
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsnot available
Fundersnot available
KeywordsThin filmScanning electron microscopeCopperIndium tin oxideCyclic voltammetryIndiumMaterials scienceAnalytical Chemistry (journal)StoichiometryBand gapCopper oxideAbsorption (acoustics)Aqueous solutionDeposition (geology)ElectrochemistryChemistryElectrodeNanotechnologyMetallurgyComposite materialOptoelectronicsPhysical chemistry

Abstract

fetched live from OpenAlex

Copper Sulphide (CuS) thin films were electrodeposited onto indium doped tin oxide coated conducting glass (ITO) substrates from an aqueous acidic bath containing CuSO4, Na2S2O3 and EDTA. The deposition mechanism was investigated using cyclic voltammetry. The appropriate potential region in which the formation of stoichiometric CuS thin films occurs was found to be -500 mV versus SCE and the solution pH was maintained at 3.0 p 0.1. X-ray diffraction studies revealed that the deposited films are found to be cubic structure with preferential orientation along (111) plane. Optical absorption measurements were used to estimate the band gap value of CuS thin films deposited at different bath temperatures. Surface morphology and film composition was analyzed using an energy dispersive x-ray analysis (EDAX) set up attached with scanning electron microscope (SEM), respectively. The experimental observations are discussed in detail.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of New Materials for Electrochemical SystemsSame topicChalcogenide Semiconductor Thin FilmsFrench-language works237,207