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Record W2884528587 · doi:10.14447/jnmes.v21i1.520

Thermally Deposited Sb2S3: Bi Thin Films for Solar Cell Absorber

2018· article· en· W2884528587 on OpenAlexvenueno aff
Durai Chella Priya, Daniel Thanabalan, J. Henry, K. Mohanraj, G. Sivakumar, S. Thanikaikarasan, P.J. Sebastián

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2018
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsnot available
Fundersnot available
KeywordsPhotoluminescenceMaterials scienceThin filmBand gapDielectricOrthorhombic crystal systemSubstrate (aquarium)Analytical Chemistry (journal)OptoelectronicsDopingAbsorption (acoustics)Crystal (programming language)OpticsNanotechnologyDiffractionChemistryComposite materialPhysics

Abstract

fetched live from OpenAlex

In recent years there has been growing interest in the materials suitable for real time storage application. Sb2S3 is a prospective material in this regard due to good photoconductivity. In this contest, thin films of Sb2S3 and Bi3+ doped Sb2S3 were deposited onto the transparent glass substrate by thermal evaporation method. The structural, optical and electrical properties were investigated by XRD, UV-Visible, Photoluminescence, and Impedance spectroscopic techniques. The XRD patterns confirm the orthorhombic crystal structured Sb2S3 and the inclusion of Bi3+ ions in the crystal system. UV-Visible analysis exhibited wide optical absorption in the visible region for both Sb2S3 and Bi3+ doped films and their band gap energy was found to be 1.60 eV and 1.55 eV respectively. The photoluminescence spectra showed a strong emission at 361nm. The value of capacitance, dielectric constant and real part of impedance decreases with increasing frequency for both the samples.

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 score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.231
Teacher spread0.216 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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