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Record W2317615660 · doi:10.1021/acs.jpcc.5b01049

Photoelectrochemical and Physical Insight into Cu<sub>2</sub>ZnSnS<sub>4</sub> Nanocrystals Using Synchrotron Radiation

2015· article· en· W2317615660 on OpenAlexafffund
Daniel Vaccarello, Lijia Liu, Jigang Zhou, Tsun‐Kong Sham, Zhifeng Ding

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2015
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsCanadian Light Source (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaWestern UniversityCanada Foundation for Innovation
KeywordsCZTSPhotocurrentMaterials scienceXANESNanocrystalAbsorption (acoustics)StoichiometrySolar energy conversionMetalOptoelectronicsNanotechnologySolar energyBand gapChemistrySpectroscopyPhysical chemistryMetallurgyPhysics

Abstract

fetched live from OpenAlex

Cu 2 ZnSnS 4 (CZTS) nanocrystals were synthesized via a one-pot method and photoelectrochemical measurements (PECMs) were used to quantitatively compare CZTS films. Based on their initial metal stoichiometry and photoresponse behavior, CZTS films were divided into groups of high-photoresponse (hp-CZTS) and low-photoresponse samples (lp-CZTS). An X-ray absorption near-edge structure (XANES) study was then performed to unravel the origin of the difference in their photovoltaic properties. The results demonstrated that the local structures of the elements and their interaction with capping ligands are different and strongly affect the photovoltaic behavior, although both CZTS groups through one-pot synthesis were free of secondary phases. It was determined that the coordination of Zn and the capping ligand–metal interaction are the two major factors for the production of higher photocurrent. The correlations will guide us to produce viable CZTS films crucial for the development of solar energy conversion.

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 head0.012
GPT teacher head0.224
Teacher spread0.213 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicChalcogenide Semiconductor Thin FilmsFrench-language works237,207