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Record W2613273958 · doi:10.1039/c7nr01422h

Nanostructural and photo-electrochemical properties of solution spin-coated Cu<sub>2</sub>ZnSnS<sub>4</sub>–TiO<sub>2</sub> nanorod forest films with an improved photovoltaic performance

2017· article· en· W2613273958 on OpenAlexafffund
Zhuoran Wang, Raynald Gauvin, George P. Demopoulos

Bibliographic record

VenueNanoscale · 2017
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCZTSNanorodMaterials scienceKesteriteSpin coatingX-ray photoelectron spectroscopyOptoelectronicsBand gapNanotechnologyDielectric spectroscopyRutileChemical engineeringThin filmElectrochemistryElectrodeChemistry

Abstract

fetched live from OpenAlex

Cu2ZnSnS4 (CZTS), other than in standard p–n junction device architecture, can be employed as a broad light absorber upon coating onto a wide bandgap electron conducting TiO2 film. Earlier CZTS sensitized TiO2 films have yielded low photoconversion efficiency and Voc. In this work, a water–ethanol solution spin coating approach has been applied to directly deposit CZTS nanocrystallites on rutile TiO2 nanorods grown on an FTO substrate (TNR) for evaluation in a sensitized solar cell configuration. The FTO@TNR@CZTS photoanode following controlled annealing is shown to exhibit improved photovoltaic properties. Focused-ion beam cross-sections of CZTS nanocoating onto TiO2 nanorod forest films have revealed nanoscale morphological details and electrochemical impedance spectroscopy helped identify TiO2 nanorod film growth characteristics for a reduced charge recombination. The band alignment of CZTS and TiO2 has been determined by XPS helping to explain the origin of Voc deficit. An all-solid state device featuring spiro OMeTAD as HTM and CdS as a buffer layer has been designed with 2% efficiency.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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