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Record W4392730517 · doi:10.1002/smll.202307807

The Multiple Roles of Na Ions in Highly Efficient CZTSSe Solar Cells

2024· article· en· W4392730517 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSmall · 2024
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsMinistry of Education and Child Care
FundersCentre of Excellence in Exciton ScienceNatural Science Foundation of Hunan ProvinceNational Natural Science Foundation of China
KeywordsKesteritePassivationCZTSMaterials scienceDopingIonDissolutionChalcopyriteEnergy conversion efficiencyLayer (electronics)Chemical engineeringOptoelectronicsNanotechnologyMetallurgyChemistryCopper

Abstract

fetched live from OpenAlex

Abstract Sodium (Na) doping is a well‐established technique employed in chalcopyrite and kesterite solar cells. While various improvements can be achieved in crystalline quality, electrical properties, or defect passivation of the absorber materials by incorporating Na, a comprehensive demonstration of the desired Na distribution in CZTSSe is still lacking. Herein, a straightforward Na doping approach by dissolving NaCl into the CZTS precursor solution is proposed. It is demonstrated that a favorable Na ion distribution should comprise a precisely controlled Na + concentration at the front surface and an enhanced distribution within the bottom region of the absorber layer. These findings demonstrated that Na ions play several positive roles within the device, leading to an overall power conversion efficiency of 12.51%.

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.

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)0.000
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 score0.256
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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