Preparation and Performance Research of CuInSe<sub>2</sub> Materials Applied in Solar Cell
Bibliographic record
Abstract
At present, CuInSe2 (referred to as CIS) semiconductor has become one of the hot points in solar cell field at home and abroad for its excellent performances, such as direct bandgap, high light absorption coefficient, high photoelectric conversion efficiency and long-term stability. In this paper, the CIS bulk materials are prepared by the horizontal Bridgman method with double-heat sources, the crystal structure, microstructure morphology and composition of the samples are analyzed in X-ray diffraction instrument (XRD) and scanning electronic microscope (SEM) with Energy Dispersive X-ray Spectrum (EDX), and surface electrical state and electrical properties of the samples are characterized in X-ray photoelectron spectroscopy (XPS) and four point resistivity test system. The results show that the CIS crystal was grown, and that the conductive performance of the samples is good which display the characteristics of p-type semiconductor. Furthermore, a thin film CIS sample was obtained by argon ion-beam scanning bombardment, and it has high solar energy absorptivity and the bandgap of 0.99 eV analyzed in Ultraviolet-visible Spectrum that is suitable for solar cell. Keywords: Solar
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".