Improvement of the physical properties of ZnO/CdTe core-shell nanowire arrays by CdCl2 heat treatment for solar cells
Bibliographic record
Abstract
CdTe is an important compound semiconductor for solar cells, and its use in nanowire-based heterostructures may become a critical requirement, owing to the potential scarcity of tellurium. The effects of the CdCl2 heat treatment are investigated on the physical properties of vertically aligned ZnO/CdTe core-shell nanowire arrays grown by combining chemical bath deposition with close space sublimation. It is found that recrystallization phenomena are induced by the CdCl2 heat treatment in the CdTe shell composed of nanograins: its crystallinity is improved while grain growth and texture randomization occur. The presence of a tellurium crystalline phase that may decorate grain boundaries is also revealed. The CdCl2 heat treatment further favors the chlorine doping of the CdTe shell with the formation of chlorine A-centers and can result in the passivation of grain boundaries. The absorption properties of ZnO/CdTe core-shell nanowire arrays are highly efficient, and more than 80% of the incident light can be absorbed in the spectral range of the solar irradiance. The resulting photovoltaic properties of solar cells made from ZnO/CdTe core-shell nanowire arrays covered with CuSCN/Au back-side contact are also improved after the CdCl2 heat treatment. However, recombination and trap phenomena are expected to operate, and the collection of the holes that are mainly photo-generated in the CdTe shell from the CuSCN/Au back-side contact is presumably identified as the main critical point in these solar cells.
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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 | 0.000 |
| 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".