The impact of processing on the optical absorption onset of CdTe thin-films and solar cells
Bibliographic record
Abstract
We critically examine how two processing steps commonly applied in the preparation of cadmium telluride (CdTe)-based solar cells, i.e., the cadmium chloride treatment and the subsequent stepwise bromine/methanol wet etching process, impact the structural and optical properties of polycrystalline CdTe thin-films. In particular, drawing upon a conjuncture of photothermal deflection spectroscopy and spectroscopic ellipsometry experimental results, we determine the spectral dependence of the optical absorption coefficient, α(E), over the photon energy range from 1.1 to 2.0 eV for samples of rf sputtered (RFS) and close space sublimation (CSS) CdTe. The impact of these processing steps on shaping the grazing incidence x-ray diffraction pattern is also examined. We extend the analysis to devices through interpretation of the spectral dependence of the external quantum efficiency associated with two cadmium chloride treated CdTe-based solar cells. The cells are comparably prepared with the exception of the absorber, one by RFS and the other by CSS. Through the use of our results for the thin-film CdTe optical functions and a model for the solar cell multilayer structure, we simulate the resultant external quantum efficiency spectrum. Through a critical contrast with the corresponding solar cell acquired experimental results, we glean insights into the carrier trapping and recombination processes that occur within the two types of CdTe absorbers.
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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 | 0.001 |
| 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 | 0.001 | 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".