The mean crystallite size within a hydrogenated nanocrystalline silicon based photovoltaic solar cell and its role in determining the corresponding crystalline volume fraction
Bibliographic record
Abstract
We examine the dependence of the crystalline volume fraction on the mean crystallite size for hydrogenated nanocrystalline silicon based photovoltaic solar cells; this work builds upon an earlier study by Schmidt et al. (Mater. Res. Soc. Symp. Proc. 1536 (2013)). For each photovoltaic solar cell considered, the X-ray diffraction and Raman spectra are measured. Through the application of Scherrer’s equation, the X-ray diffraction results are used to determine the corresponding mean crystallite sizes. Through peak decomposition, the Raman results are used to estimate the corresponding crystalline volume fraction. Plotting the crystalline volume fraction as a function of the mean crystallite size, it is found that larger mean crystallite sizes tend to favor reduced crystalline volume fractions. The ability to randomly pack smaller crystallites with a greater packing fraction than their larger counterparts was suggested as a possible explanation for this observation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".