Optoelectronic transport properties in amorphous/crystalline silicon solar cell heterojunctions measured by frequency-domain photocarrier radiometry: Multi-parameter measurement reliability and precision studies
Bibliographic record
Abstract
A theoretical one-dimensional two-layer linear photocarrier radiometry (PCR) model including the presence of effective interface carrier traps was used to evaluate the transport parameters of p-type hydrogenated amorphous silicon (a-Si:H) and n-type crystalline silicon (c-Si) passivated by an intrinsic hydrogenated amorphous silicon (i-layer) nanolayer. Several crystalline Si heterojunction structures were examined to investigate the influence of the i-layer thickness and the doping concentration of the a-Si:H layer. The experimental data of a series of heterojunction structures with intrinsic thin layers were fitted to PCR theory to gain insight into the transport properties of these devices. The quantitative multi-parameter results were studied with regard to measurement reliability (uniqueness) and precision using two independent computational best-fit programs. The considerable influence on the transport properties of the entire structure of two key parameters that can limit the performance of amorphous thin film solar cells, namely, the doping concentration of the a-Si:H layer and the i-layer thickness was demonstrated. It was shown that PCR can be applied to the non-destructive characterization of a-Si:H/c-Si heterojunction solar cells yielding reliable measurements of the key parameters.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".