THE SURFACE AND INTERFACE BEHAVIOR OF EMITTER REGION OF SOLAR CELLS IN PRODUCT LINE
Bibliographic record
Abstract
Based on the Auger electron spectroscopy (AES) and X-ray photoelectron spectroscopy (XPS), the specific surface and interface characteristics of emitter region of commercial mono-crystal Si solar cells were examined. Four chemical compositions C , O , Si , and P were detected, and the atomic concentrations (%) of C and O at the surface were much higher than their solid solubility in mono-crystal Si . The high concentration of C and O at the surface was attributed to adhered remains. The single element Si , stable oxide SiO 2, as well as intermediate oxidation states such as Si 1+ and Si 3+ corresponding to Si 2 O and Si 2 O 3, respectively, have been analyzed. The atomic concentrations (%) of these compositions and their respective chemical states at the surface and interface are likely correlative to the various defects such as electronic-like ramification of hanging bonds, vacancy cluster, or dislocations. Furthermore, the normalized quantum efficiency (QE) of the solar cells made from the wafers was measured to be lower than 74% at short wavelength (< 400 nm), and the influence of surface and interface states on the performance of solar cells was discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".