Characterization Process of Silicon Solar Cell in BAEC Lab
Bibliographic record
Abstract
This paper represents the characterization process of mono-facial solar cell in Bangladesh Atomic Energy Commission (BAEC) Lab. Mono-facial solar cell characterization performance analysis using surface reflection method, Sheet resistance method, SEM, Surface photo voltage and LIV test. The morphology of silicon wafer surface has been studied using scanning electron microscopy. It is found that the pyramid type structures are formed on the textured surface which helps to trap more light during conversion to electricity. The sheet resistance of raw and diffused sample is measured by using four point probe method. Results show that the resistivity of the wafer is decreased after diffusion which indicates the formation of n-type layer during diffusion process. The surface photo voltage data is used to find the diffusion length and life time. It is found the diffusion length 81.5μm and life time is 2.5μs. Finally, the efficiency of monofacial solar cell measured by LIV tester. Results show that the monofacial solar cell achieved fill factor (FF) of 0.310423 with a conversion efficiency (η) of 5.193843% where the active surface area is 96 cm2.
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) | 0.004 | 0.001 |
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".