Impact of Nano-FeS2 Layer on the Stability Performance of CdS-Cu2O PV Cells: A Study
Bibliographic record
Abstract
The presence of nano-structured FeS2 film at the junction of CdS-Cu2O thin film PV cells demonstrated long term stability in its performances. The CdS layer was fabricated by vacuum evaporation technique and its top surface was converted to FeS2 by dipping in hot FeCl2 solution. The Cu2O was deposited over it by plasma deposition process. A thin Ni-Au layer was deposited over the Cu2O surface by an electroless deposition process to act as the top electrical contact. The cell properties and its stability were studied under external stresses including heat and light. The cells efficiency attained 2.35% at AM1 illumination. The fabricated cells were tested under thermal cycling and light soaking and their performances were compared with other cells like Si, CdTe and CIS. Results showed that the CdS-Cu2O device with FeS2 is more stable than the other cells. From these results it was concluded that the nano FeS2 layer made perfect matching with n-CdS and p-Cu2O due to its strong inversion and yields both bulk electrons and surface holes. Moreover, the hardness of the FeS2 layer puts barriers that slow the inter-diffusion / migration of Cu ions into the bulk CdS thus preventing the formation of Cu-Cd killer centres.
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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 | 0.000 |
| 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".