Effect of an optimal oxide layer on the efficiency of graphene‐silicon Schottky junction solar cell
Bibliographic record
Abstract
Summary The harvesting of solar energy through silicon/graphene Schottky junction photovoltaic cell has been widely investigated in the last decade but the surface recombination at interface limits the high conversion efficiency. We have demonstrated the utilization of the optimum thickness (1.5 nm) of Al2O3 between the interfaces of graphene and n‐type Si as an interlayer to reduce the surface recombination along with chemical doping of perfluorinated polymeric sulfonic acid (PFSA) is used as a p‐type dopant to modulate the work function of graphene. The Kelvin probe force microscopy (KPFM) analysis revealed that the p‐doping enhances the graphene work function from 4.65 to 4.8 eV. The transport measurements are performed to study the shift in charge neutrality point of graphene. Furthermore, the effect of PFSA doping on graphene is also confirmed through Raman spectroscopy. The maximum value of power conversion efficiency (PCE) was found to be 13.52% (100 mW cm−2, AM 1.5) by introducing an optimal oxide layer and PFSA doping. The device exhibits the photoresponsivity of 0.10 AW−1. We believe that our findings will provide a route toward the development of new photovoltaic (PV) cells.
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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".