Cu nanoparticles enable plasmonic-improved silicon photovoltaic devices
Bibliographic record
Abstract
This work examines the effect of copper nanoparticles (Cu NPs) on the photocurrent efficiency of silicon photovoltaic (Si PV) devices. An optimized synthesis of stable Cu NPs is reported together with a procedure for their immobilization on the Si PV surface. A comprehensive analysis of the photocurrent and power dependence of the Cu NPs surface coverage and size is presented. A decrease in photoconversion was observed for wavelengths shorter than ~500 nm, due to the Cu interband absorption. In the low surface coverage limit, where the level of aggregation was found to be low, the surface plasmon resonance absorption dominates leading to a modest effect on the photocurrent response. As the number of aggregates increased with the surface coverage, the photocurrent efficiency also increased, and a maximum enhancement power conversion of 16% was found for a 54 ± 6 NPs per μm(2) PV cell. This enhancement was attributed to SPR light scattering and trapping into the Si PV device. Higher surface coverage yielded numerous aggregates which acted as a bulk coating and caused a decrease in both photocurrent and power measurements.
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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".