Ultrahigh-Frequency Heterodyne Lock-In Carrierography for Large-Scale Quantitative Multi-Parameter Imaging of Colloidal Quantum Dot Solar Cells
Bibliographic record
Abstract
Ultrahigh-frequency heterodyne lock-in carrierography (UHF-HeLIC) is a new near-IR dynamic photoluminescence (PL) camera-based large-area imaging technique. It is specifically developed for investigating dynamic optoelectronic events that occur at very fast diffusion-wave rates (> = 10 kHz), above which conventional camera imaging cannot be achieved. The nonlinear combination of two-frequency-modulated photogenerated carrier density waves (CDWs) with a 10 Hz beat frequency was used to generate HeLIC images in the UHF range (up to 270 kHz) above the effective CDW recombination rate. Using sequences of these high-frequency images and UHF-HeLIC theory, carrier lifetime, diffusivity, and diffusion and drift length images were reconstructed from colloidal quantum dot solar cells and used for studying the influence of surface and interface trap states on photocarrier transport processes. The new non-destructive UHF-HeLIC imaging methodology shows excellent potential for industrial in-line photovoltaic device characterization, fundamental optoelectronic physical process studies, and various other photoelectronic applications.
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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".