Carrier-density-wave transport property depth profilometry using spectroscopic photothermal radiometry of silicon wafers II: Experimental and computational aspects
Bibliographic record
Abstract
The experimental verification of a previously presented theoretical model for the photothermal radiometric (PTR) signal from an Si wafer excited by a laser of arbitrary wavelength is presented. A multiparameter fitting algorithm is developed and is used to fit experimental frequency scans to the theoretical model. The recombination lifetime and surface recombination velocity values extracted from the fits are consistent for all of the experiments performed. The diffusion coefficients for the more strongly absorbed excitation wavelengths are greater than those measured when using deeper penetrating excitation wavelengths. This discrepancy is discussed in terms of the dependence of the PTR signal on injected carrier densities and the nonlinearity of the PTR signal with temperature. The sensitivity of the PTR signal to a localized defect is shown to increase with the proximity of the defect to the centroid of the injected carrier density. The method amounts to carrier-density-wave depth profilometry of the relevant electronic transport parameters.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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".