Two-beam cross-modulation photocarrier radiometry: principles and contrast amplification in semiconductor subsurface imaging
Bibliographic record
Abstract
A two-beam photo-carrier radiometry (PCR) technique of semiconductors has been developed. The technique operates on the superposition of superband-gap and subband-gap laser beams which results in the cross-modulation of the backscattered subband-gap laser intensity by the harmonically varying free-carrier-wave density-dependent infrared absorption coefficient. A theory of this two-beam cross-modulation approach and various experimental configurations applied to the imaging of electronic contamination and defects in silicon wafers are presented. Owing to the nonlinear interaction of the two beams, the configuration revealed a new optoelectronic effect, the decrease of the residual subband-gap absorption coefficient due to the decreased carrier capture cross-section brought about by the depletion of occupied band-gap states in the presence of photons produced by radiative recombination. Quantitative values of the optoelectronic constant B associated with the rate of depletion of free-carrier capture cross-section with superband-gap intensity, as well as of IeR, the intensity of radiative recombination emissions, were obtained. These values cannot be measured by conventional PCR or other single-ended optoelectronic techniques. The theory explains the experimental dependence of electronic transport properties on the intensity of the subband-gap beam and accounts for optoelectronic imaging contrast amplification in contaminated or defect semiconductors. The two-beam cross-modulation PCR was further shown to enhance the imaging contrast of a certain electronic contamination type (Fe in p-Si). A dramatic phase contrast enhancement of subsurface defects made by low-dose proton implantation was demonstrated at superband-gap laser intensity levels one order of magnitude lower than possible with single-ended optoelectronic imaging methodologies. This is tentatively attributed to relatively low-injection trap-filling well below optoelectronic trap saturation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".