Three-layer photocarrier radiometry model of ion-implanted silicon wafers
Bibliographic record
Abstract
A three-dimensional three-layer model is presented for the quantitative understanding of the infrared photocarrier radiometry (PCR) response of ion-implanted semiconductors, specifically Si. In addition to the implanted layer and intact substrate normally assumed in all existing two-layer theoretical models to describe the photothermal response of ion-implanted semiconductors, a surface layer is considered in this three-layer model to represent a thin, less severally damaged region close to the surface. The effects on the PCR signal of several structural, transport, and optical properties of ion-implanted silicon wafers affected significantly by the ion implantation process (minority carrier lifetime, diffusion coefficient, optical absorption coefficient, thickness of the implanted layer, and front surface recombination velocity) are discussed. The dependence of the PCR signal on the ion implantation dose is theoretically calculated and compared to experimental results. Good agreement between experimental data and theoretical calculations is obtained. Both theoretical and experimental results show the PCR dependence on dose can be separated into four regions with the transition across each region defined by the implantation-induced electrical and optical degrees of damage, respectively, as the electrical and optical damage occurs at different dose ranges. It is also shown that the PCR amplitude decreases monotonically with increasing implantation dose. This monotonic dependence provides the potential of the PCR technique for industrial applications in semiconductor metrology.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".