An optoelectronic notch (‘dip’) phenomenon in the heterodyne photocarrier radiometry frequency response of Si wafers: a route to quantitative trap-state dynamic processes in semiconductors
Bibliographic record
Abstract
Abstract An anomaly was observed in the heterodyne photocarrier radiometry (HePCR) frequency response of Si wafers in the form of a signal amplitude depression (‘dip’) accompanied by a 180° phase transition. This phenomenon resembles an electronic notch filter and was investigated experimentally and theoretically by invoking free-carrier-density-wave (CDW) kinetics in generic semiconductor systems. Both homodyne PCR and HePCR signals were obtained from n- and p -type wafers of different resistivities. Dynamic nonlinear rate-equation models with two bandgap carrier traps were introduced and analytical zeroth and first-order CDW solutions were obtained in the frequency domain. The experimental frequency responses of the HePCR optoelectronic notch phenomenon were found to be in very good agreement with the theory. Characteristic CDW recombination and trap capture and emission characteristic times were obtained and studied as functions of the illuminating laser intensity. The present newly observed HePCR notch phenomenon has revealed a new mechanism of nonlinear contributions due to trap-state-related CDW dynamics in semiconductors superposed on the well-known nonlinear electron-hole recombination interactions that give rise to non-zero HePCR signals. The implications of this notch phenomenon are discussed in terms of its importance in providing physical insights into photocarrier dynamic interactions with traps, leading to identification of active CDW trap-state numbers and precision measurements of their kinetic parameters, carrier capture and emission coefficients, and quantitative trap densities that determine the optoelectronic quality of semiconductors.
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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 | 0.000 |
| 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".