Measurement accuracy analysis of photocarrier radiometric determination of electronic transport parameters of silicon wafers
Bibliographic record
Abstract
Simulations are performed to investigate the accuracy of the simultaneous determination of the electronic transport properties (the carrier lifetime, the carrier diffusion coefficient, and the front and rear surface recombination velocities) of silicon wafers by means of the photocarrier radiometry (PCR) technique through fitting frequency-scan data to a rigorous model via a multi-parameter fitting process. The uncertainties of the fitted parameter values are analyzed by calculating the dependence of the square variance including both amplitude and phase variances on the electronic transport properties. Simulation results show that the ability of the PCR to accurately determine carrier lifetimes gradually decreases for lifetimes longer than roughly 100 microseconds. In case the carrier diffusion coefficient is previously known, the carrier lifetime and front surface recombination velocity can be determined with uncertainties approximately ±20% or less. Experiments with an ion-implanted silicon wafer were performed and the carrier lifetime and front surface recombination velocity were determined with estimated uncertainties approximately ±30% and ±15%, respectively.
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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 | 0.003 | 0.016 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".