Statistical and Engineering Process Control of Phosphorus Diffused Solar Wafers Using Contactless Infrared Reflectometry
Bibliographic record
Abstract
For the silicon solar cell diffusion process, statistical process control (SPC) and engineering process control (EPC) are commonly used to ensure that yield and thoughput targets are met during high-volume industrial production. SPC uses control charts to detect out-of-specification (OOS) wafers that need to be reworked (typically those with emitters that are too lightly diffused to be contactable by the screen printed metal electrode)., EPC involves tuning of diffusion furnace parameters based on feedback from the emitter sheet resistance measurements of prior diffusion batches to reduce process variations and the frequency of OOS events. Both of these process control techniques, SPC and EPC, rely on sampled measurements of diffused wafers over each diffusion batch. This paper focuses on best practices and unique advantages of the use of contactless infrared reflectometry (IR) measurements of phosphorus-diffused wafers to implement SPC and EPC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".