In-situ process control for semiconductor manufacturing
Bibliographic record
Abstract
There is a critical need for exact, real-time reaction control of the chemical vapor deposition (CVD) systems that are used for semiconductor device manufacture. The chemical kinetic relationships underlying the fabrication processes, while they have been modeled in certain cases have, in most instances, not been experimentally confirmed. These models are especially needed to effectively control particle nucleation within CVD reactors. The lack of chemical data on these systems is, at least in part, due to the fact that reliable, suitably configured sensors have not been generally available. Fourier-transform infrared (FT-IR) spectrometry is being used to provide the required sensing, and the chemical kinetic relationships involved in device manufacture are being understood and modeled. A prototype control system has been developed using an FTIR sensor to control the reaction chemistry for a specific CVD process, and a plan for extending and commercializing this technology has been created. These recent accomplishments are described in this paper.
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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 | 0.000 |
| 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 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".