Dynamic Temperature Prediction for the Charging Process of the Fixed Chamber
Bibliographic record
Abstract
The dynamic gas flow verifier based on the rate of rise (RoR) method is employed for the in-situ calibration of mass flow controllers (MFC) in semiconductor manufacturing.Due to the complicated flow field distribution after process gas charging and the hysteresis characteristics of temperature sensors, accurate average temperature is nearly impossible to measure, and that will significantly affect the accurate metering of the flow rate.Thus, the dynamic temperature prediction based on CFD was proposed to achieve the virtual measurement of the average temperature of the chamber.Then, the dynamic temperature change for different process gases and flow rate was obtained to compensate flow rate calculation.Finally, the experimental apparatus was built up, and detailed comparison was carried out.Results show that the proposed dynamic temperature prediction could satisfy the in-situ verification of the MFCs, the accuracy is approximately 0.5% with the flow rate ranging from 5 to 2850 sccm.
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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) | 0.000 | 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 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".