Measurement of energy flux at the substrate in a magnetron sputter system using an integrated sensor
Bibliographic record
Abstract
Knowledge of the energy flux in a sputter deposition system is important for predicting and controlling the properties of the growing film. The use of discrete sensors such as thermocouples for heat measurement has a potential contact problem due to the temperature jump between the surface of the wall and the surrounding gas especially at very low pressures. Embedded sensors such as a microfabricated polysilicon thin film thermistor eliminates the problem associated with thermal connection. In this study, the fabricated sensor is calibrated using ohmic self-heating before the deposition plasma is switched on, and also after the plasma is switched off (passive mode). At low pressures (up to 20 mTorr), pressure has an insignificant effect on the thermal resistance of the sensor. For substrate temperatures up to 250 °C, the sensor response is linear with input power. For a 3 in magnetron system, values of steady state energy flux measured with the sensor range from 5 to 46 mW/cm2 for aluminum (Al) and 14 to 114 mW/cm2 for copper (Cu) depending on the process conditions. These values compare well with those determined theoretically. Magnetron power was varied between 75 and 300 W, gas pressure 5–10 mTorr, and substrate–target distance 10.8–21 cm.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".