Investigation of thermal flux to the substrate during sputter deposition of aluminum
Bibliographic record
Abstract
The transient and steady state thermal flux at the substrate during the deposition of aluminum film in a direct current magnetron sputter system has been determined by measuring the resistance of a complementary metal–oxide–semiconductor (CMOS) sensor. The sensor is calibrated using ohmic self-heating before the plasma is switched on. The steady state thermal flux at the substrate was measured to vary from 9.6 to 46 mW/cm2 at a substrate-target distance of 10.8 cm depending on the magnetron power (75–300 W) and gas pressure. Plasma radiation and electron bombardment are noted to be the most significant sources of the thermal flux to the substrate, each contributing about 36% and 29%, respectively, of the total thermal flux at the substrate for a magnetron power of 200 W and gas pressure of 5 mTorr. Thermal radiation is also an important factor, along with kinetic energy and condensation energy. Total energy per deposited atom is calculated to be in the range of 28–52 eV depending on the magnetron power and gas pressure, and increases with pressure but decreases with magnetron power. The trend seems to suggest that at higher magnetron powers (>300 W for a 3 in. target), a pressure independent total energy per deposited atom may be obtained.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".