Economical Sputtering System To Produce Large-Size Composition-Spread Libraries Having Linear and Orthogonal Stoichiometry Variations
Bibliographic record
Abstract
A multitarget sputtering machine with a water-cooled rotating substrate table has been modified to produce films on 75 mm × 75 mm wafers which map large portions of ternary phase diagrams. The system is unconventional because the stoichiometries of the elements sputtered on the wafer vary linearly with position and in an orthogonal manner. Subsequent screening of film properties is therefore quite intuitive, since the compositional variations are simple. Depositions are made under continuous rotation, so either intimate mixing of the elements (fast rotation) or artificial layered structures (slow rotation) can be produced. Rotating subtables mounted on the main rotating table hold the 75 mm × 75 mm substrates. Stationary mask openings over the targets and mechanical actuators that rotate the subtables in a precise manner accomplish the linear and orthogonal stoichiometry variations. Deposition of a film spanning the range SiSn x Al y (0 < x, y < 1), with Sn content increasing parallel to one edge on the wafer and Al content increasing in a perpendicular direction, is given to illustrate the effectiveness of the method. Since the system was easily and inexpensively built, it has enabled our research program in combinatorial materials synthesis to begin without large scale funding.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".