High-throughput resistivity apparatus for thin-film combinatorial libraries
Bibliographic record
Abstract
An apparatus, capable of measuring the dc resistance versus temperature of a 49-member library prepared by thin-film deposition techniques was designed and tested. The library is deposited by dc magnetron sputtering onto 10.16cm×10.16cm alumina substrates on which are placed aluminum masks consisting of 8mm diam holes cut on a 7×7 grid, the center-to-center spacing being 10.15mm. Electrical contact to the library is made in a standard van der Pauw geometry using 196 spring-loaded, gold-coated pins, four pins for each member of the library. The temperature is controlled using a helium refrigerator in combination with a liquid-nitrogen radiation shield that greatly reduces radiative heating of the sample stage. With the radiation shield, the cold finger is able to sustain a minimum temperature of 7K and the sample stage a minimum temperature of 27K. The temperature (27–291K) dependent dc resistivity of a thin-film silver library of varying thickness (48–639nm) is presented to highlight the capabilities of the apparatus. The thickness dependence of both the resistivity and the temperature coefficient of resistivity are quantitatively consistent with the literature. For thicknesses greater than about 100nm, the room-temperature resistivity (3.4μΩcm) are consistent with Matthiessen’s rule for 1%–2% impurity content, and the temperature coefficient of resistivity is consistent with the bulk value. For thicknesses less than 100nm, an increase in resistivity by a factor of 8 is found, which may be due to surface and boundary scattering effects; a corresponding increase in the temperature coefficient of resistivity is consistent with a concomitant decrease in the magnitude of the elastic constants and surface scattering effects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".