Development and Characterization of an Electroplated Copper Nickel Alloy–Platinum Micro-Thermocouple
Bibliographic record
Abstract
A cost effective electrodeposition technique was developed to microfabricate copper nickel alloy (CuNi)-platinum micro thermocouples. A flat smooth silicon wafer with a 9000 Å layer of oxide was chosen as the substrate material. Gold was used for the thermocouple electroplating base because of its high resistance to electrochemical corrosion and oxidation. Since gold does not adhere to the silicon substrate, a chromium layer was deposited as a seed layer for the gold deposition. The substrate is patterned using a lithography process to create a mould for the plating with junction sizes in the range 50 μm to 500 μm. The CuNi leg was electroplated onto the exposed gold surface. The platinum leg of the thermocouple was metal deposited. The CuNi composition of the microfabricated thermocouples was 16.3 percent nickel and 83.7 percent copper as determined through energy dispersive spectroscopy. The sensitivity of the microthermocouple was determined using a thermal bath, with the platinum leg as a reference. The sensitivity was 39 μV/°C for ice bath compensated and 41 μV/°C for non compensated thermocouples.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".