Axial resistivity measurement of a nanopillar ensemble using a cross-bridge Kelvin architecture
Bibliographic record
Abstract
Achieving the full potential of nanopillar electrode based devices, such as next-generation solar cells, catalyst supports, and sensors, requires axial resistivity measurements to optimize electronic performance. Here, the authors demonstrate a technique for direct measurement of the ensemble electrical properties of nanopillar thin films along the structure's longitudinal axis. A cross-bridge Kelvin resistor architecture is adapted to accommodate an indium tin oxide (ITO) nanopillar thin film fabricated by glancing angle deposition (GLAD). As-deposited GLAD ITO nanopillars were found to have a measured resistivity of (1.1 ± 0.3) × 10−2 Ω cm using our technique. Planar ITO films deposited at near normal incidence were found to have a resistivity of (4.5 ± 0.5) × 10−3 Ω cm, determined by the standard four-point-probe technique. These measurements demonstrate the viability of this modified technique for nanopillar characterization, and identify experimental limitations related to device size and edge defects.
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".