Fabrication and Characterization of Laser Pulled Platinum Microelectrodes with Controlled Geometry
Bibliographic record
Abstract
The development of a reproducible procedure for the fabrication of Pt disk-shaped microelectrodes with characteristic dimensions ranging from 50 nm to 1 μm in diameter was carried out using a laser pulling technique. The governing physical phenomena involved in their fabrication are discussed, and the importance of adding a critical quartz thinning step in the general procedure is demonstrated. The preparation of the microelectrodes involves sealing a platinum wire inside a quartz tubing using a pipet puller, thinning the composite material (platinum/quartz assembly), and laser pulling it to obtain two microelectrodes. The resulting microelectrodes display reproducible well-controlled geometry, which is important to downstream quantitative scanning electrochemical studies and imaging. Mechanical polishing of the microelectrode is required and remains the critical step in the fabrication of nanometer size electrodes. Following production, the microelectrodes are characterized by electron microscopy, scanning electrochemical microscopy, and cyclic voltammetry. Development of these microelectrodes is motivated by their subsequent application to electrocatalysis and their potential in theoretical study because of their well-defined geometry.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".