Iridium‐Bismuth‐Oxide Coatings for Use in Neural Stimulating Electrodes: The Influence of Ir/Bi Ratio
Bibliographic record
Abstract
ABSTRACT Implantable neural prosthetics with stimulating electrodes are increasingly employed in medical practices to treat neural disabilities. The electrode material is expected to provide high charge storage and injection capacity (CSC/CIC) and low impedance for safe, efficient, and precise neural stimulation, while at the same time, being small. To improve the current state‐of‐the‐art neural‐electrode material, iridium oxide (IrOx), Ir m Bi 1‐m Ox coatings of various compositions ( m = 0, 0.2, 0.4, 0.6, 0.8, and 1.0) produced by thermal deposition were evaluated. The Ir 0.8 Bi 0.2 Ox yielded a CSC of 17.7 ± 1.1 mC/cm 2 , which is four‐fold higher than that of IrOx. At the same time, the impedance of Ir 0.8 Bi 0.2 Ox at 1 kHz was measured to be half of that of IrOx. The superior performance of Ir 0.8 Bi 0.2 Ox was explained by forming amorphous structures that facilitate the intercalation of H + and OH − ions into deeper oxide structures that contribute to faradaic charge storage. The Ir 0.8 Bi 0.2 Ox electrode also showed good stability and biocompatibility, which makes it potentially a good candidate for neural stimulating electrodes.
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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 | 0.000 | 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".