Electrochemical Characterization of InN Thin Films for Biosensing Applications
Bibliographic record
Abstract
InN, a well-established optoelectronic material, is currently being considered as a promising material for sensor applications. In this study, the fundamental electrochemical properties of InN thin film and its potential for electrode chemical and bio-sensing applications are demonstrated. The cyclic voltammograms of different concentrations of dopamine solution in 1 M HClO4 were measured. Similarly, potentiostatic measurements at 1 V versus Ag/AgCl show stable responses and linear change of current density with concentrations up to 0.475 mM dopamine. The InN thin film also demonstrated repeatable positive photoresponse to cathodic currents in 1 mM Ru(NH3)63+ in 1M KCl solution under a 100 mW cm-2 808-nm laser light illumination at a constant -0.25 V (vs. Ag/AgCl) bias. The cathodic current response showed a 27% enhancement, demonstrating its potential as photocathode. This cathodic photocurrent behavior is explained through the electron accumulation of the InN material.
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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 | 0.000 |
| 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".