The role of electrodeposition conditions in creating MnO2-based flexible non-enzymatic glucose sensors
Bibliographic record
Abstract
Rapid growth in diabetes morbidity compels researchers to develop an enzymeless alternative to currently used enzymatic glucose monitors. In relation to the target glucose electrooxidation reaction, a series of non-enzymatic flexible MnO 2 -based electrodes was fabricated by means of electrodeposition. The effect of electrodeposition parameters (solution temperature, concentration, deposition potential) on morphological and electrochemical characteristics of prepared MnO 2 samples was investigated. To exhibit practical prospects of electrodeposited MnO 2 electrocatalysts for the in vivo use, glucose electrooxidation was performed in an isotonic NaCl-based phosphate-buffered saline with pH 7.40 containing physiological (1–30 mM) glucose concentrations. A rotating ring-disk electrode was applied to reveal differences in the electrodeposition process under various conditions as well as to solidly establish potentials of MnO 2 cathodic dissolution and O 2 /Cl 2 evolution at pH 7.40. For the most active sensor electrode with pronounced MnO 2 surface architecture a linear square root concentration plot in the full physiological glucose range (1–30 mM) was demonstrated. Sensitivity values up to ca. 41.8 and 81.2 μA mM −0.5 cm −2 at 25 and 37 °C, respectively, were observed. Excellent reproducibility of the glucose oxidation current and good glucose selectivity of electrodeposited MnO 2 in relation to some common interferent substances (fructose, galactose, xylose, ribose, urea, lactic acid, acetone, ascorbic acid, paracetamol) were revealed. • Electrodeposition parameters strongly affect surface structure of a MnO 2 catalyst. • Electrodeposited MnO 2 provides reproducible glucose oxidation currents (pH 7.40). • Concentration plot shows linearity in a physiological glucose range (1–30 mM). • Sensitivity in the glucose oxidation achieves 27.9–41.8 μA mM −0.5 cm −2 geo at 25 °C. • MnO 2 affords glucose selectivity in the presence of physiological interferents.
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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) | 0.001 | 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) | 0.000 | 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".