Voltammetry at Hexamethyl-P-Terphenyl Poly(Benzimidazolium) (HMT-PMBI)-Coated Glassy Carbon Electrodes: Charge Transport Properties and Detection of Uric and Ascorbic Acid
Bibliographic record
Abstract
We describe the voltammetric behavior of an anion-exchange membrane, hexamethyl-p-terphenyl poly(benzimidazolium) (HMT-PMBI). The anion-exchange properties of HMT-PMBI chemically modified electrodes were investigated using K4Fe(CN)6 and K2IrCl6 as redox probes. The permselectivity properties of HMT-PMBI chemically modified electrodes were ascertained using tris(2-2’)bipyridyl-ruthenium(II) chloride Ru(bpy)32+. Cyclic voltammetry and chronoamperometry were utilized to extract parameters such as the concentration of the redox mediators inside the films and the apparent diffusion coefficients. We found the concentration of K4Fe(CN)6 and K2IrCl6 redox species within HMT-PMBI-coated films to be on the order of 0.04–0.1 mol·dm−3, and values of Dapp ca. 10−10–10−9 cm2·s−1. To evaluate the possibility of using such a polymer coating in electroanalysis, HMT-PMBI-modified electrodes were utilized for the voltammetric detection of uric acid in artificial urine, Surine® and ascorbic acid in Vitamin C samples. The results showed that HMT-PMBI-coated electrodes can detect uric acid in Surine® with a limit of detection (LoD) of 7.7 µM, sensitivity of 0.14 µA·µM−1·cm−2, and linear range between 5 μM and 200 μM, whereas for Vitamin C tablets, the LoD is 41.4 µM, the sensitivity is 0.08 µA·µM−1·cm−2, and the linear range is between 25 μM and 450 μM.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".