Redox Polyelectrolytes with pH-Sensitive Electroactive Functionality in Aqueous Media
Bibliographic record
Abstract
A framework of ferrocene-containing polymers bearing adjustable pH- and redox-active properties in aqueous electrolyte environments was developed. The electroactive metallopolymers were designed to possess enhanced hydrophilicity compared to the vinylferrocene (VFc) homopolymer, poly(vinylferrocene) (PVFc), by virtue of the comonomer incorporated into the macromolecule, and could also be prepared as conductive nanoporous carbon nanotube (CNT) composites that offered a variety of different redox potentials spanning a ca. 300 mV range. The presence of charged non-redox-active moieties such as methacrylate (MA) in the polymeric structure endowed it with acid dissociation properties that interacted synergistically with the redox activity of the ferrocene moieties to impart pH-dependent electrochemical behavior to the overall polymer, which was subsequently studied and compared to several Nernstian relationships in both homogeneous and heterogeneous configurations. This zwitterionic characteristic was leveraged for the enhanced electrochemical separation of several transition metal oxyanions using a P(VFc 0.63 - co -MA 0.37 )-CNT polyelectrolyte electrode, which yielded an almost twofold preference for chromium as hydrogen chromate versus its chromate form, and also exemplified the electrochemically mediated and innately reversible nature of the separation process through the capture and release of vanadium oxyanions. These investigations into pH-sensitive redox-active materials provide insight for future developments in stimuli-responsive molecular recognition, with extendibility to areas such as electrochemical sensing and selective separation for water purification.
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 | 0.000 | 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 | 0.001 |
| 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".