Conducting Poly(anilineboronic acid) Nanostructures: Controlled Synthesis and Characterization
Bibliographic record
Abstract
Abstract Self‐doped poly(anilineboronic acid) (PABA) nanostructures have been prepared by chemical polymerization in an aqueous acid solution and aliphatic alcohols. In aliphatic alcohols, PABA is soluble under the polymerization conditions. According to 11 B NMR studies, the formation of anionic tetrahedral boronate ester in aliphatic alcohols in the presence of fluoride forms the basis of self‐doped, soluble PABA. Transmission electron microscope images show the formation of nanostructures with different shapes and forms in different solvents after precipitation of the polymer as a result of ion exchange in the presence of 0.5 M HCl. The spectroscopic and cyclic voltammetric results confirm the formation of conducting PABA nanostructures in high yield. The conductivity of PABA thin films made from the nanostructures prepared in aqueous acid, methanol, ethanol and 1‐propanol is approximately 15 and 3.0, 2.1 and 1.9 S · cm −1 , respectively. The conducting PABA nanostructures are processable since they are easily re‐dispersed in the various solvents up to approximately 5 mg · mL −1 . UV‐vis kinetic measurements, XPS and 11 B NMR results suggest that the formation of various nanostructures is influenced by the polymerization rate, the degree of self‐doping versus external doping, and the polarity of the solvents used. The PABA nanostructured films produced from these structures exhibit enhanced redox stability in a wider potential window in non‐aqueous media compared to polyaniline due to formation of six‐member heterocyclic complexes containing a boron‐imine dative bond resulting in a self‐doped self‐cross‐linked polymer. The degree of crosslinking depends on the nature of nanostructures. In non‐aqueous media, the self‐doped, self‐cross‐linked PABA nanostructured films are much less susceptible to cathodic and anodic degradation at extreme potentials, overcoming a major limitation of more common conducting polymers. magnified image
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".