Morphologically Controlled Bioinspired Dopamine‐Polypyrrole Nanostructures with Tunable Electrical Properties
Bibliographic record
Abstract
In order to develop functional nanostructures with controllable size, composition, morphology, and interface, a series of dopamine (DA) modified polypyrrole (PPy) nanostructures that have tunable electrical conductivity and improved water dispersibility are prepared. The DA‐PPy nanostructures exhibit various morphologies, including nanosphere, nanofiber, nanorod, and nanoflake; and all of these nanostructures can be achieved by simply varying the DA/Py reacting mole ratio. Furthermore, the potential application of each as‐fabricated DA‐PPy, which depend on their tunable electrical properties, are explored. In particular, DA‐PPy resulting from a 0.032 dopamine/pyrrole (DA/Py) mole ratio demonstrate superior capacitance for supercapacitors; at DA/Py = 0.064, DA‐PPy can be implemented as a co‐filler into the epoxy network to prepare hybrid electrically conductive adhesives and DA‐PPy synthesized from 0.64 DA/Py mole ratio reveals impressive electromagnetic microwave absorption ability that can be used for electromagnetic interference shielding applications. Due to the synergetic effects of DA and electrically conductive polymer PPy, this one‐step procedure represents a promising protocol to control the syntheses and properties of nanomaterials for applications in advanced electronic devices.
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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".