A Nanofibrous Polypyrrole Membrane with an Ultrahigh Areal Specific Capacitance and Improved Energy and Power Densities
Bibliographic record
Abstract
For conductive polymers to be competitive with carbon-based electrode materials, it is critical to increase their surface area and electroactivity. In this work, a thick nanofibrous polypyrrole (PPy) membrane with communicating interfiber spaces was prepared through one-pot interfacial polymerization for the first time. The electrochemical properties and conductivity of the membrane were studied with cyclic voltammetry, electrochemical impedance spectroscopy, and a four-point probe. Its morphology, chemistry, and thermostability were evaluated by scanning electron microscopy, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and thermogravimetric analysis. The areal specific capacitances measured between 0.0 and 0.8 V at 1 mA/cm 2 were 19179, 13264, 7238, and 4458 mF/cm 2 for the membranes doped with docusate sodium (AOT), camphor-10-sulfonic acid (β) (CSA), Cl –, and poly(sodium 4-styrenesulfonate) (PSS), respectively. The capacity retentions after 1000 cycles were 83, 74, 67, and 61% for the AOT-, CSA-, PSS-, and Cl – -doped membranes, respectively. The Coulombic efficiency was above 99% for all of the membranes. They showed energy densities of 1.7, 1.2, 0.7, and 0.4 mWh/cm 2 and power densities of 0.61, 0.75, 0.66, and 0.62 mW/cm 2 for the AOT-, CSA-, Cl – -, and PSS-doped membranes, respectively. The ultrahigh areal specific capacitance of PPy-AOT is due to its nanofibrous structure. A mechanism has been proposed to explain how this structure is formed based on the role of AOT as the surfactant. This nanofibrous PPy membrane is easy to prepare and metal-free and offers a very high areal specific capacitance, making it an excellent candidate to construct electrodes in pseudosupercapacitors.
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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 | 0.001 | 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".