Dielectric properties and conductivity of PVdF-co-HFP/LiClO<sub>4</sub> polymer electrolytes
Bibliographic record
Abstract
In this study, it was aimed to prepare a series of PVdF-co-HFP based electrolytes with different LiClO4 loadings and to investigate their chemical and electrical properties in detail. For this purpose, PVdF-co-HFP based electrolytes with different LiClO4 loadings (1–20 weight %) were prepared using solution casting method. X-ray diffraction (XRD), differential scanning calorimetry, and thermogravimetric (TGA) –differential thermal and dielectric spectroscopy analysis of PVdF-co-HFP/LiClO4 were performed to characterize their structural, thermal, and dielectric properties, respectively. XRD results showed that the diffraction peaks of PVdF-co-HFP/LiClO4 electrolytes broadened and decreased with LiClO4. TGA patterns exhibited that PVdF-co-HFP/LiClO4 electrolytes with 20 wt % of LiClO4 had the lowest thermal stability and it degraded above 473 K, which is highly applicable for solid polymer electrolytes. Dielectric constant, dielectric loss, and conductivities were calculated by measuring capacitance and dielectric loss factor of PVdF-co-HFP/LiClO4 in the range from 10 mHz to 20 MHz frequencies at room temperature. In consequence, conductivities of PVdF-co-HFP/LiClO4 increased significantly with frequency for low loading of LiClO4 while they only slightly changed with higher LiClO4 addition. On the other hand, dielectric constant values of PVdF-co-HFP/LiClO4 films decreased with frequency whereas they rose with LiClO4 addition. The dielectric studies showed an increase in dielectric constant and dielectric loss with decreasing frequency. This result was attributed to high contribution of charge accumulation at the electrode–electrolyte interface. The electrolyte showed the maximum conductivity of 8 × 10−2 S/cm at room temperature.
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) | 0.001 | 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".