Evaluation of Electrical Properties and Antibacterial Performance of PVA-PVP/CuO-Cr2O3 Nanocomposites
Bibliographic record
Abstract
This study aims to analyse the dielectric properties of polyvinyl alcohol (PVA) and polyvinyl pyrrolidone (PVP) composites filled with chromium oxide (CrO) and copper oxide (CuO) nanoparticles.The study explores the effect of these particle concentrations on the AC electrical conductivity, dielectric loss, and dielectric constant, to employ these materials in antibacterial applications.Nanocomposites of PVA and PVP with different proportions of CrO and CuO were synthesised, and their electrical characteristics were examined by dielectric analysis methods.The AC electrical conductivity, dielectric loss, and dielectric constant were assessed within a defined frequency range, with differing nanoparticle concentrations to evaluate their influence on these parameters.The antibacterial bioactivity of the composites was assessed, and the influence of escalating nanoparticle concentrations on their efficacy was studied.The investigation demonstrated that both the dielectric loss and the dielectric constant decreased with increasing frequency; however, both parameters increased with higher concentrations of CrO nanoparticles.The electrical conductivity of alternating current increased with increasing frequency and the concentration of CrO and CuO nanoparticles.The increase in efficacy was seen with increasing nanoparticle concentration in the nanocomposites' antibacterial activity against Streptococcus and Serratia species.This study confirms that PVA-PVP/CrO-CuO nanocomposites exhibit improved electrical properties, This makes them well-suited for use in electronic devices and energy storage systems.Furthermore, the antibacterial effect of these materials opens new avenues for their use in medical and antimicrobial applications, contributing to the development of multifunctional materials in various fields.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".