Multifunctional nanocomposites of poly(vinylidene fluoride) reinforced by carbon nanotubes and magnetite nanoparticles

In the present study, the effect of nano magnetite (Fe3O4) content on structural, dielectric/electrical, magnetic and thermal properties of poly(vinylidene fluoride)/carbon nanotubes matrix, is investigated. Nanocomposite films of polyvinylidene fluoride, carbon nanotubes and Fe3O4 nanoparticles were prepared by the twin screw compounding method. Fe3O4, as magnetic inclusions was incorporated into the composites with carbon nanotubes loadings well above the percolation threshold, where conductive networks were formed. Magnetic characterization revealed the ferrimagnetic behavior of nanocomposites, with saturation magnetization values depending on magnetite content. Results obtained from the analysis of Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD) and Differential Scanning Calorimetry (DSC) techniques were very informative for the study of the polymorphism and crystallinity in PVDF. The incorporation of Fe3O4 inclusions in PVDF/CNT matrix, gradually increase both electrical conductivity and dielectric permittivity up to 10 wt% Fe3O4 content, while at the higher Fe3O4 content (15 wt%) reduced values were obtained. This behavior, at higher Fe3O4 content, should be possible related to the insulating and barrier role of Fe3O4 nanoparticles

Exploring the High Frequencies AC Conductivity Response in Disordered Materials by Using the Damped Harmonic Oscillator

The AC conductivity response of disordered materials follows a universal power law of the form σ′ (ω) ∝ ωn at the low frequency regime, with the power exponent values in the range 0 < n < 1. At the high frequency regime, in many experimental data of different disordered materials, superlinear values of the power exponent n were observed. The observed superlinear values of the power exponent are usually within 1 < n < 2, but in some cases values n > 2 were detected. The present work is based on the definitions of electromagnetic theory as well as the Havriliak–Negami equation and the damped harmonic oscillator equation, which are widely used for the description of dielectric relaxation mechanisms and vibration modes in the THz frequency region, respectively. This work focuses mainly on investigating the parameters that affect the power exponent and the range of possible n values. © 2022 by the author. Licensee MDPI, Basel, Switzerland

OPTICAL AND DIELECTRIC PROPERTIES OF PURE AND NANOFIBER-COMPOSITE POLYURETHANE

[No abstract available

The Electrical Conductivity of Ionic Liquids: Numerical and Analytical Machine Learning Approaches

In this paper, we incorporate experimental measurements from high-quality databases to construct a machine learning model that is capable of reproducing and predicting the properties of ionic liquids, such as electrical conductivity. Empirical relations traditionally determine the electrical conductivity with the temperature as the main component, and investigations only focus on specific ionic liquids every time. In addition to this, our proposed method takes into account environmental conditions, such as temperature and pressure, and supports generalization by further considering the liquid atomic weight in the prediction procedure. The electrical conductivity parameter is extracted through both numerical machine learning methods and symbolic regression, which provides an analytical equation with the aid of genetic programming techniques. The suggested platform is capable of providing either a fast, numerical prediction mechanism or an analytical expression, both purely data-driven, that can be generalized and exploited in similar property prediction projects, overcoming expensive experimental procedures and computationally intensive molecular simulations. © 2022 by the authors

A method for the calculation the activation energies of thermally stimulated depolarization current peaks: Application in polyvinylidene fluoride/graphene nanocomposites

A simple method is presented for the calculation of the activation energies of first order peaks of Thermally Stimulated Depolarization Current (TSDC). Three equations are derived, which relate the activation energy of the relaxation process, to three characteristic temperatures of the TSDC thermographs, which correspond to the peak temperature TM, and the half of the peak current temperatures T1, T2 (T1<T2). Each equation gives an expression of the activation energy as a function of two out of the three characteristic temperatures of the TSDC peak, assuming typical values of activation energy in the range 0.2–2.0 eV. The proposed equations were compared with other methods based on the same characteristic temperatures, in pristine PVDF and PVDF with 1wt% graphene samples at a temperature range where the MWS relaxation takes place. In PVDF-graphene samples, the MWS peak was found to consist of two overlapping mechanisms. © 2021 Elsevier B.V