Improved dielectric and electrical properties of PANI achieved by using low cost mineral additive

Kılıç, Mehmet; Karabul, Yaşar; Özdemir, Zeynep Güven; Mısırlıoğlu, Banu Süngü

doi:10.1109/tdei.2018.007482

Cited by 8 publications

(7 citation statements)

References 23 publications

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“…The results show that the surface emissivity of the slag particles is 0.89 when the surface temperature is 1402 • C. With the increasing awareness of energy conservation and emission reduction, many scholars gradually realize the broad prospect of blast furnace slag preparation of slag cotton [19], [20]. They explore the new technology of direct fibrosis of blast furnace slag preparation of slag cotton, and have made some achievements [21]- [29]. Basalt cotton was prepared by 60% blast furnace slag and 40% basalt, and its feasibility was verified [21].…”

Section: Introductionmentioning

confidence: 99%

“…A new nonlinear unmixing method (NBRU) was used to retrieve the best spatial distribution of seven minerals from hyperspectral data and evaluate the mineral abundance performance [28]. Through the influence of different mineral additives on the complex permittivity and electrical modulus of polyaniline, the experimental results show that low cost sodium metasilicate has a significant impact on the dielectric properties of polyaniline [29]. The methods of [8]- [13] described in this paper are all completed in the laboratory.…”

Section: Introductionmentioning

confidence: 99%

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Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Zhu

et al. 2020

IEEE Access

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This paper focuses on how to perspective the melting behavior of solid iron tailings in molten blast furnace slag and take a new non-contact visual analytical method to predict its melting law. The optimized convolution neural network (CNN) is used to track the moving target in charge coupled device (CCD) camera system efficiently and accurately, and the melting behavior of SiO 2 is described by coordinate translation transformation theory. Hierarchical agglomerative clustering (HAC) and delaunay triangulation were used to extract the characteristic parameters of the melting process of SiO 2. The prediction model of the melting rate of SiO 2 at high temperature was established by least square fitting (LSF) and dimensional analysis, and compared with the actual melting rate of SiO 2 obtained by experiments. The results show that the melting characteristics of SiO 2 at high temperature are in accord with certain function rule. The performance of optimized CNN in terms of processing time and accuracy is significantly improved, and the fusion rate prediction model of SiO 2 is verified by 100% accuracy. It provides theoretical support and model basis for the improvement of slag cotton preparation technology. INDEX TERMS Melting rate, target tracking, feature extraction, dimensional analysis, best match.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Zhu

et al. 2020

IEEE Access

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“…In the present study, conductivity properties of the polymer-based natural mineral reinforced composites have been evaluated since polymer composites which are prepared by using natural additives and waste materials have remarkable electrical properties such as high dielectric constant, low dielectric loss, and enhanced electrical conductivity. [38][39][40] The data obtained by Reference 41 for pure PPy, PPy/5% EKS, PPy/10% EKS, and PPy/20% EKS composites in the frequency range of 1 Hz to 40 MHz at 296 K-323 K temperature has been used as experimental data set for ML. The ac conductivity versus angular frequency curves in the logarithmic scale at the related temperatures for pure PPy, PPy/5% EKS, PPy/10% EKS, and PPy/20% EKS composites in Figure 2.…”

Section: Resultsmentioning

confidence: 99%

Machine learning models for estimating the AC conductivity mechanism of Edirne Kufeki stone reinforced Polypyrrole composites

Eyecioğlu

2022

J of Applied Polymer Sci

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In this study, the detailed temperature and frequency-dependent (ac) conductivity analyzes of Polypyrrole/Edirne Kufeki Stone (PPy/EKS) composites have been realized by considering both experimental and Machine Learning (ML) algorithms predicted data. In this respect, the experimental ac conductivity data of pure PPy, PPy/5% EKS, PPy/10% EKS, and PPy/20% EKS composites between 1 Hz and 40 MHz at 296, 313, and 333 K temperatures have been usedfor the data set of ML. First, a benchmark study has been done for applied ML algorithms to obtain an eligible model. It is found that the Gaussian process regression (GPR) algorithm provided the best prediction performance. Since it has been observed a good conformity between the experimental and prediction data of GPR model, the ac conductivity (σ ac ) versus angular frequency (w) curves of the composites produced experimentally have been estimated for new temperature values, which were not treated experimentally. Then, the σ ac ¼ f w ð Þ curves of at temperature values have been estimated by GPR which is for the EKS composites at various contributions that have not been experimentally produced. Ultimately, the GPR algorithm developed in the present work enables us to determine the optimum EKS additive percentage, working temperature, and frequency band for the PPy polymer matrix.

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“…Complex impedance emphasizes the grain boundary conduction process and highlights the large resistance. Complex modulus focuses on the electrical transport phenomena and small capacitance [ 4 , 13 , 14 ]. The variations of grain, grain boundary, interface, porosity, material proportion, and filler dispersion in the porous composites can be reflected in the complex modulus and complex impedance responses [ 4 , 10 , 12 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

“…The variations of grain, grain boundary, interface, porosity, material proportion, and filler dispersion in the porous composites can be reflected in the complex modulus and complex impedance responses [ 4 , 10 , 12 , 15 , 16 ]. Many studies examined the electrical performances (complex modulus and complex impedance) of inorganic/organic composites for a variety of applications [ 1 , 4 , 13 , 17 , 18 ]. However, there are few literature reports on the study of the electrical responses (complex modulus and complex impedance) of ceramic/polymer composites, especially the investigation of the electric properties of porous ceramic/polymer composites according to their material proportion and microstructural feature.…”

Section: Introductionmentioning

confidence: 99%

Complex Impedance and Modulus Analysis on Porous and Non-Porous Scaffold Composites Due to Effect of Hydroxyapatite/Starch Proportion

You

Cheng²,

Tan³

et al. 2023

Polymers

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This study aims to investigate the electric responses (complex modulus and complex impedance analysis) of hydroxyapatite/starch bone scaffold as a function of hydroxyapatite/starch proportion and the microstructural features. Hence, the non-porous and porous hydroxyapatite/starch composites were fabricated with various hydroxyapatite/starch proportions (70/30, 60/40, 50/50, 40/60, 30/70, 20/80, and 10/90 wt/wt%). Microstructural analysis of the porous hydroxyapatite/starch composites was carried out by using scanning electron microscopy. It shows that the formation of hierarchical porous microstructures with high porosity is more significant at a high starch proportion. The complex modulus and complex impedance analysis were conducted to investigate the electrical conduction mechanism of the hydroxyapatite/starch composites via dielectric spectroscopy within a frequency range from 5 MHz to 12 GHz. The electrical responses of the hydroxyapatite/starch composites are highly dependent on the frequency, material proportion, and microstructures. High starch proportion and highly porous hierarchical microstructures enhance the electrical responses of the hydroxyapatite/starch composite. The material proportion and microstructure features of the hydroxyapatite/starch composites can be indirectly reflected by the simulated electrical parameters of the equivalent electrical circuit models.

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Improved dielectric and electrical properties of PANI achieved by using low cost mineral additive

Cited by 8 publications

References 23 publications

Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Notice of Retraction: Perspective and Prediction of the Rule of High Temperature Melting of SiO₂ via Visual Analysis

Machine learning models for estimating the AC conductivity mechanism of Edirne Kufeki stone reinforced Polypyrrole composites

Complex Impedance and Modulus Analysis on Porous and Non-Porous Scaffold Composites Due to Effect of Hydroxyapatite/Starch Proportion

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