Theoretical and experimental studies on DC conductivity and temperature-dependent AC conductivity of poly(butyl methacrylate)/Nd-TiO2 nanocomposites

2019 ◽  
Vol 33 (8) ◽  
pp. 1061-1077 ◽  
Author(s):  
K Suhailath ◽  
MT Ramesan
Keyword(s):  
Ac Conductivity ◽  
Volume Fraction ◽  
Experimental Studies ◽  
Dc Conductivity ◽  
Butyl Methacrylate ◽  
Temperature Dependent ◽  
Exponential Factor ◽  
Structural Regularity ◽  
Uniform Dispersion ◽  
Xrd Patterns

Electrically conductive nanocomposite system based on poly(butyl methacrylate) (PBMA) with different contents of neodymium-doped titanium dioxide (Nd-TiO2) was prepared by in situ free radical polymerization method. The effect of Nd-TiO2 on the morphology and structural properties of the composites was carried out by scanning electron microscope (SEM) and X-ray diffraction analysis (XRD). The temperature-dependent AC conductivity and DC electrical conductivity of PBMA/Nd-TiO2 nanocomposites were studied with respect to the different volume fraction of Nd-TiO2 nanoparticles. SEM and XRD patterns revealed the uniform dispersion and structural regularity of nanoparticles in the polymer matrix. The AC conductivity of PBMA and its composites were found to be increased with an increase in temperatures and frequencies. The activation energy and exponential factor were analyzed from AC conductivity and both results indicate the hopping conduction mechanism present in PBMA/Nd-TiO2 nanocomposite, which is responsible for the variation of conductivity with temperature also. The DC conductivity of nanocomposites was higher than pure PBMA and the conductivity increases with increase in the concentration of Nd-TiO2 nanoparticles. Experimental and theoretical investigations based on McCullough, Bueche, Scarisbrick, and Mamunya modeling were carried out to observe the DC conductivity differences induced by the addition of Nd-TiO2 nanoparticles in PBMA matrix. Among the various modeling studied here, Mamunya model shows better agreement with the experimental conductivity.

Studies on mechanical properties, dielectric behavior and DC conductivity of neodymium oxide/poly (butyl methacrylate) nanocomposites

2020 ◽  
pp. 096739112096065
Author(s):  
K Suhailath ◽  
Meenu Thomas ◽  
MT Ramesan
Keyword(s):  
Mechanical Properties ◽  
Tensile Strength ◽  
Neodymium Oxide ◽  
Dielectric Behavior ◽  
Dc Conductivity ◽  
Butyl Methacrylate ◽  
X Ray Diffraction ◽  
Sem Images ◽  
X Ray ◽  
Uniform Dispersion

The current article aims to develop poly (butyl methacrylate) (PBMA) nanocomposites with enhanced electrical and mechanical properties by incorporating neodymium oxide (Nd2O3) nanoparticles between the PBMA chains. The morphological, thermal and structural profiles of the PBMA nanocomposites reinforced with different loading of Nd2O3 nanoparticles were investigated by scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermogravimetric analysis (TGA). The SEM images revealed that the morphology of the PBMA was significantly influenced by the insertion of Nd2O3. The uniform dispersion of Nd2O3 in the polymer composite was visible at 5 wt% loading of nano-filler. The main crystalline peaks of Nd2O3 nanoparticles in the amorphous PBMA structure were revealed by the X-ray diffraction analysis. The thermal stability of PBMA was greatly enhanced by the dispersion of Nd2O3 in the PBMA matrix. The tensile strength and elongation at break of the composites were measured and both results showed the enhanced mechanical properties of PBMA due to the reinforcement of Nd2O3 nanoparticles. The various parameters affecting the increased tensile strength of composite by the incorporation of nanoparticles were studied by different theoretical modeling. The electrical properties such as dielectric constant and the dielectric loss tangent (tan δ) of PBMA nanocomposites were enhanced with the addition of nanoparticles. Also, the DC conductivity of polymer composites was estimated and the applicability of different theoretical models for predicting the conductivity properties of PBMA/Nd2O3 nanocomposites were examined.

scholarly journals Synthesis, Characterization and Electrical Properties of ZnFe2O4 Nanoparticles

2021 ◽  
Vol 7 (2) ◽  
pp. 946-948
Author(s):  
Md Ashfaq Hussain ◽  
S Sindhu ◽  
B Raghunanda ◽  
S. Molakeri Ajai Kumar
Keyword(s):  
Ac Conductivity ◽  
Zinc Ferrite ◽  
Size Range ◽  
Combustion Method ◽  
Dc Conductivity ◽  
Temperature Dependent ◽  
Particle Size Range ◽  
Ft Ir ◽  
Znfe2o4 Nanoparticles ◽  
Increasing Temperature

Zinc ferrite (ZnFe2O4) nanoparticles were prepared by combustion method. The FT-IR, XRD and SEM with EDS were used to characterize the prepared sample. The characterization results confirm the successful synthesis of ZnFe2O4 nanoparticles with the particle size range of 24 – 30 nm. The temperature dependent DC conductivity of the sample has been studied in the temperature range 30-175 °C and AC conductivity was investigated between the frequencies of 10 Hz and 10 MHz. DC conductivity of the sample was increased while increasing temperature and AC conductivity was increased as the frequency increased.

Study on Cavity Growth in Uniaxial Tension of ZK60 Magnesium Alloy

2007 ◽  
Vol 353-358 ◽  
pp. 687-690
Author(s):  
Yan Dong Yu ◽  
De Liang Yin ◽  
Bao You Zhang
Keyword(s):  
Volume Fraction ◽  
Cavity Growth ◽  
Experimental Studies ◽  
Superplastic Forming ◽  
Cavity Radius ◽  
Analysis Software ◽  
Mixed Characteristic ◽  
Substantial Growth ◽  
Zk60 Magnesium Alloy ◽  
Electronic Microscope

Cavity growth is a typical microstructure feature in superplastic forming (SPF) of materials. Substantial growth and interlink of cavities in superplastic deformation usually lead to reduction in elongation, even to failure. Consequently, it is necessary to investigate the mechanism and model of cavity growth. In this paper, experimental studies on cavity growth were carried out by means of superplastic tension of ZK60 magnesium alloys. Scanning electronic microscope (SEM) was employed for observation of fractography. Experimental cavity radius and volume fraction were determined by optical microscopy and corresponding picture-based analysis software. It is found that, the fractured surfaces after a superplastic elongation have a mixed characteristic of intergranular cavities and dimples. Further, the cavity growth is identified to follow a exponentially increasing mode.

MICROSTRUCTURE AND MECHANICAL BEHAVIOR OF AMORPHOUS Al–Cu–Ti METAL FOAMS SYNTHESIZED BY SPARK PLASMA SINTERING

2017 ◽  
Vol 24 (Supp02) ◽  
pp. 1850022
Author(s):  
MAOYUAN LI ◽  
LIN LU ◽  
ZHEN DAI ◽  
YIQIANG HONG ◽  
WEIWEI CHEN ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Mechanical Behavior ◽  
Intermetallic Compounds ◽  
Spark Plasma Sintering ◽  
Elevated Temperatures ◽  
Volume Fraction ◽  
Metal Foams ◽  
Plasma Sintering ◽  
Spark Plasma ◽  
Xrd Patterns

Amorphous Al–Cu–Ti metal foams were prepared by spark plasma sintering (SPS) process with the diameter of 10[Formula: see text]mm. The SPS process was conducted at the pressure of 200 and 300[Formula: see text]MPa with the temperature of 653–723[Formula: see text]K, respectively. NaCl was used as the space-holder, forming almost separated pores with the porosity of 65 vol%. The microstructure and mechanical behavior of the amorphous Al–Cu–Ti metal foams were systematically investigated. The results show that the crystallinity increased at elevated temperatures. The effect of pressure and holding time on the crystallization was almost negligible. The intermetallic compounds, i.e. Al–Ti, Al–Cu and Al–Cu–Ti were identified from X-ray diffraction (XRD) patterns. It was found that weak adhesion and brittle intermetallic compounds reduced the mechanical properties, while lower volume fraction and smaller size of NaCl powders improved the mechanical properties.

Quantitative Experimental Study of SiO2-Water Nanofluids on Backward-Facing Step Flow under Low Reynolds Number

2018 ◽  
Vol 916 ◽  
pp. 221-225
Author(s):  
Ji Zu Lv ◽  
Liang Yu Li ◽  
Cheng Zhi Hu ◽  
Min Li Bai ◽  
Sheng Nan Chang ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Reynolds Number ◽  
Volume Fraction ◽  
Pure Water ◽  
Experimental Studies ◽  
Flow Characteristics ◽  
Thermal Engineering ◽  
Heat Transfer Medium ◽  
Step Flow

Nanofluids is an innovative study of nanotechnology applied to the traditional field of thermal engineering. It refers to the metal or non-metallic nanopowder was dispersed into water, alcohol, oil and other traditional heat transfer medium, to prepared as a new heat transfer medium with high thermal conductivity. The role of nanofluids in strengthening heat transfer has been confirmed by a large number of experimental studies. Its heat transfer mechanism is mainly divided into two aspects. On the one hand, the addition of nanoparticles enhances the thermal conductivity. On the other hand, due to the interaction between the nanoparticles and base fluid causing the changes in the flow characteristics, which is also the main factor affecting the heat transfer of nanofluids. Therefore, a intensive study on the flow characteristics of nanofluids will make the study of heat transfer more meaningful. In this experiment, the flow characteristics of SiO2-water nanofluids in two-dimensional backward step flow are quantitatively studied by PIV. The results show that under the same Reynolds number, the turbulence of nanofluids is larger than that of pure water. With the increase of nanofluids volume fraction, the flow characteristics are constantly changing. The quantitative analysis proved that the nanofluids disturbance was enhanced compared with the base liquid, which resulting in the heat transfer enhancement.

A COMPARATIVE STUDY OF MULTIPLE REGRESSION AND MACHINE LEARNING TECHNIQUES FOR PREDICTION OF NANOFLUID HEAT TRANSFER

2021 ◽  
pp. 1-22
Author(s):  
Eyup Kocak ◽  
Ulku Ece Ayli ◽  
Hasmet Turkoglu
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Multiple Regression ◽  
Volume Fraction ◽  
Particle Diameter ◽  
Machine Learning Techniques ◽  
Exponential Factor ◽  
Nano Fluid ◽  
Neuro Fuzzy ◽  
Interface System

Abstract The aim of this paper is to introduce and discuss prediction power of the multiple regression technique, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Interface System (ANFIS) methods for predicting the forced convection heat transfer characteristics of a turbulent nano fluid flow a pipe. Water and Al2O3 mixture is used as the nano fluid. Utilizing FLUENT software, numerical computations were performed with volume fraction ranging between 0.3% and 5%, particle diameter ranging between 20 and 140 nm and Reynolds number ranging between 7000 and 21000. Based on the computationally obtained results, a correlation is developed for Nusselt number using the multiple regression method. Also, based on the CFD results different ANN architectures with different number of neurons in the hidden layers and several training algorithms (Levenberg-Marquardt, Bayesian Regularization, Scaled Conjugate Gradient) are tested to find the best ANN architecture. In addition, Adaptive Neuro-fuzzy Interface System (ANFIS) is also used to predict the Nusselt number. In the ANFIS, number of clusters, exponential factor and Membership Function (MF) type are optimized. The results obtained from multiple regression correlation, ANN and ANFIS were compared. According to the obtained results, ANFIS is a powerful tool with a R2 of 0.9987 for predictions.

A Percolation Equation for Modeling Experimental Results for Continuum Percolation Systems

2001 ◽  
Vol 699 ◽  
Author(s):  
D.S. McLachlan ◽  
C. Chiteme ◽  
W.D. Heiss ◽  
Junjie Wu
Keyword(s):  
Experimental Data ◽  
Ac Conductivity ◽  
Volume Fraction ◽  
Power Laws ◽  
Second Order ◽  
Experimental Results ◽  
Analytical Equation ◽  
Scaling Properties ◽  
First Order ◽  
Dc And Ac Conductivity

AbstractThe standard percolation equations or power laws, for dc and ac conductivity (dielectric constant) are based on scaling ansatz, and predict the behaviour of the first and second order terms, above and below the percolation or critical volume fraction (øc), and in the crossoverregion. Recent experimental results on ac conductivity are presented, which show that these equations, with the exception of real σm above øc and the first order terms in the crossover region, are only valid in the limit σi/σc = 0, where for an ideal dielectric σi=ωε0εr.A single analytical equation, which has the same parameters as the standard percolation equations, and which, for ac conductivity, reduces to the standard percolation power laws in the limit σi(ωε0εr)/σc = 0 for all but one case, is presented. The exception is the expression for real σm below øc, where the standard power law is always incorrect. The equation is then shown to quantitatively fit both first and second order dc and ac experimental data over the entire frequency and composition range. This phenomenological equation is also continuous, has the scaling properties required at a second order metal-insulator and fits scaled first order dc and ac experimental data. Unfortunately, the s and t exponents that are necessary to fit the data to the above analytical equation are usually not the simple dimensionally determined universal ones and depend on a number of factors.

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