Dependence of Z Parameter for Tensile Strength of Multi-Layered Interphase in Polymer Nanocomposites to Material and Interphase Properties

Effect of contact number among graphene nanosheets on the conductivities of tunnels and polymer composites

Simple equations are expressed for tunnel conductivity, tunnel resistance and conductivity of a graphene-filled composite by the number of contacts and interphase part. More specially, the active filler amount is suggested by interphase depth, which changes the contact number. The conductivity of nanocomposite is presented by filler content, filler dimensions, tunneling length and interphase depth. The innovative model is surveyed by the experimented conductivity of real examples. Too, the impacts of numerous issues on the tunnel resistance, tunnel conductivity and conductivity of nanocomposite are discussed to validate the novel equations. The estimates agree with the experimented data and the impacts of several terms on the tunnel resistance, tunnel conductivity and conductivity of system are sensible. Thin and big nanosheets positively affect the nanocomposite's conductivity, but thick nanosheets improve the tunnel conductivity. High conductivity is found at short tunnels, while the nanocomposite's conductivity directly depends on the tunneling length. The dissimilar effects of these features on the tunneling properties and conductivity are described.

Simulating of effective conductivity for grapheme-polymer nanocomposites

The efficient conductivity of graphene-polymer systems is expressed supposing graphene, tunneling and interphase components. The volume shares and inherent resistances of the mentioned components are used to define the efficient conductivity. Besides, the percolation start and the share of graphene and interphase pieces in the nets are formulated by simple equations. Also, the resistances of tunneling and interphase parts are correlated to graphene conductivity and their specifications. Suitable arrangements among experimented data and model's estimates as well as the proper trends between efficient conductivity and model's parameters validate the correctness of the novel model. The calculations disclose that the efficient conductivity improves by low percolation level, dense interphase, short tunnel, large tunneling pieces and poor polymer tunnel resistivity. Furthermore, only the tunneling resistance can govern the electron transportation between nanosheets and efficient conductivity, while the big amounts of graphene and interphase conductivity cannot play a role in the efficient conductivity.

Nanocomposite of CO2-Based Polycarbonate Polyol with Highly Exfoliated Nanoclay

Polypropylene carbonate (PPC) derived from carbon dioxide has been used as a precursor for the synthesis of polyurethane (PU). The high viscosity of the PPC is the key parameter hindering its processability during PU synthesis. Herein, a PPC nanocomposite with highly exfoliated nanoclay was prepared through a solution intercalation process. A wide range of nanoclay concentrations incorporated into the PPC were studied. The impacts of the nanoclay on the PPC were investigated in order to maintain the polymer structure while improving its physical properties. The characterizations of PPC nanocomposites showed that the highly exfoliated nanoclay contributed to a viscosity reduction, and a slight reduction in the molecular weight. The polymer degradation was indicated by the formation of cyclic propylene carbonate. The minimum or critical concentration of nanoclay was found to be between ∼0.5 and 2.0 wt %. Within this range, the polymer degradation is minimal. The PPC nanocomposites with a lower viscosity showed excellent precursors for making PU coating materials. The PU coating derived from the PPC nanocomposite has higher anticorrosive properties in comparison with the non-modified PU coating.

Progressing of a power model for electrical conductivity of graphene-based composites

This work presents a power equation for the conductivity of graphene-based polymer composites by the tunneling length, interphase deepness and filler size. The impressions of these factors on the effective concentration and percolation beginning of graphene nano-sheets in nanocomposites are also expressed. The developed equations for percolation beginning and conductivity are examined by the experimented data of some examples, which can guesstimate the interphase depth, tunneling size and percolation exponent. Besides, the impacts of numerous factors on the percolation beginning and conductivity are designed. The developed equation for percolation beginning shows the formation of thick interphase and large tunnels in the reported samples. So, disregarding of tunneling and interphase spaces in polymer graphene nanocomposites overpredicts the percolation beginning. Additionally, the developed model presents the acceptable calculations for the conductivity of samples. Among the mentioned parameters, the concentration and graphene conductivity in addition to the interphase depth induce the strongest effects on the conductivity of composites.

Development of Kovacs model for electrical conductivity of carbon nanofiber-polymer systems

This study develops a model for electrical conductivity of polymer carbon nanofiber (CNF) nanocomposites (PCNFs), which includes two steps. In the first step, Kovacs model is developed to consider the CNF, interphase and tunneling regions as dissimilar zones in the system. In the second step, simple equations are expressed to estimate the resistances of interphase and tunnels, the volume fraction of CNF and percolation onset. Although some earlier models were proposed to predict the electrical conductivity of PCNFs, developing of Kovacs model causes a better understanding of the effects of main factors on the nanocomposite conductivity. The developed model is supported by logical influences of all factors on the conductivity and by experimented conductivity of several samples. The calculations show good accordance to the experimented data and all factors rationally manage the conductivity of PCNFs. The highest conductivity of PCNF is gained as 0.019 S/m at the lowest ranges of polymer tunnel resistivity (ρ = 500 Ω m) and tunneling distance (d = 2 nm), whereas the highest levels of these factors (ρ > 3000 Ω m and d > 6 nm) cannot cause a conductive sample. Also, high CNF volume fraction, poor waviness, long and thin CNF, low "k", thick interphase, high CNF conduction, high percentage of percolated CNFs, low percolation onset and high interphase conductivity cause an outstanding conductivity in PCNF.

A Review on Non-Enzymatic Electrochemical Biosensors of Glucose Using Carbon Nanofiber Nanocomposites

Diabetes mellitus has become a worldwide epidemic, and it is expected to become the seventh leading cause of death by 2030. In response to the increasing number of diabetes patients worldwide, glucose biosensors with high sensitivity and selectivity have been developed for rapid detection. The selectivity, high sensitivity, simplicity, and quick response of electrochemical biosensors have made them a popular choice in recent years. This review summarizes the recent developments in electrodes for non-enzymatic glucose detection using carbon nanofiber (CNF)-based nanocomposites. The electrochemical performance and limitations of enzymatic and non-enzymatic glucose biosensors are reviewed. Then, the recent developments in non-enzymatic glucose biosensors using CNF composites are discussed. The final section of the review provides a summary of the challenges and perspectives, for progress in non-enzymatic glucose biosensors.

Modeling of Electrical Conductivity for Polymer-Carbon Nanofiber Systems

There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)-polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation onset, interphase thickness, CNF waviness, tunneling length among nanoparticles, and the fraction of the networked CNF. The outputs of the developed model correctly agree with the experimentally measured conductivity of several samples. Additionally, parametric analyses confirm the acceptable impacts of main factors on the conductivity of composites. A higher conductivity is achieved by smaller waviness and lower radius of CNFs, lower percolation onset, less tunnel distance, and higher levels of interphase depth and fraction of percolated CNFs in the nanocomposite. The maximum conductivity is obtained at 2.37 S/m by the highest volume fraction and length of CNFs.

Potential Use of Chitosan-TiO2 Nanocomposites for the Electroanalytical Detection of Imidacloprid

The detection of toxic insecticides is a major scientific and technological challenge. In this regard, imidacloprid is a neonicotinoid that is a systemic insecticide that can accumulate in agricultural products and affect human health. This work aims to study the properties of chitosan–TiO₂ nanocomposites in which nanoparticles with high surface area serve as molecular recognition sites for electroanalytical imidacloprid detection. We show that the best sensitivity to imidacloprid was obtained using a modified electrode with a chitosan–TiO₂ nanocomposite with a 40 wt.% of TiO₂ nanoparticles. By using a three-phase effective permittivity model which includes chitosan, TiO₂, an interface layer between nanoparticles and a matrix, we showed that nanocomposites with 40 wt.% of TiO₂ the interface volume fraction reaches a maximum. At higher nanoparticle concentration, the sensitivity of the sensor decreases due to the decreasing of the interface volume fraction, agglomeration of nanoparticles and a decrease in their effective surface area. The methodology presented can be helpful in the design and optimization of polymer-based nanocomposites for a variety of applications.

Influence of TiO2 and ZrO2 Nanoparticles on Adhesive Bond Strength and Viscosity of Dentin Polymer: A Physical and Chemical Evaluation

The present study aimed to formulate an experimental adhesive (EA) and reinforce it with 5 wt.% titanium dioxide (TiO₂) or zirconium oxide (ZrO₂) to yield 5% TiO₂ and 5% ZrO₂ adhesives, respectively, and then analyze the impact of this reinforcement on various mechanical properties of the adhesives. The EA contained a blend of monomers such as bisphenol A glycol dimethacrylate (BisGMA), triethylene glycol dimethacrylate (TEGDMA), 2-hydroxyethyl methacrylate (HEMA), and ethyl 4-dimethylamino benzoate and camphorquinone. The EA included ethyl 4-dimethylamino benzoate and camphorquinone photo-initiators, and diphenyliodonium hexafluorophosphate (DPIHP) was also included to act as an electron initiator. The TiO₂ and ZrO₂ nanoparticles were incorporated into the EA post-synthesis. To characterize the filler nanoparticles, scanning electron microscopy (SEM) and line-energy dispersive X-ray (EDX) spectroscopy were performed. The adhesives were characterized by analyzing their rheological properties, shear-bond strength (SBS), and interfacial failure types. Further, the resin-dentin interface was also analyzed via SEM. The TiO₂ nanoparticles were spherically shaped on the SEM micrographs, while the ZrO₂ nanoparticles were seen as non-uniformly shaped agglomerates. The EDX mapping demonstrated the presence of Ti and oxygen for TiO₂ and Zr and oxygen for the ZrO₂ nanoparticles. Both 5% TiO₂ and 5% ZrO₂ adhesives revealed decreased viscosity as compared with the EA. The 5% TiO₂ adhesive demonstrated higher SBS values for both non-thermocycled (NTC) and thermocycled samples (NTC: 25.35 ± 1.53, TC: 23.89 ± 1.95 MPa), followed by the 5% ZrO₂ adhesive group (NTC: 23.10 ± 2.22, TC: 20.72 ± 1.32 MPa). The bulk of the failures (>70%) were of adhesive type in all groups. The SEM analysis of the resin-dentin interface revealed the development of a hybrid layer and resin tags (of variable depth) for the EA and 5% TiO₂ groups. However, for the 5% ZrO₂ group, the hybrid layer and resin tag establishment appeared compromised. Reinforcement of the EA with TiO₂ or ZrO₂ caused an increase in the adhesive's SBS (with the 5% TiO₂ group demonstrating the highest values) in comparison with the EA (without nanoparticles). However, both nanoparticle-containing adhesives revealed decreased viscosity compared with the EA (without nanoparticles). Further studies investigating the impact of diverse filler concentrations on the properties of adhesives are suggested.

Characterizations and interfacial reinforcement mechanisms of multicomponent biopolymer based scaffold

It is difficult for a single component biopolymer to meet the requirements of scaffold at present. The development of multicomponent biopolymer based scaffold provides an effective method to solve the issue based on the advantages of each kind of the biomaterials. However, the compatibility between different components might be very poor due to the difficulties in forming strong interfacial bonding, and thereby significantly degrading the integrated mechanical properties of the scaffold. In recent years, interface phase introduction, surface modification and in situ growth have been the major strategies for enhancing interfacial bonding. This article presents a comprehensive overview on the research in the area of constructing multicomponent biopolymer based scaffold and reinforcing their interfacial properties, and more importantly, the interfacial bonding mechanisms are systematically summarized. Detailly, interface phase introduction can build a bridge between biopolymer and other components to form strong interface bonding with the two phases under the action of interface phase. Surface modification can graft organic molecules or polymers containing functional groups onto other components to crosslink with biopolymer. In situ growth can directly in situ synthesize other components with the action of nucleating agent serving as an adherent platform for the nucleation and growth of other components to biopolymer surface by chemical bonding. In addition, the mechanical properties (including strength and modulus) and biological properties (including bioactivity, cytocompatibility and biosensing in vitro, and tissue compatibility, bone regeneration capacity in vivo) of multicomponent biopolymer based scaffold after interfacial reinforcing are also reviewed and discussed. Finally, suggestions for further research are given with highlighting the need for specific investigations to assess the interface formation, structure, properties, and more in vivo studies of scaffold before applications.

Effects of Size and Aggregation/Agglomeration of Nanoparticles on the Interfacial/Interphase Properties and Tensile Strength of Polymer Nanocomposites

In this study, several simple equations are suggested to investigate the effects of size and density on the number, surface area, stiffening efficiency, and specific surface area of nanoparticles in polymer nanocomposites. In addition, the roles of nanoparticle size and interphase thickness in the interfacial/interphase properties and tensile strength of nanocomposites are explained by various equations. The aggregates/agglomerates of nanoparticles are also assumed as large particles in nanocomposites, and their influences on the nanoparticle characteristics, interface/interphase properties, and tensile strength are discussed. The small size advantageously affects the number, surface area, stiffening efficiency, and specific surface area of nanoparticles. Only 2 g of isolated and well-dispersed nanoparticles with radius of 10 nm (R = 10 nm) and density of 2 g/cm³ produce the significant interfacial area of 250 m² with polymer matrix. Moreover, only a thick interphase cannot produce high interfacial/interphase parameters and significant mechanical properties in nanocomposites because the filler size and aggregates/agglomerates also control these terms. It is found that a thick interphase (t = 25 nm) surrounding the big nanoparticles (R = 50 nm) only improves the B interphase parameter to about 4, while B = 13 is obtained by the smallest nanoparticles and the thickest interphase.

A simple model for constant storage modulus of poly (lactic acid)/poly (ethylene oxide)/carbon nanotubes nanocomposites at low frequencies assuming the properties of interphase regions and networks

The networks of nanoparticles in nanocomposites cause solid-like behavior demonstrating a constant storage modulus at low frequencies. This study examines the storage modulus of poly (lactic acid)/poly (ethylene oxide)/carbon nanotubes (CNT) nanocomposites. The experimental data of the storage modulus in the plateau regions are obtained by a frequency sweep test. In addition, a simple model is developed to predict the constant storage modulus assuming the properties of the interphase regions and the CNT networks. The model calculations are compared with the experimental results, and the parametric analyses are applied to validate the predictability of the developed model. The calculations properly agree with the experimental data at all polymer and CNT concentrations. Moreover, all parameters acceptably modulate the constant storage modulus. The percentage of the networked CNT, the modulus of networks, and the thickness and modulus of the interphase regions directly govern the storage modulus of nanocomposites. The outputs reveal the important roles of the interphase properties in the storage modulus.

A multistep methodology for calculation of the tensile modulus in polymer/carbon nanotube nanocomposites above the percolation threshold based on the modified rule of mixtures

A multistep model is proposed for calculating the tensile modulus values of polymer/carbon nanotube (CNT) nanocomposites (PCNTs) based on the modified rule of mixtures, assuming a percolated network of nanoparticles. In the first step, the network of nanoparticles is considered as a new phase with a novel volume fraction and Young's modulus. Then, the volume fraction of the filler network in the PCNTs is correlated to the density of the network. Also, the percolation of the nanoparticles is related to the aspect ratio of the nanoparticles. Finally, a new model is proposed based on the modified rule of mixtures (the Riley model) of the properties of the filler network. The predictions of the proposed model are compared with experimental results and the roles of the nanoparticles and network properties in the modulus values of nanocomposites are determined. The proposed model presents acceptable predictions when compared with the experimental data. Moreover, the density and modulus of the filler network, as well as the aspect ratio and diameter of the nanoparticles was found to directly affect the moduli of the nanocomposites.

A multistep model is proposed for calculating the tensile modulus values of polymer/carbon nanotube (CNT) nanocomposites (PCNTs) based on the modified rule of mixtures, assuming a percolated network of nanoparticles.

Predicting the electrical conductivity in polymer carbon nanotube nanocomposites based on the volume fractions and resistances of the nanoparticle, interphase, and tunneling regions in conductive networks

Some limited models have been suggested to determine the conductivity of polymer carbon nanotube (CNT) nanocomposites (PCNTs). However, earlier models (e.g., the Kovacs model) cannot properly consider the roles of the interphase regions or tunneling properties on the percolation threshold and subsequent conductivity of PCNTs. In this paper, the Kovacs model is further developed by assuming that the CNT, interphase, and tunneling regions are separate phases. Also, some simple equations are provided to calculate the percolation threshold as well as the volume fractions and resistances of the CNT, interphase, and tunneling regions in conductive networks. The experimental conductivity results for several samples are compared with the predictions of the developed model. In addition, the calculations of the developed model at different parameter levels are explained and justified. The conductivity calculations show good agreement with the experimental data. Moreover, the developed model reasonably explains the roles of the different parameters on the conductivity. For example, long, thin, and straight CNTs efficiently improve the conductivity because they form large networks in the nanocomposites. Additionally, a thick interphase enlarges the conductive networks, resulting in a desirable conductivity. The conductivity of PCNTs only depends on the tunneling resistance; this is the case because the poor resistance/significant conductivity of the CNT and interphase regions do not influence the conductivity. The developed equations can replace conventional approaches for predicting the conductivity of nanocomposites.

Some limited models have been suggested to determine the conductivity of polymer carbon nanotube (CNT) nanocomposites (PCNTs).

Estimation of the tensile modulus of polymer carbon nanotube nanocomposites containing filler networks and interphase regions by development of the Kolarik model

The Kolarik model for the tensile modulus of co-continuous blends is developed for polymer/carbon nanotube (CNT) nanocomposites assuming continuous CNT networks and the reinforcing and percolating efficiencies of the interphase.

A Two-Step Methodology to Study the Influence of Aggregation/Agglomeration of Nanoparticles on Young's Modulus of Polymer Nanocomposites

A two-step technique based on micromechanical models is suggested to determine the influence of aggregated/agglomerated nanoparticles on Young's modulus of polymer nanocomposites. The nanocomposite is assumed to include nanoparticle aggregation/agglomeration and effective matrix phases. This method is examined for different samples, and the effects of important parameters on the modulus are investigated. Moreover, the highest and the lowest levels of predicted modulus are calculated based on the current methodology. The suggested technique can correctly predict Young's modulus for the samples assuming the aggregation/agglomeration of nanoparticles. Additionally, the aggregation/agglomeration of nanoparticles decreases Young's modulus of polymer nanocomposites. It is demonstrated that the high modulus of nanoparticles is not sufficient to obtain a high modulus in nanocomposites, and the surface chemistry of components should be adjusted to prevent aggregation/agglomeration and to disperse nano-sized particles in the polymer matrix.