Herein, we present a quick and cost-effective electrodeposition method to synthesize binder-free cobalt oxide (Co3O4) nanostructures. The structural crystallinity of the prepared electrodes was examined using X-ray diffraction (XRD), while Fourier-transform infrared spectroscopy (FTIR) was used to study the stretching and bending vibrations of metal-oxygen bonds. Scanning electron microscopy (SEM) revealed that as the concentration increased from 1 mM, nanoparticles transitioned from agglomeration to sheet formation. The supercapacitor properties of these Co3O4 nanostructure electrodes were investigated in a 6 M KOH solution. Among the electrodes, Co3O4@FNF-1 exhibited the highest capacitance of 1444 F g(-1) at a current density of 0.5 A g(-1). Additionally, the optimized Co3O4@FNF-1 electrode demonstrated 96% stability after 8000 cycles and showed excellent glucose sensing capabilities. These findings suggest that the binder-free Co3O4 electrode is a promising candidate for high-performance supercapacitor and biosensing applications.

Magnesium oxide (MgO) nanoparticles found considerable interest from the researcher because of their versatile biocompatible properties and the plethora of applications including anticancer, antimicrobial, antidiabetic, drug delivery, and tissue engineering etc. The growing applications of the MgO nanoparticles necessitate exploring new synthesis routes with faster production rates. Method: In this study, MgO nanoparticles were synthesized by ultrasonication-assisted co-precipitation method and calcined at 800°. MgO nanoparticles were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energydispersive X-ray spectroscopy (EDS) analysis. XRD results showed that the particles have a body-centered cubic (BCC) structure with a crystallite size of about 19.07 nm. SEM results displayed the spherical morphology of MgO nanoparticles. The impurity elements were absent as determined through EDX analysis and showed the high purity of the synthesized MgO. These particles are tested for in-vitro biological applications. The antibacterial activity of MgO nanoparticles on different bacteria was determined by the minimum inhibitory concentration (MIC) test. MIC test revealed that antibacterial activity increases by increasing the concentration of MgO nanoparticles. The synthesized nano-MgO showed high purity and spherical morphology and characterization analysis revealed that nano-MgO and biocompatible and can be applied in biomedical applications as verified by their bacterial activity test.

Reliable and cost-effective glucose sensors are in rising demand among diabetes patients. The combination of metals and conducting polymers creates a robust electrocatalyst for glucose oxidation, offering enzyme-free, high stability, and sensitivity with outstanding electrochemical results. Herein, graphene is grown on nickel foam by chemical vapor deposition to make a graphene@nickel foam scaffold (G@NF), on which silver nanoplates-polyaniline (Ag-PANI) 3D architecture is developed by sonication-assisted co-electrodeposition. The resulting binder-free 3D Ag-PANI/G@NF electrode was highly porous, as characterized by x-ray photoelectron spectroscopy, Field emission scanning electron microscope, x-ray diffractometer, FTIR, and Raman spectroscopy. The binder-free 3D Ag-PANI/G@NF electrode exhibits remarkable electrochemical efficiency with a superior electrochemical active surface area. The amperometric analysis provides excellent anti-interference performance, a low limit of deduction (0.1 nM), robust sensitivity (1.7 × 1013µA mM-1cm-2), and a good response time. Moreover, the Ag-PANI/G@NF enzyme-free sensor is utilized to observe glucose levels in human blood serums and exhibits excellent potential to become a reliable clinical glucose sensor.

Thermo-mechanical and mechanical properties of Magnesia-Carbon (MgO - C) refractories are of great importance in industrial furnace applications and are greatly influenced by the amount of carbon in the MgO Matrix. In this research work, the effect of exfoliated graphite nanosheets (EGS) content on mechanical behavior and thermal shock resistance of MgO-based refractories was examined. MgO nanoparticles were synthesized by the co-precipitation method and micro-MgO particles were used as received. EGS was added in both micro and nanoMgO in variable amounts ranging from 0.5 to 2.5 wt % to study its effect on fracture strength and thermal shock resistance. The morphology of synthesized MgO nanoparticles and the fractured surfaces of the resultant composites were analyzed by field emission scanning electron microscopy (FESEM) coupled with energy dispersive xray (EDX) spectroscopy, transmission electron microscopy (TEM), X-ray diffraction analysis (XRD), and compression testing. The synthesized nano-MgO and as received micro-MgO particles were found to be of spherical morphology with no impurity elements as observed by FESEM and EDX mapping. XRD analysis did not show any phase change after the sintering of the composites. The FESEM and TEM images of the fractured surfaces of MgO-EGS refractory samples displayed the fine distribution of EGS. EGS were embedded in MgO particles, enhancing the composite-refractory samples ' fractured strength. Fracture strength and thermal shock resistance were increased with the increasing amount of EGS in MgO. However, the highest fracture strength and thermal shock resistance values were achieved for nano-MgO with 2.5 wt% EGS. The resulting refractory samples can be used as furnace linings having a lower carbon content and enhanced thermo-mechanical properties.

In the current study, thermal-hydraulic design of the heat exchanger and composite material design are integrated to develop polymer composite tube materials for heat exchanger applications. For preliminary analysis, the scheme utilizes basic thermal resistance equations, Kern and Bell-Delaware methods for the design of baffled shell and tube heat exchangers, and differential effective medium theory for the design of composite materials. The preliminary analysis clarifies that the thermal conductivity of tubes is a performance-limiting parameter in the case of liquid-liquid applications. The heat exchanger's design imposes that the tubes' thermal conductivity must be enhanced to >= 8.5 W/m.K for achieving heat transfer comparable to those of metal counterparts. To attain the threshold thermal conductivity, the design of polymer composites employing differential effective medium theory requires that high volume fractions (> 0.3) of high effective aspect ratio (> 10 or 0.1) thermally conductive fillers be incorporated in a polymer matrix. Finally, the samples are fabricated of polypropylene matrix and expandable graphite filler with variable volume fractions (0.1-0.4). The highest thermal conductivity of 8.3 W/m.K was achieved in a 40 vol% sample. The comparison of measured and computed thermal conductivity values shows an acceptable agreement supported by electron microscopy and thermal images.

The recent approach for enhancing the thermal conductivity of polymer-composites is to generate an interconnecting network of thermally conductive fillers. However, the existing models for effective thermal conductivity of composites are, generally, based on effective medium theory and valid for dilute filler concentration (low volume fraction), which leads to inaccurate predictions with non-dilute and percolating filler concentrations. In this work, the model is developed focusing on non-dilute filler concentrations, which is more practical for the recent approach towards thermally conductive polymer-composites. The existing model for dilute filler concentrations is modified based on Bruggeman's differential scheme wherein the ‘non-dilute concentrations’ are obtained by integrating the effect of adding ‘dilute concentrations’ in small increments. The proposed model can handle particulate fillers of variable geometry. The proposed model is validated by producing different polymer matrix composite systems with ceramic fillers. Using Al2O3 or AlN as filler, and high-density polyethylene or polypropylene as matrix, different binary composite systems were processed with volume fractions up to 0.5. From the parametric studies, conducted to establish the understandings of the model, the aspect ratio of filler particles is found the most critical. The proposed model is expected to be the mathematical ground for the industry and researchers to produce computationally designed polymer composites with tailorable ultrahigh thermal conductivity in corrosive environment-heat transfer applications such as polymeric heat exchangers for seawater desalination.

Polysulphone (PSU) composites with carbon nanotubes (PSU-CNT) and graphene nanoplatelets (PSU-GNP) were developed through the solution casting process, using various weight load percentages of 1, 3, 5, and 10 wt% of CNT and GNP nanofillers. The microstructural and thermal properties of the PSU-based composites were compared. The microstructural characterisation of both composites (PSU-CNTs and PSU-GNPs) showed a strong matrix–filler interfacial interaction and uniform dispersion of CNTs and GNPs in the PSU matrix. The analysis demonstrated that both the thermal conductivity and effusivity improved with the increase in the weight percentage (wt%) of CNTs and GNPs because of the percolation effect. The polysulphone-based composite containing 10 wt% CNTs showed a remarkably high thermal conductivity value of 1.13 (W/m·K), which is 163% times higher than pure PSU. While the glass transition temperature (Tg) was shifted to a higher temperature, the thermal expansion was reduced in all the PSU-CNT and PSU-GNP composites. Interestingly, the CNTs allowed homogeneous distribution and a reasonably good interfacial network of interaction with the PSU matrix, leading to better microstructural characteristics and thermal properties than those of the PSU-GNP composites. The findings highlight the importance of controlling the nature, distribution, and content of fillers within the polymeric matrix.

This work is focused on optimizing the properties of encapsulant for low-concentration photovoltaic (LCPV) modules leading to improved electrical power and module life. Thermal conductivity (TC), long-term shear modulus (G∞) and coefficient of thermal expansion (CTE) of backside encapsulant are optimized using finite element (FE) simulations on LCPV module. It is found that as compared with ethylene-vinyl acetate (EVA), increased TC can improve electrical power, while decreased CTE and G∞ can improve module life. Polymer composites with improved properties are computationally designed using in-house built design codes. Thermoplastic polyurethane (TPU) and ceramic fillers (particularly Al2O3 and AlN) with designated particle’s geometry and volume fraction are predicted as the most suitable constituents. The selected compositions are processed, and their properties are measured accordingly. The measured properties are used in the parent FE simulations to predict the expected values of electrical power and module life to confirm the feasibility of replacing EVA with TPU-composites. The proposed composite has a combination of high TC and tailored CTE and G∞, which lowers the cell temperature and thermal strains enhancing the electrical power by 4.38% and the module life by 93%, respectively.

Most of the predictive models for thermal conductivity of composites are derived based on the assumption that the filler concentration in the matrix is dilute. This assumption leads to inaccurate predictions when filler concentration is essentially non-dilute and hence there is a need to propose a model that could handle a non-dilute filler concentration. In this work an improved and realistic model for effective thermal conductivity of polymer matrix composites with non-dilute filler’s concentrations is derived and validated by experiments. The proposed model can handle fillers with variable size and shapes. The derivation is based on the Bruggeman’s differential effective medium theory where the high volume fractions can be obtained by incrementally adding ‘small volume fractions’ into the ‘existing composite’ at each stage. The proposed model is validated by experimentally produced different series of ceramic particles-polymer composites. Differently sized and shaped alumina (Al2O3) & aluminum nitride (AlN) particulate fillers, and high density polyethylene (HDPE) & polypropylene (PP) matrices were used as the variable ingredients. Using different combinations of filler, matrix and particle size six different series of composites were produced with variable filler concentrations up to 50% by volume. The microstructure of the produced samples was studied by field emission scanning electron microscope to relate the morphology with the predictions. The predictions of proposed model are found in close agreement with the measured thermal conductivities. To understand the detailed effects of different parameters, parametric studies are presented and discussed. It is found that aspect ratio of particulate fillers is the most sensitive parameter to enhance effective thermal conductivity. Overall, the proposed model is proven to be useful in composite material design for heat transfer applications. It is expected that the proposed model will open new doors for the researchers and polymer composite industry to develop new composite designs for achieving ultrahigh thermal conductivities.

A computational design methodology is reported to propose a high-performance composite for backside encapsulation of concentrated photovoltaic (CPV) systems for enhanced module life and electrical power. Initially, potential polymer composite systems that are expected to provide the target properties, such as thermal conductivity, coefficient of thermal expansion, and long-term shear modulus are proposed using in-house built design codes. These codes are based on differential effective medium theory and mean-field homogenization, which lead to the selection of matrix, filler, volume fractions, and type of particulates. Thermoplastic polyurethane (TPU) loaded with ceramics fillers of a minimum spherical diameter of 6 μm are found potential composites. Some representative samples are synthesized through the melt-mixing and compression-molding route and characterized. The target properties including thermal conductivity, coefficient of thermal expansion, viscoelastic parameters, and long-term shear modulus are measured and used to evaluate the performance of CPV modules using previously published finite element model. The proposed composite can drag the cell temperature down by 5.8 °C when compared with neat TPU which leads to a 4.3% increase in electrical power along with a reasonable module life. It is expected that this approach will make a baseline for the effective production of polymer composites in various industrial applications.

Most of the currently used encapsulants are inefficient for cooled concentrated photovoltaic (CPV) systems. The encapsulant of cells for CPV systems, must have an optimum combination of thermal conductivity, coefficient of thermal expansion and long term shear modulus. In this work an improved backside composite encapsulation is designed and developed that can provide increased power output and longer life by enhancing the effectiveness of cooling and reducing thermal stresses. The best combination of material properties is identified through parametric studies on finite element model of CPV laminate using ethylene vinyl acetate as datum line. It is found that increasing thermal conductivity from 0.311 to 0.75 W/mK can improve the cooling and hence the power production by 2%. While long term shear modulus and coefficient of thermal expansion needs to be reduced for a longer service life. Using in-house built material design codes, optimum combinations of matrix and filler were identified that could provide the set range of properties. In line with material design code, a total of only four samples using thermoplastic polyurethane as matrix and Al2O3 or AlN as fillers were synthesized to validate the design experimentally. The material properties were measured and used in the parent finite element model to evaluate the performance of the experimentally developed material and to validate the parametric studies. A good agreement is found between the experimental and computational results and hence the overall methodology is found effective for application focused design and development of composite materials. It is expected that this material design and development approach will provide a useful guideline to the CPV manufacturing industries.

A percolating network of hybrid fillers can provide significant synergic enhancement of thermal conductivity in polymer matrix composites. Especially, when platelets and fibers of high aspect ratios are mixed to form a percolating network, the percolation thresholds are small. However, the optimum ratio of platelets to fibers must be acquired for the maximum synergic enhancement. In this work, polysulfone (PSU) matrix‐hybrid fillers composite is designed with high thermal conductivity using a computational model. The calibration of computational model with several experimentally measured thermal conductivities of polymer matrix‐hybrid nanocomposites leads to the composition where maximum synergic effect/maximum thermal conductivity is expected. For the specific PSU–Graphene nano‐platelets (GNPs)/Carbon nano‐tubes (CNTs) hybrid composites synthesized in this study, the composition with maximum thermal conductivity as designed by the model is PSU/8.4% GNPs/1.6% CNTs. The samples produced experimentally around this composition have shown close agreement with the predictions of the model. Sensitivity analyses and parametric studies conducted on the model highlight that the dimensional parameters and the interface resistance of the fillers are the most sensitive to enhance the effective thermal conductivity. POLYM. COMPOS., 40:1419–1432, 2019. © 2018 Society of Plastics Engineers

Friction stir welding is a recently developed technique for joining low-melting metals and polymers. In the present work, friction stir welded joints of high-density polyethylene (HDPE) sheets were produced using a newly designed tool with a concave shoulder and a grooved conical pin. The joints were produced with and without the additions of ceramic particulates including silicon carbide (SiC), alumina, graphite, and silica. The effect of strain rate on the tensile properties of base material and plain welded joints was examined. In addition to tensile properties of composite joints, hardness profiles across the weld nugget were analyzed. It was observed that the increasing strain rate improved both the tensile strength and the ductility of the plain welded joints. The tool was able to yield a joint efficiency of around 84% in the plain welded samples. Although, in terms of joint efficiency, the composite joints were less efficient than the plain welded HDPE, SiC additions were found to yield better material properties relative to other reinforcements. Finally, it was concluded that an SiC–HDPE composite joint can be of practical importance in high strain rate applications, provided the optimum tool design and stir welding parameters are available.

Computational design for property management of composite materials offers a cost sensitive alternate approach in order to understand the mechanisms involved in the thermal and structural behavior of material under various combinations of inclusions and matrix material. The present study is concerned with analyzing the elasto-plastic and thermal behavior of Al2O3-Ni droplet composites using a mean field homogenization and effective medium approximation (EMA) using an in-house code. Our material design approach relies on a method for predicting potential optimum thermal and structural properties for Al2O3-Ni composites by considering the effect of inclusion orientation, volume, size, thermal interface resistance, percolation and porosity. The primary goal for designing such alumina-based composites is to have enhanced thermal conductivity for effective heat dissipation and spreading capabilities. At the same time, other functional properties like thermal expansion coefficient, elastic modulus, and electrical resistivity have to be maintained or enhanced. The optimum volume fraction was found to occur between 15 and 20 vol. %Ni while the average nickel particle size of 5 μm was found a minimum size that will enhance the thermal conductivity. The Young’s modulus was found decreasing as the volume fraction of nickel increases, which would result in enhanced fracture toughness. Electrical conductivity was found to be greatly affected by the percolation phenomenon in the designed range of volume fraction minimum particle size. As a validation, Al2O3 composites with 10% and 15% volume fraction Ni and droplet size of 18 μm are developed using spark Plasma Sintering process. Thermal conductivity and thermal expansion coefficient of the samples are measured to complement the computational design. Microstructural analysis of the sintered samples was also studied using optical microscope to study the morphology of the developed samples. It was found that the present computational design tool was accurate enough in predicting the desired properties of Al2O3-Ni composites.

Copper/diamond (Cu/D) composites are famous in thermal management applications for their high thermal conductivity values. They, however, offer some interface related problems like high thermal boundary resistance and excessive debonding. This paper investigates interfacial debonding in Cu/D composites subjected to steady-state and transient thermal cyclic loading. A micro-scale finite element (FE) model was developed from a SEM image of the Cu/20 vol % D composite sample. Several test cases were assumed with respect to the direction of heat flow and the boundary interactions between Cu/uncoated diamonds and Cu/Cr-coated diamonds. It was observed that the debonding behavior varied as a result of the differences in the coefficients of thermal expansions (CTEs) among Cu, diamond, and Cr. Moreover, the separation of interfaces had a direct influence upon the equivalent stress state of the Cu-matrix, since diamond particles only deformed elastically. It was revealed through a fully coupled thermo-mechanical FE analysis that repeated heating and cooling cycles resulted in an extremely high stress state within the Cu-matrix along the diamond interface. Since these stresses lead to interfacial debonding, their computation through numerical means may help in determining the service life of heat sinks for a given application beforehand.

It has been demonstrated that effective medium approximation and mean field homogenization technique is a useful computational tool to predict the effective thermal and structural properties of alumina-nickel (Al2O3-Ni) composites. Nickel particle size and volume fraction, thermal interface resistance and porosity are found significant factors that affect thermal conductivity, elastoplastic behavior, elastic modulus and thermal expansion coefficient of Al2O3-Ni composite. To complement the computational design, Al2O3-Ni composite samples with designed range of volume fractions and nickel particle size are developed using spark plasma sintering process and properties are measured for model verification.

Copper/diamond (Cu/D) composites are known for their applications in thermal management systems. This paper investigates the effect of interfacial thermal resistance (TR) upon the effective thermal conductivity of Cu/D composites through experimental and numerical means. The composite samples were made using uncoated, Cu-coated, and Cr-coated diamond particles. The transient plane source method was used to measure the thermal conductivity of the composite samples, while the micrographs of the specimens were used to develop the finite element models. Together with the experimental and numerical results, the interfacial TR was identified in each sample. Although Hasselman–Johnson model calculated the conductivity values with significant error, the trend shown by experimental results is still followed. The finite element model, however, led to an error of less than 1%. The numerical analysis showed that the TR depends not only upon the diamond volume fraction but also upon the coating material. Finally, it has been demonstrated that numerical simulation may be employed to reveal the appropriate combinations of diamond fraction and the coating material in order to attain the desired level of effective thermal conductivity.

The diamond-copper composite system has become the most attractive material in the research and development of new materials for thermal management applications. In this work, copper matrix composites reinforced with diamond particles were produced by conventional sintering method through powder metallurgy route. Diamond particles were used as uncoated, copper(nickel) coated (CuD) and chromium coated (CrD). Diamond particles were mixed with copper powder mechanically and cold compacted under uniaxial conditions. The cold compacted pellets were sintered in a vacuum tube furnace. Cold compaction pressure, sintering temperature and holding time were optimized for maximum densification and the composites were produced with different volume percent of diamond particles at optimized parameters. The densification was found maximum for the composite samples cold compacted at 525 MPa and sintered at 900 degrees C for 2 h. The best thermal conductivities achieved with uncoated, CuD and CrD particles were 275, 284 and 312 W/mK respectively. In comparison, better densification and good interfacial bond with copper matrix was observed in the CrD reinforced composites. (C) 2014 Elsevier B.V. All rights reserved.

In present paper, the fabrication and humidity sensing properties of aluminum phthalocyanine chloride (AlPcCl) thin film based sensors have been presented. AlPcCl thin films with nominal thickness of 50–100nm are deposited on glass substrates between pre-deposited 50nm thick aluminum electrodes. The gap between the electrodes is 50μm. It is observed that the sensing mechanism is based on the variation of resistance with change in humidity. For change in relative humidity (RH) from 20% to 92%, the change in resistance is 22.2×102 and 13.3×102 times respectively for the sensors having 50nm and 100nm thick AlPcCl films, while the 1h annealing of these samples at 100°C results in increase in average sensitivity up to 30% and 40% respectively. The consequence of measuring frequency and absorption–desorption behavior of the humidity sensor are also discussed in detail. It is also observed that annealing results in minimization of hysteresis and reduction of recovery time (τrec) up to 63% and 70% in sensors with 50nm and 100nm thick organic film respectively, while the response (τres) time is 10s for both the sensors.