Manwar Hussain

Enhancement of electroconductivity of polyaniline/graphene oxide nanocomposites through in situ emulsion polymerization

The present study introduces a systematic approach to disperse graphene oxide (GO) during emulsion polymerization (EP) of Polyaniline (PANI) to form nanocomposites with improved electrical conductivities. PANI/GO samples were fabricated by loading different weight percents (wt%) of GO through modified in situ EP of the aniline monomer. The polymerization process was carried out in the presence of a functionalized protonic acid such as dodecyl benzene sulfonic acid, which acts both as an emulsifier and protonating agent. The microstructure of the PANI/GO nanocomposites was studied by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, UV–Vis spectrometry, Fourier transform infrared, differential thermal, and thermogravimetric analyses. The formed nanocomposites exhibited superior morphology and thermal stability. Meanwhile, the electrical conductivities of the nanocomposite pellets pressed at different applied pressures were determined using the four-probe analyzer. It was observed that the addition of GO was an essential component to improving the thermal stability and electrical conductivities of the PANI/GO nanocomposites. The electrical conductivities of the nanocomposites were considerably enhanced as compared to those of the individual PANI samples pressed at the same pressures. An enhanced conductivity of 474 S/m was observed at 5 wt% GO loading and an applied pressure of 6 t. Therefore, PANI/GO composites with desirable properties for various semiconductor applications can be obtained by in situ addition of GO during the polymerization process.

Aminated polyethersulfone-silver nanoparticles (AgNPs-APES) composite membranes with controlled silver ion release for antibacterial and water treatment applications.

The present study reports the antibacterial disinfection properties of a series of silver nanoparticle (AgNP) immobilized membranes. Initially, polyethersulfone (PES) was functionalized through the introduction of amino groups to form aminated polyethersulfone (NH2-PES, APES). AgNPs were then coordinately immobilized on the surface of the APES composite membrane to form AgNPs-APES. The properties of the obtained membrane were examined by FT-IR, XPS, XRD, TGA, ICP-OES and SEM-EDAX analyses. These structural characterizations revealed that AgNPs ranging from 5 to 40 nm were immobilized on the surface of the polymer membrane. Antibacterial tests of the samples showed that the AgNPs-APES exhibited higher activity than the AgNPs-PES un-functionalized membrane. Generally, the AgNPs-APES 1 cm × 3 cm strip revealed a four times longer life than the un-functionalized AgNPs polymer membranes. The evaluation of the Ag(+) leaching properties of the obtained samples indicated that approximately 30% of the AgNPs could be retained, even after 12 days of operation. Further analysis indicated that silver ion release can be sustained for approximately 25 days. The present study provides a systematic and novel approach to synthesize water treatment membranes with controlled and improved silver (Ag(+)) release to enhance the lifetime of the membranes.

Wettability investigation of UV/O 3 and acid functionalized MWCNT and MWCNT/PMMA nanocomposites by contact angle measurement

The dispersion state of individual MWCNT in the polymer matrix influences the mechanical, thermal, and electrical properties of the resulting composite. One method of obtaining a good dispersion state of MWCNT in a polymer matrix is to functionalize the surface of MWCNT using various treatments to enhance the surface energy and increase the dispersibility of MWCNT. In this study, wettability and surface energy of UV/O3 and acid-treated multiwall carbon nanotubes (MWCNTs) and its polymethyl methacrylate (PMMA) polymer nanocomposites were measured using contact angle analysis in various solvent media. Contact angle analysis was based on ethylene glycol-water-glycerol probe liquid set and data was further fitted into geometric mean (Fowkes), van Oss-Chaudhury-Good (GvOC), and Chang-Qing-Chen (CQC) models to determine both nonpolar and acid base surface energy components. Analysis was conducted on MWCNT thin films subjected to different levels of UV/O3 and acid treatments as well as their resulting MWCNT/PMMA nanocomposites. Contact angle analysis of thin films and nanocomposites revealed that the total surface energy of all samples was well fitted with each other. In addition, CQC model was able to determine the surface nature and polarity of MWCNT and its nanocomposites. Results indicated that the wettability changes in the thin filmand its nanocomposites are due to the change in surface chemistry. Finally, electrical properties of nanocomposites were measured to investigate the effect of surface functionality (acid or basic) on the MWCNT surfaces.

Significant Enhancement of Mechanical and Thermal Properties of Thermoplastic Polyester Elastomer by Polymer Blending and Nanoinclusion

Thermoplastic elastomer composites and nanocomposites were fabricated via melt processing technique by blending thermoplastic elastomer TPEE with polybutylene terephthalate PBT thermoplastic and also by adding small amount of organo modified nanoclay and/or polytetrafluoroethylene PTFE. We study the effect of polymer blending on the mechanical and thermal properties of TPEE blends with and without nanoparticle additions. Significant improvement was observed by blending only TPEE and virgin PBT polymers. With a small amount 0.5 wt.% of nanoclay or PTFE particles added to the TPEE composite, there was further improvement in both the mechanical and thermal properties. To study mechanical properties, flexural strength FS, flexural modulus FM, tensile strength TS, and tensile elongation TE were all investigated. Thermogravimetric analysis TGA and differential scanning calorimetry DSC were used to analyze the thermal properties, including the heat distortion temperature HDT, of the composites. Scanning electron microscopy SEM was used to observe the polymer fracture surface morphology. The dispersion of the clay and PTFE nanoparticles was confirmed by transmission electron microscopy TEM analysis. This material is proposed for use as a baffle plate in the automotive industry, where both high HDT and high modulus are essential.

Effect of Nanoparticles on Mechanical and Flame-retardant Properties of Polyether-Block-Polyamide Polymer Nanocomposites

ABSTRACT In this study, polyester elastomer-based thermoplastic (TPEE) nanocomposites were fabricated for flame-retardant applications. Small amounts of graphene and nanoclay were added to the nanocomposites to investigate their effects on the mechanical and thermal properties of the nanocomposites. The addition of a phosphorous flame-retardant additive resulted in a significant improvement of the Young’s modulus and thus yield stress in the synthesized nanocomposites as compared to those made with the virgin TPEE. There was no synergistic improvement in mechanical properties with the addition of graphene and nanoclay to the nanocomposites. However, thermal properties, mainly the heat deflection temperature and fire performance (UL-94 V0), were improved significantly by the addition of graphene and nanoclay and a synergistic effect was observed. Heat distortion temperature and thermogravimetric analysis were used to analyze the thermal properties of the nanocomposites. The UL-94 testing method was used to investigate the fire performance of the nanocomposites. Scanning electron microscopy was used to observe the polymer fracture surface morphology. The dispersion of the graphene and nanoclay particles was confirmed by transmission electron microscopy analysis. GRAPHICAL ABSTRACT

Preparation of Miscible PVA/PEG Blends and Effect of Graphene Concentration on Thermal, Crystallization, Morphological, and Mechanical Properties of PVA/PEG (10 wt%) Blend

Water-soluble polymers such as poly(vinyl alcohol) (PVA) and poly(ethylene glycol) (PEG) and their nanocomposites with graphene were prepared by using a solution mixing and casting technique. The effect of different PEG loadings was investigated to determine the optimum blend ratio. The films were characterized using Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and thermogravimetric analyzer (TGA) methods. Also, the mechanical properties including tensile strength and elongation at break were measured using a universal tensile testing machine. FTIR results confirmed the formation of the H-bond between PEG and PVA. DSC studies revealed that PEG has a significant plasticization effect on PVA as seen by the drop in the glass transition temperature ( ). The blend with 10 wt% PEG loading was found to be the optimum blend because of good compatibility as shown by FTIR and SEM results and improved thermal properties. PVA/PEG (10%) nanocomposites were prepared using graphene as a nanofiller. It was found that the elongation at break increased by 62% from 147% for the PVA/PEG (10%) blend to 209% for the nanocomposite with graphene loading of 0.2 wt%. The experimental values of tensile strength were compared using the predictive model of Nicolais and Narkis.

Prediction of whiteness index of cotton using bleaching process variables by fuzzy inference system

A fuzzy prediction model has been built based on hydrogen peroxide concentration, temperature and time of bleaching as the input variables and knitted fabric whiteness index as the output variable. The process parameters affecting the whiteness index of cotton knitted fabrics are very non-linear. Fuzzy inference system is a prospective modeling tool as it can map effectively in nonlinear domain with minimum investigational data. Triangular-shaped membership functions were considered for the variables and total 48 rules were created in this study. It was found that the sole effect of the concentration of hydrogen peroxide on whiteness is pretty low, but is affected by temperature noticeably even in a fixed concentration of hydrogen peroxide. The model proposed in the present study has been verified by additional experimental data set. The root mean square, mean absolute error percentage and coefficient of determination (R2) between the predicted and experimental values were found to be 0.536, 0.798 and 0.959 respectively. The results validate that the model can be applied suitably for the prediction of fabric whiteness index in textile industries.