Enhancement of integrated nano-sensor performance comprised of electrospun PANI/carbonaceous material fibers for phenolic detection in aqueous solutions

The detection of trace levels of organic residue in water samples is a key health issue. This manuscript describes the fabrication of integrated nano-sensors composed of electrospun microfibers consisting of a nanocomposite of carbonaceous materials (CNMs) containing polyaniline (PANI) and polycaprolactone (PCL) for phenolic detection in aqueous solutions. The morphology of the resulting microfiber composite was characterized by scanning electron microscopy. It revealed elongated fibers with a highly interconnected web-like pattern in the presence of reduced graphene oxide (rGO). Shorter microfibers were observed in the composite filled with multi-walled carbon nanotubes (MWCNTs), whereas large agglomerates were formed upon the incorporation of single-walled CNTs (SWCNTs) and graphene 300 (G300). Comparative analysis showed that the PANI/CNM sensors exhibited the best electrochemical properties, in particular in the presence of rGO and MWCNTs, where greater electrical conductivity was achieved, i.e., 4.33 × 10-3 and 7.22 × 10-4 S/cm, respectively, as compared to the PANI-PCL sensor (3.79 × 10-4 S/cm). All the PANI/CNM sensors exhibited high sensitivity. Notably, PANI/rGO was found to have a detection limit of 8.34 × 10-3 µM for aminophenol. All the sensors exhibited good selectivity in the presence of interference to detecting phenolic compounds in aqueous solutions, thus confirming their value for industrial applications.

Effect of Ultrasonication Parameters on the Structural, Morphological, and Electrical Properties of Polypyrrole Nanoparticles and Optimization by Response Surface Methodology

Polypyrrole (PPy) nanoparticles are reliable conducting polymers with many industrial applications. Nevertheless, owing to disadvantages in structure and morphology, producing PPy with high electrical conductivity is challenging. In this study, a chemical oxidative polymerization-assisted ultra-sonication method was used to synthesize PPy with high conductivity. The influence of critical sonication parameters such as time and power on the structure, morphology, and electrical properties was examined using response surface methodology. Various analyses such as SEM, FTIR, DSC, and TGA were performed on the PPy. An R² value of 0.8699 from the regression analysis suggested a fine correlation between the observed and predicted values of PPy conductivity. Using response surface plots and contour line diagrams, the optimum sonication time and sonication power were found to be 17 min and 24 W, respectively, generating a maximum conductivity of 2.334 S/cm. Meanwhile, the model predicted 2.249 S/cm conductivity, indicating successful alignment with the experimental data and incurring marginal error. SEM results demonstrated that the morphology of the particles was almost spherical, whereas the FTIR spectra indicated the presence of certain functional groups in the PPy. The obtained PPy with high conductivity can be a promising conducting material with various applications, such as in supercapacitors, sensors, and other smart electronic devices.

Experimental and Computational Study of Mechanical and Thermal Characteristics of h-BN and GNP Infused Polymer Composites for Elevated Temperature Applications

Polymer-based nanocomposites are being considered as replacements for conventional materials in medium to high-temperature applications. This article aims to discover the synergistic effects of reinforcements on the developed polymer-based nanocomposite. An epoxy-based polymer composite was manufactured by reinforcing graphene nanoplatelets (GNP) and h-boron nitride (h-BN) nanofillers. The composites were prepared by varying the reinforcements with the step of 0.1 from 0.1 to 0.6%. Ultrasonication was carried out to ensure the homogenous dispersion of reinforcements. Mechanical, thermal, functional, and scanning electron microscopy (SEM) analysis was carried out on the novel manufactured composites. The evaluation revealed that the polymer composite with GNP 0.2 by wt % has shown an increase in load-bearing capacity by 265% and flexural strength by 165% compared with the pristine form, and the polymer composite with GNP and h-BN 0.6 by wt % showed an increase in load-bearing capacity by 219% and flexural strength by 114% when compared with the pristine form. Furthermore, the evaluation showed that the novel prepared nanocomposite reinforced with GNP and h-BN withstands a higher temperature, around 340 °C, which is validated by thermogravimetric analysis (TGA) trials. The numerical simulation model is implemented to gather the synthesised nanocomposite's best composition and mechanical properties. The minor error between the simulation and experimental data endorses the model's validity. To demonstrate the industrial applicability of the presented material, a case study is proposed to predict the temperature range for compressor blades of gas turbine engines containing nanocomposite material as the substrate and graphene/h-BN as reinforcement particles.

Development and Characterization of Integrated Nano-Sensors for Organic Residues and pH Field Detection

Meeting global water quality standards is a real challenge to ensure that food crops and livestock are fit for consumption, as well as for human health in general. A major hurdle affecting the detection of pollutants in water reservoirs is the lapse of time between the sampling moment and the availability of the laboratory-based results. Here, we report the preparation, characterization, and performance assessment of an innovative sensor for the rapid detection of organic residue levels and pH in water samples. The sensor is based on carbonaceous nanomaterials (CNMs) coated with an intrinsically conductive polymer, polyaniline (PANI). Inverse emulsion polymerizations of aniline in the presence of carbon nanotubes (CNTs) or graphene were prepared and confirmed by thermogravimetric analysis and high-resolution scanning electron microscopy. Aminophenol and phenol were used as proxies for organic residue detection. The PANI/CNM nanocomposites were used to fabricate thin-film sensors. Of all the CNMs, the smallest limit of detection (LOD) was achieved for multi-walled CNT (MWCNT) with a LOD of 9.6 ppb for aminophenol and a very high linearity of 0.997, with an average sensitivity of 2.3 kΩ/pH at an acid pH. This high sensor performance can be attributed to the high homogeneity of the PANI coating on the MWCNT surface.