Robust construction of polyvinyl alcohol intercalated graphene oxide nanofiltration membrane for desalination via pervaporation

The construction and modification of a Graphene Oxide (GO) membrane, incorporating polyvinyl alcohol (PVA) cross-linked with maleic acid (MA) and supported by a nylon membrane, have been successfully completed. Systematic variations in PVA and MA concentrations were conducted to achieve membranes with favorable characteristics, stability, and excellent desalination performance. Optimization studies utilizing the Central Composite Design (CCD) revealed that the most optimal desalination results were obtained with 10 mL of PVA (0.1 mg mL-1) and 0.9 M of MA (GO-MA0.9-PVA10/Nylon membrane). Experimental findings demonstrated that the inclusion of PVA and MA resulted in an increased interlayer distance of GO and enhanced membrane stability. The addition of PVA increases GO membrane hydrophilicity, while the addition of MA reduces membrane hydrophilicity. The GO-MA0.9-PVA10/Nylon membrane exhibited the highest desalination performance, boasting a rejection value exceeding >99.9% and a permeance of 18.76 kg m-2.h-1 under 1% NaCl feed at a temperature of 50 °C. This membrane demonstrated consistent desalination performance stability over an extended period of up to 70 h. Moreover, it exhibited durability through 8 cycles of 24-h usage with washing treatment. In conclusion, the GO-MA0.9-PVA10/Nylon membrane is strongly recommended for practical applications, outperforming other membrane options based on the comprehensive evaluation of its stability and desalination efficiency.

Size Prediction and Electrical Performance of Knitted Strain Sensors

Benefitting from the multifunctional properties of knitted fabrics with elasticity, flexibility, and high resilience, knitted strain sensors based on structure and strain performance are widely utilized in sports health due to their adaptability to human movements. However, the fabrication process of common strain sensors mainly relies on experienced technicians to determine the best sensor size through repeated experiments, resulting in significant size errors and a long development cycle. Herein, knitted strain sensors based on plain knit were fabricated with nylon/spandex composite yarn and silver-plated nylon yarn using a flat knitting process. A size prediction model of knitted strain sensors was established by exploring the linear relationship between the conductive area size of samples and knitting parameters via SPSS regression analysis. Combined with stable structures and high performance of good sensitivity, stability, and durability, the knitted strain sensors based on size prediction models can be worn on human skin or garments to monitor different movements, such as pronunciation and joint bending. This research indicated that the reasonable size control of the knitted strain sensor could realize its precise positioning in intelligent garments, exhibiting promising potential in intelligent wearable electronics.

Development of a multifunctional graphene/Fe-loaded polyester textile: robust electrical and catalytic properties

A graphene/Fe loaded polyester fabric (PET) with robust electrical and catalytic properties has been successfully developed for the first time via a simple coating-incorporation method using hyperbranched poly(amidoamine) (PAMAM) dendrimer as the binder. Both graphene oxide (GO/rGO) and zerovalent iron (Fe0) nanoparticles were loaded on the polyester fabric surface before and after chemical grafting of PAMAM. Full characterization of fabrics before and after modifications has been performed by sessile droplet goniometry, ζ-potential, K/S coating evenness, SEM, XPS, FTIR, TGA and DSC analyses. The results showed successful and uniform coating of GO/rGO and loading of Fe0 on PET and also showed the correlation between the type of chemical moiety responsible for uniform GO coating, high Fe0 loading and their electrical and catalytic activities. Sheet resistance (Rsh) analysis was carried out to measure the conductivity of the samples. The lowest Rsh (corresponding to high conductivity) was found in PET-PAM-rGO-Fe0 (0.74 ± 0.13 kΩ sq-1) followed by PET-rGO-Fe0 (1.32 ± 0.18 kΩ sq-1), PET-PAM-rGO (2.96 ± 0.08 kΩ sq-1) and PET-rGO (3.41 ± 0.34 kΩ sq-1). Furthermore, Fe0-loaded samples were found to be effective in the catalytic removal of toxic water pollutants (crystal violet dye) with ∼99% removal of pollutants in around one hour, as observed by UV-vis spectroscopy. The relatively high electrical conductivity and catalytic activity of PET-PAM-rGO-Fe0 are related to the role played by PAMAM in the uniform rGO coating and high Fe0 loading. These findings are of great importance as they allow envisaging the development of multifunctional textiles for combined smart and green chemistry application.