Textile-based humidity sensors can be an important component of smart wearable electronic-textiles and have potential applications in the management of wounds, bed-wetting, and skin pathologies or for microclimate control in clothing. Here, we report a wearable textile-based humidity sensor for the first time using high strength (∼750 MPa) and ultratough (energy-to-break, 4300 J g) SWCNT/PVA filaments via a wet-spinning process. The conductive SWCNT networks in the filaments can be modulated by adjusting the intertube distance by swelling the PVA molecular chains via the absorption of water molecules. The diameter of a SWCNT/PVA filament under wet conditions can be as much as 2 times that under dry conditions. The electrical resistance of a fiber sensor stitched onto a hydrophobic textile increases significantly (by more than 220 times) after water sprayed. Textile-based humidity sensors using a 1:5 weight ratio of SWCNT/PVA filaments showed high sensitivity in high relative humidity. The electrical resistance increases by more than 24 times in a short response time of 40 s. We also demonstrated that our sensor can be used to monitor water leakage on a high hydrophobic textile (contact angle of 115.5°). These smart textiles will pave a new way for the design of novel wearable sensors for monitoring blood leakage, sweat, and underwear wetting.

In this manuscript, we report a novel highly sensitive wearable strain sensor based on a highly stretchable multi-walled carbon nanotube (MWCNT)/Thermoplastic Polyurethane (TPU) fiber obtained via a wet spinning process.

We report a facile green approach to the synthesis of silver nanoparticles (Ag NPs) on the surface of graphene oxide nanosheets functionalized with mussel-inspired dopamine (GO-Dopa) without additional reductants or stabilizers at room temperature. The resulting hybrid Ag/GO-Dopa exhibits good dispersity and excellent catalytic activity in the reduction of nitroarenes.

No abstract

A numerical simulation of the mold filling process during resin transfer molding (RTM) was performed using the boundary element method (BEM). Experimental verification was also done. Darcy's law for anisotropic porous media was employed along with mass conservation to construct the governing differential equation. The resulting potential problem was solved with the boundary element technique. As the calculation domain changed due to the proceeding resin front, boundary nodes were rearranged for each time step. The node which goes out of the calculation domain as time progresses was relocated at the intersection between the solid boundary and the line drawn between the node at previous and at current time steps. Results showed good agreement with data for a rectangular mold. To evaluate further the validity of the model, the area velocity of the resin‐impregnated region during mold filling was calculated. The area velocity thus calculated was compared with the corresponding resin inlet velocity to check the mass conservation. A close agreement was observed, which renders confidence in the resin front proceeding algorithm. Numerical calculations were also performed for complicated geometries to illustrate the effectiveness of the current method.