We demonstrate an ultrasensitive wearable temperature sensor prepared using an emerging material, graphene nanowalls (GNWs), and its ease of combination with polydimethylsiloxane (PDMS). Fabrication of the sensor allows for a polymer-assisted transfer method making it considerably facile, biocompatible and cost effective. The resultant device exhibits a positive temperature coefficient of resistivity (TCR) as high as 0.214 °C⁻¹, which is three fold higher than that of conventional counterparts. We attribute this to the excellent stretchability and thermal sensitivity of GNWs together with the large expansion coefficient of PDMS. Moreover, the sensor is capable of monitoring body temperature in real time, and it presents a quite fast response/recovery speed as well as long term stability. Such wearable temperature sensors could constitute a significant step towards integration with the next frontier in personalized healthcare and human–machine interface systems.

The lifetime and power conversion efficiency are the key issues for the commercialization of perovskite solar cells (PSCs). In this paper, the development of 2D/3D perovskite hybrids (CA₂PbI₄/MAPbI_xCl_3−x) was firstly demonstrated to be a reliable method to combine their advantages, and provided a new concept for achieving both stable and efficient PSCs through the hybridization of perovskites. 2D/3D perovskite hybrids afforded significantly-improved moisture stability of films and devices without encapsulation in a high humidity of 63 ± 5%, as compared with the 3D perovskite (MAPbI_xCl_3−x). The 2D/3D perovskite-hybrid film did not undergo any degradation after 40 days, while the 3D perovskite decomposed completely under the same conditions after 8 days. The 2D/3D perovskite-hybrid device maintained 54% of the original efficiency after 220 hours, whereas the 3D perovskite device lost all the efficiency within only 50 hours. Moreover, the 2D/3D perovskite hybrid achieved comparable device performances (PCE: 13.86%) to the 3D perovskite (PCE: 13.12%) after the optimization of device fabrication conditions.