In this work, layered hybrid composites formed by tin oxide (SnO) nanoparticles synthesized by hydrolysis and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) have been analyzed. Prior to the composite study, both SnO and PEDOT:PSS counterparts were characterized by diverse techniques, such as X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), photoluminescence (PL), atomic force microscopy (AFM), optical absorption and Hall effect measurements. Special attention was given to the study of the stability of the polymer under laser illumination, as well as the analysis of the SnO to SnO2 oxidation assisted by laser irradiation, for which different laser sources and neutral filters were employed. Synergetic effects were observed in the hybrid composite, as the addition of SnO nanoparticles improves the stability and electrical conductivity of the polymer, while the polymeric matrix in which the nanoparticles are embedded hinders formation of SnO2. Finally, the Si passivation behavior of the hybrid composites was studied.

Li-ion batteries (LiB) play nowadays a major role in several technological fields. In addition to enhanced high capacity and long cyclability, some other issues regarding safety, materials sustainability, and low cost remain unsolved. Tin oxide (SnO2) presents several of those advantages as an anode material; however, some aspects still require to be investigated such as capacity fading over cycles. Herein, tin oxide nanoparticle-based anodes have been tested, showing high capacities and a significant cyclability over more than 150 cycles. A complementary strategy introducing doping elements such as Li and Ni during the synthesis by hydrolysis has been also evaluated versus the use of undoped materials, in order to assess the dependence on SnO2 quality and properties of battery performance. Diverse aspects such as the Sn charge state in the synthesized nanoparticles, the variable incorporation of dopants, and the structure of defects have been considered in the understanding of the obtained capacity.

Early-stage fire-warning systems (EFWSs) have attracted significant attention owing to their superiority in detecting fire situations occurring in the pre-combustion process. Substantial progress on EFWSs has been achieved recently, and they have presented a considerable possibility for more evacuation time to control constant unintentional fire hazards in our daily life. This review mainly makes a comprehensive summary of the current EFWSs, including the working mechanisms and their performance. According to the different working mechanisms, fire alarms can be classified into graphene oxide-based fire alarms, semiconductor-based fire alarms, thermoelectric-based fire alarms, and fire alarms on other working mechanisms. Finally, the challenge and prospect for EFWSs are briefly provided by comparing the art of state of fire alarms. This work can propose a more comprehensive understanding of EFWSs and a guideline for the cutting-edge development direction of EFWSs for readers.

Since the beginning of the COVID-19 pandemic, the use of face masks has become not only mandatory in several countries but also an acceptable approach for combating the pandemic. In the quest for designing an effective and useful face mask, triboelectric nanogenerators (TENGs) have been recently proposed. Novel functionalities are provided with the use of TENGs in face masks due to the induced triboelectrification generated by the exhaled and inhaled breath, allowing their use as an energy sensor. Nonetheless, within the face mask, the presence of nontextile plastics or other common triboelectric (TE) materials can be undesired. Herein, we propose the use of an all-fabric TENG (AF-TENG) with the use of high molecular weight polyethylene (UHMWPE) and cotton fabric as negative and positive triboelectric layers, respectively. With these materials, it is possible to detect the breathing of the patient, which in the case of not detecting a signal over a few minutes can trigger an alarm locally, providing valuable time. Also, in this article, we have sent breathing signals locally and remotely to distances up to 20 km via Wi-Fi and LoRa, the same as warning signals in the case of detecting anomalies. This work reveals the use of TENGs in smart face masks as an important tool to be used in difficult epidemiological periods to the general public, bringing much more comfort and relaxation to patients and elderly in today’s society, and based on pristine eco-friendly materials.