Owing to harsh working environments and complex industrial requirements, traditional gas sensors are prone to deformation damage, possess a limited detection range, require a high working temperature, and display low reliability, thereby necessitating the development of flexible and low-temperature gas sensors. In this study, we developed a low-temperature polyimide (PI)-based flexible gas sensor comprising a reduced graphene oxide (rGO)/MoS₂ composite. The micro-electro-mechanical system technology was used to fabricate Au electrodes on a flexible PI sheet to form a “sandwiched” sensor structure. The rGO/MoS₂ composites were synthesized via a one-step hydrothermal method. The gas-sensing response was the highest for the composite comprising 10% rGO. The structure of this material was characterized, and a PI-based flexible gas sensor comprising rGO/MoS₂ was fabricated. The optimal working temperature of the sensor was 141 °C, and its response-recovery time was significantly short upon exposure to 50–1500 ppm NH₃. Thus, this sensor exhibited high selectivity and a wide NH₃ detection range. Furthermore, it possessed the advantages of low power consumption, a short response-recovery time, a low working temperature, flexibility, and variability. Our findings provide a new framework for the development of pollutant sensors that can be utilized in an industrial environment.

Despite the numerous available treatments for cancer, many patients succumb to side effects and reoccurrence. Zinc oxide (ZnO) quantum dots (QDs) are inexpensive inorganic nanomaterials with potential applications in photodynamic therapy. To verify the photoluminescence of ZnO QDs and determine their inhibitory effect on tumors, we synthesized and characterized ZnO QDs modified with polyvinylpyrrolidone. The photoluminescent properties and reactive oxygen species levels of these ZnO/PVP QDs were also measured. Finally, in vitro and in vivo experiments were performed to test their photodynamic therapeutic effects in SW480 cancer cells and female nude mice. Our results indicate that the ZnO QDs had good photoluminescence and exerted an obvious inhibitory effect on SW480 tumor cells. These findings illustrate the potential applications of ZnO QDs in the fields of photoluminescence and photodynamic therapy.

Medical image technology is becoming more and more important in the medical field. It not only provides important information about internal organs of the body for clinical analysis and medical treatment but also assists doctors in diagnosing and treating various diseases. However, in the process of medical image feature extraction, there are some problems, such as inconspicuous feature extraction and low feature preparation rate. Combined with the learning idea of convolution neural network, the image multifeature vectors are quantized in a deeper level, which makes the image features further abstract and not only makes up for the one‐sidedness of single feature description but also improves the robustness of feature descriptors. This paper presents a medical image processing method based on multifeature fusion, which has high feature extraction effect on medical images of chest, lung, brain and liver, and can better express the feature relationship of medical images. Experimental results show that the accuracy of the proposed method is more than 5% higher than that of other methods, which shows that the performance of the proposed method is better.