In an era of environmentally friendly development, methods of the green synthesis of zinc oxide nanoparticles (ZnO NPs) from plant extracts have become a focus of research attention because of the benefits of environmental sustainability, simplicity, and low price. The present review introduces a green mechanism for the synthesis of ZnO NPs using the extracts of plants, exploring factors that influence the morphology of ZnO NPs and their antibacterial properties, and the mechanisms of antibacterial action. The results indicate that the factors that influence morphology include the intrinsic crystallographic morphological properties and conditions of the preparation of ZnO NPs. In terms of preparation conditions, the influence of plant extract concentration, precursor concentration, reaction time, and calcination temperature on NP morphology is related to the species of plants used, with precursor concentration the most significant factor affecting the morphology of ZnO NPs. A pH of 12 appears be the most appropriate alkalinity for the synthesis of ZnO NPs from plant extracts. In addition, the synthesized ZnO NPs display excellent antibacterial properties, the mechanism of which involves photocatalysis, reactive oxygen species, and interactions between ZnO NPs and bacterial surfaces. Factors influencing the antibacterial properties are the type of bacteria and the concentration and morphology of ZnO NPs. Finally, the methods of preparation of antibacterial textiles using synthetic ZnO NPs are discussed in relation to the preparation of antibacterial fibers, fabric, and composite textiles. Here, the future trend of such antibacterial textiles is considered, providing the direction for further research of antibacterial textiles.

Second-hand consumption of clothing plays a vital role in promoting the overall global trend of low-carbon transition; however, the COVID-19 outbreak put this consumption model into a development dilemma. Cultivating consumers’ sustainable behavior will be an effective way to promote the sustainable development of the apparel industry. Based on the unified theory of acceptance and use of technology (UTAUT), this study starts with fashion-sharing behavior and investigates the antecedents that influence consumers’ use of second-hand clothing-sharing platforms in the post-pandemic era. The research background involves the Chinese clothing-sharing market in the growing period. The findings revealed that the pandemic raised people’s awareness of health and hygiene protection. In addition, the cleaning problem of platform clothing has become the primary reason for curbing consumers’ choice of sharing. High-cost performance, high efficiency, and convenience can stimulate consumers to use shared services. Considering that the pandemic has driven consumer economic fluctuations, perceived economic risks could widen the gap between willingness and behavior. In conclusion, platforms must fully realize the transparency of the clothing cleaning and maintenance process, improve their own construction level such as ease of use, convenience, and safety, and incorporate functional clothing-sharing to refine people’s sustainable consumption habits.

Biosynthesis of metal-oxide nanoparticles using plant extracts has been attracting increasing interest. In this study, we focused on the green synthesis of zinc oxide (ZnO) nanomaterials using zinc acetate as a precursor and mulberry fruit extract as a green reducing agent and determined the antioxidant activity. Powder X-ray diffraction and UV-Vis and Fourier Transform Infra-Red (FT-IR) spectroscopy were used for structure elucidation and to determine the crystallinity of the synthesized product. The morphology of samples was determined using Scanning Electron Microscopy (SEM). Our results indicated the successful synthesis of ZnO nanoparticles. SEM findings revealed the nanoparticles to be spherical; they were found to agglomerate and showed a narrow space between particles, which could be indicative of improved activity. The antioxidant activity of ZnO nanoparticles was determined using a 2,2-Diphenyl-1-Picryl-Hydrazyl (DPPH) free-radical scavenging assay taking into account time and concentration. Our results indicated that ZnO nanoparticles with mulberry fruit extract that were synthesized using green chemistry could effectively scavenge the free DPPH radicals, thereby confirming their superior antioxidant activity.

Clothing-based respiratory monitoring can provide real-time non-invasive respiratory monitoring services for subjects, and can be used as a reference for daily health observation. In this study, an optical fiber sensing Section woven into plain fabric is produced by a hand-weaving machine, and the produced sensing fabric is then made into a respiratory monitoring garment. This paper explored the luminescence and coupling principle of notched optical fiber through theoretical analysis and simulation, and demonstrated the feasibility of making it into respiratory sensing fabric. We used this structure to make a fabric and then sew the fabric with the yoke to make a smart garment. In testing, we obtained the static respiratory waveform and the respiratory rate (R-R) during daily common movements, which were also compared with two types of commercial sensors. The results showed that the smart garment based on optical fiber sensing fabric maintains good consistency with the monitoring waveform of commercial sensors and good R-R obtained in static motion (error not more than 2 rpm). Monitoring tests showed that the garment has high monitoring accuracy and motion monitoring stability. Moreover, it was also very comfortable and can be used as daily respiratory monitoring equipment.

Clothing image in the e-commerce industry plays an important role in providing customers with information. This paper divides clothing images into two groups: pure clothing images and dressed clothing images. Targeting small and medium-sized clothing companies or merchants, it compares traditional machine learning and deep learning models to determine suitable models for each group. For pure clothing images, the HOG+SVM algorithm with the Gaussian kernel function obtains the highest classification accuracy of 91.32% as compared to the Small VGG network. For dressed clothing images, the CNN model obtains a higher accuracy than the HOG+SVM algorithm, with the highest accuracy rate of 69.78% for the Small VGG network. Therefore, for end-users with only ordinary computing processors, it is recommended to apply the traditional machine learning algorithm HOG+SVM to classify pure clothing images. The classification of dressed clothing images is performed using a more efficient and less computationally intensive lightweight model, such as the Small VGG network.

As the electron transport layer of dye‐sensitized solar cells (DSSCs), the photoanode is an important component that affects photoelectric conversion efficiency (PCE). The commonly used material titanium dioxide (TiO₂) is difficult to prepare as nanostructures with large specific surface area, which affects dye loading and electrolyte diffusion. Herein, TiO₂ nanofibers and ZnO‐TiO₂ composite nanofibers with different molar ratios are synthesized by electrospinning technology. The above nanofibers are coated on photoanodes by the doctor blade method to assemble DSSCs. The influence of the composite ratio of ZnO‐TiO₂ composite nanofibers on the photoelectric performance of the assembled DSSCs is explored. The ZnO‐TiO₂ composite nanofibers with a molar ratio of 1 : 2 have large specific surface area and porosity and have the smallest charge transfer resistance at the photoanode‐electrolyte interface. The PCE of the nanofiber‐modified DSSCs reaches a maximum of 3.66%, which is 56% higher than that of the TiO₂ nanofiber‐modified DSSCs. The photovoltaic parameters such as open circuit voltage (V_OC), current density (J_SC), and fill factor (FF) are 0.58 V, 10.36 mA/cm², and 0.61, respectively. Proper compounding of zinc oxide (ZnO) can not only make the nanofibers absorb more dyes and enhance the light‐harvesting ability but also improve the diffusion of the electrolyte and enhance the electron transport, thus successfully improving the power conversion efficiency of DSSCs.