Currently, there is a growing demand for water treatment technologies considering global environmental challenges such as degradation and depletion of water resources. Micro- and nanobubble (MNB) technology and its application for wastewater treatment has emerged as a problem-solving alternative for such challenges. This paper reviews the important studies on water treatment in the areas of MNBs and discusses their fundamental properties, such as bubble stability (as tiny entities in water solutions), generation methods, and various chemical and physical features. The paper further overviews the current status of MNB application in water treatment processes such as flotation, aeration, and disinfection and its uses in various sectors, including agriculture, aquaculture, medical, and industry. Based on this review, studies regarding MNBs' basic properties, generation, and application are identified and recognized for future research. This study concludes that despite the promising role of MNBs in water-related application, the current status of research has not reached its true potential. Specifically, there is a need to enhance MNB application at a broader scale.

In order to classify several kinds of rice (including the rice grown by plasma seed treatment), the datasets of the hyperspectral images (HSIs) of rice were constructed. Multilayer perceptron (MLP) has a good classification performance on rice HSIs because it removes translation invariance and local connectivity. Residual learning can improve the feature extraction ability of MLP network because of retaining the original information, preventing the model from degenerating, and facilitating the rapid convergence of the model. Therefore, a rice hyperspectral image classification model based on MLP network and residual learning is proposed. The results show that the proposed model has a higher classification accuracy (98.48%) than the other common classification models. In addition, the model has been verified on two public datasets with the accuracy higher than 99.95%.

We design a graphene-based broadband tunable terahertz metamaterial absorber (MMA). Its structure consists of a surface graphene pattern layer, a medium layer and an underlying metal film. CST simulation results show that the absorption bandwidth for more than 90% absorption rate reaches 2.12 THz, and the range is 3.2–5.32 THz. The absorption bandwidth for more than 99% absorption rate reaches 1.38 THz, and the range is 3.45–4.83 THz, which was not achieved by most of the previous MMA. Multiple reflection interference theory is used to confirm the simulation results. In order to explore the physical mechanism of wideband absorption, we study the surface electric field distribution of the structure. We also find that the absorber has polarization insensitivity and wide-angle incidence characteristics. The absorption frequency of the absorber can be adjusted by changing the chemical potential of graphene. Therefore, the absorber has potential applications in terahertz absorption, filtering and sensing.

Chitosan is widely used in the production of various hydrogels due to its non-biological toxicity, good biocompatibility, and strong biodegradability. However, chitosan-based hydrogels have not been widely used in tissue engineering due to their poor mechanical strength, poor stability and high biotoxicity of cross-linking agents. As a green technology, low temperature plasma is rich in active groups that can be involved in various chemical reactions, such as replacing the components on the chitosan chain, contributing to the cross-linking of chitosan. In this study, a plasma-assisted preparation method of chitosan-based hydrogels was developed and the properties, including mechanics, water absorption, and degradation (or stability), were characterized and analyzed. It is proved that plasma treatment plays a significant role in improving the mechanical strength and stability of hydrogels.