As the focus of architecture, furniture, and other fields, wood has attracted extensive attention for its many advantages, such as environmental friendliness and excellent mechanical properties. Inspired by the wetting model of natural lotus leaves, researchers prepared superhydrophobic coatings with strong mechanical properties and good durability on the modified wood surface. The prepared superhydrophobic coating has achieved functions such as oil-water separation and self-cleaning. At present, some methods such as the sol-gel method, the etching method, graft copolymerization, and the layer-by-layer self-assembly method can be used to prepare superhydrophobic surfaces, which are widely used in biology, the textile industry, national defense, the military industry, and many other fields. However, most methods for preparing superhydrophobic coatings on wood surfaces are limited by reaction conditions and process control, with low coating preparation efficiency and insufficiently fine nanostructures. The sol-gel process is suitable for large-scale industrial production due to its simple preparation method, easy process control, and low cost. In this paper, the research progress on wood superhydrophobic coatings is summarized. Taking the sol-gel method with silicide as an example, the preparation methods of superhydrophobic coatings on wood surfaces under different acid-base catalysis processes are discussed in detail. The latest progress in the preparation of superhydrophobic coatings by the sol-gel method at home and abroad is reviewed, and the future development of superhydrophobic surfaces is prospected.

Taxonomic studies of leaves are one of the most effective means of correctly identifying plant species. In this paper, mixed activation function is used to improve the ResNet50 network in order to further improve the accuracy of leaf recognition. Firstly, leaf images of 15 common tree species in northern China were collected from the Urban Forestry Demonstration Base of Northeast Forestry University (45°43′–45°44′ N, 126°37′–126°38′ E, forest type was artificial forest), and a small leaf dataset was established. After that, seven commonly used activation functions were selected to improve the ResNet50 network structure, and the improved network was applied to the transfer learning research of the leaf small dataset. On this basis, five activation functions with better performance were selected for the study of mixed activation functions in deep learning. Two of these five activation functions are arbitrarily selected for combination, and a total of twenty combinations are obtained. Further, the first activation function was used in each combination to replace the first ReLU function after all addition operations in the ResNet50 network residual block structure, and another activation function was used to replace the other position ReLU functions. The experimental results show that in the transfer learning of the leaf small dataset using the ResNet50 deep residual network, the appropriate combination of mixed activation functions can increase the performance of the improved network to a certain extent. Among them, the ELU-Swish1 combination has the most significant improvement effect on the network performance, whose final effective validation accuracy reaches 98.17%. Furthermore, the comparison with GoogLeNet and VGG-16 also demonstrates the excellent performance of the improved ELU-Swish1 ResNet50 (ES-ResNet50) network architecture. Finally, tests on the other two small leaf datasets, Flavia and Swedish, also demonstrate the performance improvement of ES-ResNet50. The validation accuracy of the improved ES-Resnet 50 algorithm on these two datasets reaches 99.30% and 99.39%, respectively. All these experiments prove that the recognition performance of leaf transfer learning using the ES-ResNet50 network is indeed improved, which may be caused by the complementarity of the e-exponential gradient of ELU and Swish1 activation functions in the negative region.

In addition to filtering some sediments, hydrophobic wood sponges can also absorb many organic solvents, particularly crude oil. The leakage of crude oil poses a serious threat to the marine ecosystem, and oil mixed with water also generates great danger for its use. From the perspective of low cost and high performance, wood sponges exhibit great potential for dealing with crude oil pollution. Wood sponge is a renewable material. With a highly oriented layered structure and a highly compressible three-dimensional porous frame, wood sponges are extremely hydrophobic, making them ideal for oil–water separation. Currently, the most common approach for creating wood sponge is to first destroy the wood cell wall to obtain a porous-oriented layered structure and then enhance the oil–water separation ability via superhydrophobic treatment. Wood sponge prepared using various experimental methods and different natural woods exhibits distinctive properties in regards to robustness, compressibility, fatigue resistance, and oil absorption ability. As an aerogel material, wood sponge offers multi-action (absorption, filtration) and reusable oil–water separation functions. This paper introduces the advantages of the use of wood sponge for oil–water separation. The physical and chemical properties of wood sponge and its mechanism of adsorbing crude oil are explained. The synthesis method and the properties are discussed. Finally, the use of wood sponge is summarized and prospected.

Compared with other materials, polyethylene terephthalate (PET) has high transparency, excellent physical and mechanical properties in a wide temperature range and good hygiene and safety, so it is widely used in the packaging industry, especially in the packaging of beverages and foods. The optimization of PET bottles is mainly reflected in three aspects: material optimization, structure optimization and process optimization, among which there is much research on material optimization and process optimization, but there is no complete overview on structure optimization. A summary of structural optimization is necessary. Aiming at structural optimization, the finite element method is a useful supplement to the beverage packaging industry. By combining the computer-aided design technology and using finite element software for finite element simulation, researchers can replace the experimental test in the pre-research design stage, predict the effect and save cost. This review summarizes the development of PET bottles for beverage packaging, summarizes various optimization methods for preventing stress cracking in beverage packaging, and especially focuses on comparing and evaluating the effects of several optimization methods for packaging structure. Finally, the future development of all kinds of optimization based on structural optimization in the field of beverage packaging is comprehensively discussed, including personalized design, the combination of various methods and the introduction of actual impact factor calculation.

The substrate of solar cells with high haze, transparent, flexible, green and low coatings will be needed in the future. This paper reports a method for ultraviolet-assisted delignification of wood in an alkaline solution environment to improve the transmittance of “transparent wood”. Scanning electron microscope (SEM), X-ray diffraction image (XRD), Fourier transform infrared (FTIR) spectroscopy and transmittance-haze and chemical composition analysis were used to explore the mechanisms underlying the effect of ultraviolet-assisted lignin modification on the optical properties of “transparent wood”. The results show that UV-assisted delignification accelerates the rate of removal of lignin and chromogenic groups, which in turn improves the optical properties of the “transparent wood”, with UV-assisted lignin modification for 2 h increasing the light transmission of the “transparent wood” by 20%. UV-assisted delignification for 4 h and impregnation resulted in “transparent wood” with a transparency of 71% and a haze of 90%. This report provides a rapid and easy method to prepare high-quality “transparent wood”. The “transparent wood” with high transmittance and high haze is a potential candidate for transparent solar substrates. Meanwhile, this method is enlightening for high quality, fast and green preparation of other derived functional materials based on lignin wood.