Direct Fabrication of Microcantilever Structures with High Shape Accuracy Using Projection-Based Stereolithography.

Microcantilever structures such as microgears play an important role in precision mechanisms, where highly accurate cantilever characteristics guarantee the reliable function of these structures. Projection-based stereolithography (PSL) technology is widely used to fabricate sophisticated microstructures owing to its high precision and remarkable efficiency, and plenty of works have been done to improve the precision of structures with macroscale. However, the shape accuracy of microcantilever structures fabricated through PSL process is always neglected, which severely hinders its application in precision mechanisms. In this work, we investigated the influence of major factors on the shape accuracy of microcantilever structures in PSL process through orthogonal tests. Different resin materials were tested to investigate the influence of material properties. Printing experiments showed that for a given PSL system, microcantilever structures with confined size could be directly and accurately manufactured using a set of optimized processing parameters, which dramatically speed up the production process and effectively improved the reliability of microcantilevers. This work provides a comprehensive understanding of the capability of PSL to fabricate microcantilever structures and guides the manufacturing processes of micromechanisms with cantilever features, which effectually promotes the industrial application of PSL technology.

A Perovskite Material Screening and Performance Study Based on Asymmetric Convolutional Blocks.

This study introduces an innovative method for identifying high-efficiency perovskite materials using an asymmetric convolution block (ACB). Our approach involves preprocessing extensive data on perovskite oxide materials and developing a precise predictive model. This system is designed to accurately predict key properties such as band gap and stability, thereby eliminating the reliance on traditional feature importance filtering. It exhibited outstanding performance, achieving an accuracy of 96.8% and a recall of 0.998 in classification tasks, and a coefficient of determination (R2) value of 0.993 with a mean squared error (MSE) of 0.004 in regression tasks. Notably, DyCoO3 and YVO3 were identified as promising candidates for photovoltaic applications due to their optimal band gaps. This efficient and precise method significantly advances the development of advanced materials for solar cells, providing a robust framework for rapid material screening.

Arginine and tryptophan-rich dendritic antimicrobial peptides that disrupt membranes for bacterial infection in vivo.

The potent antibacterial activity and low resistance of antimicrobial peptides (AMPs) render them potential candidates for treating multidrug-resistant bacterial infections. Herein, a minimalist design strategy was proposed employing the "golden partner" combination of arginine (R) and tryptophan (W), along with a dendritic structure to design AMPs. By extension, the α/ε-amino group and the carboxyl group of lysine (K) were utilized to link R and W, forming dendritic peptide templates αRn(εRn)KWm-NH2 and αWn(εWn)KRm-NH2, respectively. The corresponding linear peptide templates R2nKWm-NH2 and W2nKRm-NH2 were used as controls. Their physicochemical properties, activity, toxicity, and stability were compared. Among these new peptides, the dendritic peptide R2(R2)KW4 was screened as a prospective candidate owing to its preferable antibacterial properties, biocompatibility, and stability. Additionally, R2(R2)KW4 not only effectively restrained the progression of antibiotic resistance, but also demonstrated synergistic utility when combined with conventional antibiotics due to its unique membrane-disruptive mechanism. Furthermore, R2(R2)KW4 possessed low toxicity (LD50 = 109.31 mg/kg) in vivo, while efficiently clearing E. coli in pulmonary-infected mice. In conclusion, R2(R2)KW4 has the potential to become an antimicrobial regent or adjuvant, and the minimalist design strategy of dendritic peptides provides innovative and encouraging thoughts in designing AMPs.

Three-Dimensional Rock Core-Like Microstructure Fabricated by Additive Manufacturing for Petroleum Engineering.

To improve the recovery rate of oil in the formation, oil recovery technology has been continuously studied. Considering the experimental cost and data measurement in oil recovery research, laboratory oil recovery is the most effective method. The rock core model used in the simulation directly affects whether the research results are credible. However, the current three-dimensional rock core model manufacturing methods and corresponding models lack of reproducible, customizable, and visualized characteristics. In this study, a reproducible rock core model of microsphere accumulation based on the structure of natural rock core was designed and manufactured by microstereolithography. Oil recovery experiments and simulation studies show that the rock core model has similar flow characteristics to natural rock cores. In addition, resin rock core models with different structures and hydrogel rock core models with deformability are also manufactured by microstereolithography and used for simulation analysis. This research provides an effective and reproducible rock core structure model for the experiment of oil recovery research.