Due to the unique conditions of the space environment and abundant resources, the field investigation and study of the Moon, Earth’s sole natural satellite, represent a crucial milestone in China’s forthcoming deep space endeavors. The successful collection of lunar soil by the Chang’E-5 mission signifies the next phase of the lunar exploration program, which aims to establish a preliminary research station on the lunar south pole. Highly adhesive fine dust particles with an adhesion strength of 0.1 to 1.0 kN/m², which originate from the regolith, disperse throughout the lunar surface. These particles exhibit a lasting attraction and subsequent persistent adhesion to the surface of spacecraft or spacesuits. The accumulation of highly adhesive dust on spacecraft presents a serious issue to hinder long-term extravehicular activity and the establishment of a permanent station on lunar surface. In contrast to the immediate physical damage caused by hypervelocity (> 1.0 km/s) impacts, this adhesion observed at low- velocity (0.01 to 100 m/s) collisions can more unobtrusively and mortally degenerate the performance of equipment. In recent years, many interaction models have been developed to forecast the adhesion and ejection dynamics of lunar dust on various surfaces. Most researches on the electrostatic force applied on dust particles near the surface use point-charge approximation. Although this simplification makes the simulation easier, the error can be large due to the polarization of dust induced by the image charge.

Recently, the team led by Guoqi Li and Bo Xu from the Institute of Automation, Chinese Academy of Sciences, published a research paper in National Science Review. The team, drawing on principles from neuroscience, proposed an innovative neuromorphic spike-based large language model, aimed at enhancing the energy efficiency and interpretability of LLMs. This research not only opens new directions for the development of efficient AI but also provides valuable insights for the design of next-generation neuromorphic chips.

Researchers in China conducted a comprehensive overview of the fabrication of magnetic robotic materials, structural design, actuation systems, and their application scenarios. In terms of fabrication, permanent magnetic particles are discussed. Structural design encompasses one-dimensional, two-dimensional, and three-dimensional architectures, as well as bio-inspired structures. The actuation systems primarily introduce coil-based mechanisms and permanent magnet-based approaches. Application scenarios mainly include targeted drug delivery and minimally invasive surgery, among others.

Two-dimensional (2D) materials have emerged as a significant class of materials promising for photocatalysis, and defect engineering offers an effective route for enhancing their photocatalytic performance. In this mini-review, a first-principles design perspective on defect engineering in 2D materials for photocatalysis is provided. Various types of defects in 2D materials, spanning point, line, and planar defects are explored, and their influence on the intrinsic properties and photocatalytic efficacy of these materials is highlighted. Additionally, the use of theoretical descriptors to characterize the stability, electronic, optical, and catalytic properties of 2D defective systems is summarized. Central to the discussion is the understanding of electronic structure, optical properties, and reaction mechanisms to inform the rational design of photocatalysts based on 2D materials for enhanced photocatalytic performance. This mini-review aims to provide insights into the computational design of 2D defect systems tailored for efficient photocatalytic applications.

The environmental, social, and governance (ESG) report is globally recognized as a keystone in sustainable enterprise development. However, current literature has not concluded the development of topics and trends in ESG contexts in the twenty-first century. Therefore, we selected 1114 ESG reports from global firms in the technology industry to analyze the evolutionary trends of ESG topics by text mining. We discovered the homogenization effect toward low environmental, medium governance, and high social features in the evolution. We also designed a strategic framework to look closer into the dynamic changes of firms’ within-industry representiveness and cross-sector distinctiveness, which demonstrates corporate social responsibility and sustainability. We found that companies are gradually converging toward the third quadrant, which indicates that firms contribute less to industrial outstanding and professional distinctiveness in ESG reporting. Firms choose to imitate ESG reports from each other to mitigate uncertainty and enhance behavioral legitimacy.

Professor Keisuke Fujii, a leading researcher in quantum science at The University of Osaka, has been named among the Quantum 100, a major global initiative celebrating the centennial of the development of quantum mechanics in 2025, proclaimed by the United Nations and led by UNESCO.