A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has advanced the characterization and retrieval capability evaluation of microphysical properties of Venusian clouds and haze. 

A research team led by Professor JIANG Changlong at the Hefei Institutes of Physical Science, Chinese Academy of Sciences, has developed a highly sensitive, real-time sensor for detecting trace water, addressing key challenges in modern industrial quality control and environmental monitoring. 

Nitrogen dioxide is one of the most harmful air pollutants in urban and industrial regions, contributing to respiratory disease, smog formation, and climate forcing. As governments tighten air quality standards worldwide, scientists are searching for affordable and efficient ways to remove this toxic gas before it reaches the atmosphere. A new theoretical study reveals that a simple and naturally abundant element, potassium, could dramatically enhance the ability of biochar to capture and chemically transform nitrogen dioxide.

Cities are growing. Forests are shrinking. But what’s happening beneath our feet—in the soil of the very trees that line our streets and parks—may be even more critical to the planet’s future than we realize.

As global temperatures continue to rise, scientists are working to understand how warming affects the planet’s carbon cycle. A new study published in Biocontaminant reveals that higher temperatures significantly alter how aquatic microbes process carbon released during the decomposition of animal carcasses, with important implications for water quality and climate change predictions.

Artificial intelligence (AI) is rapidly advancing across modern healthcare, yet its role in pediatric surgery remains limited and ethically complex. 

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.