A research team led by Prof. WAN Yinhua from the Institute of Process Engineering has developed a machine learning framework to analysis virus filtration processes in therapeutic protein purification. The new method enables intelligent identification of critical parameters affecting virus retention efficiency and provides predictive guidance for process optimization.
A research team led by Prof. WANG Shuqiang from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences introduced a Prior-Guided Adversarial Learning with Hypergraph (PALH) model for predicting abnormal connections in Alzheimer's disease.
Scientists from the Institute of Metal Research have proposed a new deep correlation between the spin splitting torque and the Fermi surface geometry, achieving a quantum limit of 100% in a system with a flat Fermi surface.
Researchers from Yunnan University, the Shanghai Astronomical Observatory of the Chinese Academy of Sciences, and the National Astronomical Observatory of Japan have unveiled new insights into the fragmentation mechanisms of high-mass star-forming regions.
A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences, has developed a basalt fiber/cotton fiber composite yarn that integrates weavability with multiple functional properties.
A research team from the Qingdao Institute of Bioenergy and Bioprocess Technology of the Chinese Academy of Sciences has developed a confined crystallization strategy. This approach reconstructs—i.e., redesigns—the crystallization pathway during spray coating at its source through solvation structure regulation. Specifically, the team established a localized high-concentration (LHC) precursor system within individual spray droplets, enabling precise control over nucleation behavior during film formation.
A new study led by Dr. JIANG Yi from the Institute of Psychology of the Chinese Academy of Sciences has revealed the first clear evidence that visual awareness acts as a "conductor" that refines the speed, precision, and neural coordination of attentional rhythmic sampling.
Researchers from the Institute of Genetics and Developmental Biology developed an AI model named TillerPET, which overcomes these longstanding limitations by enabling simultaneous in-situ high-throughput phenotyping of tiller number and compactness from post-harvest rice RGB images. It demonstrates stable performance across multi-year, multi-location rice RGB datasets.
A new study reveals that global progress on numerous SDGs with high initial benchmarks has either stalled or gone into reverse. In contrast, SDG indicators with lower baseline performance continue to register gains. Researchers caution that the vast majority of countries will fail to meet their 2030 SDG targets under current trends.
Researchers from the Institute of Applied Ecology of the Chinese Academy of Sciences has developed a "top-down" synthetic microbiome strategy to enrich microbial consortia capable of efficient lignin degradation from straw compost and straw-returning soils, providing new insight into how microbial communities work together to break down lignin.
A new study led by the Aerospace Information Research Institute of the Chinese Academy of Sciences, along with their collaborators, has demonstrated that high pressure can significantly enhance and precisely tune terahertz (THz) radiation from the two-dimensional semiconductor gallium telluride (GaTe).
A research team led by Prof. NIE Sheng from the Aerospace Information Research Institute of the Chinese Academy of Sciences has developed a new bathymetric mapping framework. This framework integrates the indirect inversion of land Elevation Satellite-2 (ICESat-2) LiDAR data with multi-source remote sensing observations. By combining wave-based indirect bathymetry, multi-source feature fusion, and a temporal sample-transfer strategy, it achieves high-accuracy, wide-coverage mapping in optically complex shallow waters.
A research team led by Prof. YE Jichun from the Ningbo Institute of Materials Technology and Engineering of the Chinese Academy of Sciences, in collaboration with partners, has proposed a synergistic technical solution enabling industrial tunnel oxide passivating contact (TOPCon) solar cells to simultaneously achieve high efficiency, low cost, and excellent bifacial power generation performance.
A joint research team from the Institute of Metal Research and Zhengzhou University has achieved power conversion efficiency surpassing 20% in flexible modules capable of withstanding a range of external stresses. The study highlights the use of single-walled carbon nanotubes as window electrodes for scalable flexible perovskite solar modules.
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