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.
A research team led by PAN Jianwei and LU Chaoyang from the University of Science and Technology of China has demonstrated a high-speed atom rearrangement technique that significantly advances neutral-atom quantum computation.
A new study by Ashutosh Tripathi from the Xinjiang Astronomical Observatory of the Chinese Academy of Sciences, together with his collaborators, has identified highly significant short-timescale quasi-periodic oscillations in several blazars.
A research team led by Prof. PAN Shilie at the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has developed the fluorooxoborate crystal NH4B4O6F (ABF)—offering aneffective solution to the practical challenges of VUV NLO materials.
A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has developed a novel Hg-based chalcogenide HGSC—featuring linear [Hg3Se2] building units. The team systematically investigated the crystal's structure, optical properties, and thermal response behavior.
A research team led by Prof. ZHU Yongguan, a member of the Chinese Academy of Sciences (CAS) at the CAS Research Center for Eco-Environmental Sciences, has identified the mechanisms by which sponge city construction significantly enhances urban plant diversity.
Researchers from the Wuhan Botanical Garden of the Chinese Academy of Sciences used "Hongyang" kiwifruit to simulate high-temperature stress (30°C, 35°C, 40°C, compared with a 25°C control). They systematically monitored physiological indicators, transcriptome characteristics, and dynamic changes in related metabolites to clarify how high-temperature stress affects anthocyanin biosynthesis and stability, providing a theoretical basis for developing fruit quality regulation strategies under high-temperature conditions.
A research team led by Prof. YAN Hong from the Institute of Earth Environment of the Chinese Academy of Sciences, in collaboration with Australian scholars, reconstructed Australian summer monsoon (AuSM) variability over the past 13.5 ka using a 5.13-m-long sediment core from Bromfield Swamp in the tropical monsoon region of northern Australia.
A research team from the Institute of Geochemistry of the Chinese Academy of Sciences, together with collaborators, used complementary molecular dynamics simulations, combining ab initio and deep-learning potential methods. Their findings reveal that under deep lower mantle and core–mantle boundary (CMB) conditions, water and the key hydrous mineral δ-AlOOH enter a superionic state—which combines features of a solid crystal lattice with liquid-like mobile ions—thereby fundamentally altering their stability and dehydration behavior.
A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences has developed a new method combining deep learning with physical radiative transfer modeling to improve the retrieval of atmospheric aerosol properties from complex satellite observations, supporting high-resolution, near-real-time monitoring of haze and dust events.
A recent satellite-based study has uncovered alarming declines in groundwater storage across High Mountain Asia, widely known as the "Asian Water Tower". This critical water source, which sustains agricultural irrigation, urban water supplies and ecological security for hundreds of millions of people in more than a dozen downstream countries, is depleting at a staggering rate of approximately 24.2 billion tonnes per year.
A research team led by Prof.YU Xuefeng from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences developed a knowledge-driven multi-agent and robot system (MARS) for end-to-end autonomous materials discovery.
A research team from the Institute of Metal Research has developed an efficient, stable, atomic-scale catalyst for carbon monoxide (CO) oxidation. This advance offers promising strategies for environmental catalysis and designing low-cost, high-performance catalysts.
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