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 Physics of the Chinese Academy of Sciences, along with the collaborators, have conducted a random multipolar driving experiment on a two-dimensional large superconducting quantum processor: Chuang-tzu 2.0, and observed a long-lived prethermal regime where the system temporarily avoids full thermalization.
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 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.
Researchers from the Xishuangbanna Tropical Botanical Garden (XTBG) of the Chinese Academy of Sciences identified a key gene, JcSPL9, which can significantly increase both seed yield and oil content in Jatropha.
A research team led by Eric H. Xu from the Shanghai Institute of Materia Medica of the Chinese Academy of Sciences, along with MA Xiong from Renji Hospital, determined how Ostα/β transports bile acids and why it differs fundamentally from previously characterized carriers through cryo-EM structure determination, molecular dynamics simulations, and electrophysiological analyses.
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 Institute of Earth Environment of the Chinese Academy of Sciences used online observation techniques to characterize the δ18Ov, δ2Hv and d-excessᵥ isotopic compositions of water vapor produced by the combustion of coal, natural gas and liquefied gas, as well as water vapor emitted from vehicle exhaust.
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 collaborative research team from the Institute of Metal Research (IMR) of the Chinese Academy of Sciences and Nanyang Technological University in Singapore, has revealed the dual and dynamic role that sulfate-reducing bacteria (SRB) play in both accelerating and later partially mitigating the corrosion and cracking of high-strength steel pipelines to transport oil, gas, and hydrogen.
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