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.
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.
Led by the Institute of Vertebrate Paleontology and Paleoanthropology of the Chinese Academy of Sciences, the team—which included researchers from China, Australia, Spain, and the United States—conducted multidisciplinary archaeological investigations at the Xigou site in the Danjiangkou Reservoir region of central China. Their work yielded evidence of sophisticated stone tool technologies dating from 160,000 to 72,000 years ago, revealing that hominins in the region were far more innovative and adaptable than previously thought.
While paleontologists have uncovered dozens of such Cambrian soft-bodied fossil sites—including China's early Cambrian Chengjiang biota in Yunnan and Canada's middle Cambrian Burgess Shale biota, the most famous examples of their kind—no equivalent top-tier soft-bodied fossil deposit had ever been found from the critical post-Sinsk Event time interval. That changed over the past five years, however, with the discovery of the Huayuan biota—a world-class soft-bodied fossil deposit dating to shortly after the Sinsk Event.
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.
Researchers from the Institute of Metal Research of the Chinese Academy of Sciences have stretched a chain of gold atoms by a record-breaking 46%, providing direct evidence of how fundamental metal bonds behave under extreme deformation. This study also reveals how structural changes at the atomic scale influence electrical transport.
86-10-68597521 (day)
86-10-68597289 (night)
52 Sanlihe Rd., Xicheng District,
Beijing, China (100864)
Copyright © 2002 - Chinese Academy of Sciences
