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Showing 1–6 of 6 results
Advanced filters: Author: Pengyi Lu Clear advanced filters

  • China’s restoration policies since 1980 turned its land sector from a carbon source to a sink of 175.9 (143.8–205.8) Tg C yr–¹ (2001–2020), with over 70% of this due to land management, highlighting its role in carbon neutrality.

    • Chao Yue
    • Mengyang Xu
    • Shilong Piao
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-15

  • Ytterbium oxide buffer layer for use in perovskite solar cells yields a certified power conversion efficiency of more than 25%, which enhances stability across a wide variety of perovskite compositions.

    • Peng Chen
    • Yun Xiao
    • Rui Zhu
    Research
    Nature
    Volume: 625, P: 516-522

  • The unconventional hexagonal phase CuCo PBA with open structure, large pore size, and high specific surface area is synthesized, and it delivers much better small molecular gas adsorption performance than the traditional cubic counterpart.

    • Jinwen Yin
    • Jing Wang
    • Zhanxi Fan
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-11

  • DNA methyltransferase1 (DNMT1) plays a key role in stem cell and progenitor cell maintenance in mammalian epithelium tissues. Here the authors uncover a role for DNMT1 in the regulation of stem/progenitor cells in normal and tumorigenic mouse mammary gland.

    • Rajneesh Pathania
    • Sabarish Ramachandran
    • Muthusamy Thangaraju
    Research
    Nature Communications
    Volume: 6, P: 1-11

  • The scarcity and high price of noble metal catalysts pose critical challenges for the chemical industry, and finding strategies that ensure complete atom efficiency has become a pivotal endeavour. This work introduces the fabrication of amorphous single-layer PtSex catalysts for the hydrogen evolution reaction with high atom-utilization efficiency.

    • Yongmin He
    • Liren Liu
    • Zheng Liu
    Research
    Nature Catalysis
    Volume: 5, P: 212-221

  • Recent developments in machine learning have seen the merging of ensemble and deep learning techniques. The authors review advances in ensemble deep learning methods and their applications in bioinformatics, and discuss the challenges and opportunities going forward.

    • Yue Cao
    • Thomas Andrew Geddes
    • Pengyi Yang
    Reviews
    Nature Machine Intelligence
    Volume: 2, P: 500-508