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Beyond Tradition: A MOF-On-MOF Cascade Z-Scheme Heterostructure for Augmented CO Photoreduction.
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Beijing Key Laboratory for Green Catalysis and Separation and Department of Chemical Engineering, College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, P. R. China.
Metal-organic frameworks (MOFs) are rigorously investigated as promising candidates for CO capture and conversion. MOF-on-MOF heterostructures integrate bolstered charger carrier separation with the intrinsic advantages of MOF components, exhibiting immense potential to substantially escalate the efficiency of photocatalytic CO reduction (CORR). However, the structural and compositional complexity poses significant challenges to the controllable development of these heterostructures.
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Intercellular mitochondria transfer is an evolutionarily conserved process in which one cell delivers some of their mitochondria to another cell in the absence of cell division. This process has diverse functions depending on the cell types involved and physiological or disease context. Although mitochondria transfer was first shown to provide metabolic support to acceptor cells, recent studies have revealed diverse functions of mitochondria transfer, including, but not limited to, the maintenance of mitochondria quality of the donor cell and the regulation of tissue homeostasis and remodelling.
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In recent years, substantial strides have been made in the field of visual image reconstruction, particularly in its capacity to generate high-quality visual representations from human brain activity while considering semantic information. This advancement not only enables the recreation of visual content but also provides valuable insights into the intricate processes occurring within high-order functional brain regions, contributing to a deeper understanding of brain function. However, considering fusion semantics in reconstructing visual images from brain activity involves semantic-to-image guide reconstruction and may ignore underlying neural computational mechanisms, which does not represent true reconstruction from brain activity.
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