All Outputs (3)

Large Room-Temperature Magnetoresistance in van der Waals Ferromagnet/Semiconductor Junctions (2022)
Journal Article
Zhu, W., Xie, S., Lin, H., Zhang, G., Wu, H., Hu, T., …Wang, K. (2022). Large Room-Temperature Magnetoresistance in van der Waals Ferromagnet/Semiconductor Junctions. Chinese Physics Letters, 39(12), Article 128501. https://doi.org/10.1088/0256-307x/39/12/128501

A magnetic tunnel junction (MTJ) is the core component in memory technologies, such as the magnetic random-access memory, magnetic sensors and programmable logic devices. In particular, MTJs based on two-dimensional van der Waals (vdW) heterostructur... Read More about Large Room-Temperature Magnetoresistance in van der Waals Ferromagnet/Semiconductor Junctions.

Author Correction: Single-atom Cu anchored catalysts for photocatalytic renewable H2 production with a quantum efficiency of 56% (2022)
Journal Article
Zhang, Y., Zhao, J., Wang, H., Xiao, B., Zhang, W., Zhao, X., Lv, T., Thangamuthu, M., Zhang, J., Guo, Y., Ma, J., Lin, L., Tang, J., Huang, R., & Liu, Q. (2022). Author Correction: Single-atom Cu anchored catalysts for photocatalytic renewable H2 production with a quantum efficiency of 56%. Nature Communications, 13, Article 2062. https://doi.org/10.1038/s41467-022-29799-z

Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27698-3, published online 10 January 2022.

In Supplementary Fig. 28b in the Supplementary PDF for this article, the figure panel incorrectly read ‘345 mW/cm2’ but should have... Read More about Author Correction: Single-atom Cu anchored catalysts for photocatalytic renewable H2 production with a quantum efficiency of 56%.

Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming (2022)
Journal Article
Peng, Z., Maciel-Guerra, A., Baker, M., Zhang, X., Hu, Y., Wang, W., …Dottorini, T. (2022). Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming. PLoS Computational Biology, 18(3), Article e1010018. https://doi.org/10.1371/journal.pcbi.1010018

Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs... Read More about Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming.