Robust ultraclean atomically thin membranes for atomic-resolution electron microscopy

Liming Zheng, Yanan Chen, Ning Li, Jincan Zhang, Nan Liu, Junjie Liu, Wenhui Dang, Bing Deng, Yanbin Li, Xiaoyin Gao, Congwei Tan, Zi Yang, Shipu Xu, Mingzhan Wang, Hao Yang, Luzhao Sun, Yi Cui, Xiaoding Wei, Peng Gao (), Hong-Wei Wang () and Hailin Peng ()
Additional contact information
Liming Zheng: Peking University
Yanan Chen: Tsinghua University
Ning Li: Peking University
Jincan Zhang: Peking University
Nan Liu: Tsinghua University
Junjie Liu: Peking University
Wenhui Dang: Peking University
Bing Deng: Peking University
Yanbin Li: Stanford University
Xiaoyin Gao: Peking University
Congwei Tan: Peking University
Zi Yang: Tsinghua University
Shipu Xu: Peking University
Mingzhan Wang: Peking University
Hao Yang: Peking University
Luzhao Sun: Peking University
Yi Cui: Stanford University
Xiaoding Wei: Peking University
Peng Gao: Peking University
Hong-Wei Wang: Tsinghua University
Hailin Peng: Peking University

Nature Communications, 2020, vol. 11, issue 1, 1-8

Abstract: Abstract The fast development of high-resolution electron microscopy (EM) demands a background-noise-free substrate to support the specimens, where atomically thin graphene membranes can serve as an ideal candidate. Yet the preparation of robust and ultraclean graphene EM grids remains challenging. Here we present a polymer- and transfer-free direct-etching method for batch fabrication of robust ultraclean graphene grids through membrane tension modulation. Loading samples on such graphene grids enables the detection of single metal atoms and atomic-resolution imaging of the iron core of ferritin molecules at both room- and cryo-temperature. The same kind of hydrophilic graphene grid allows the formation of ultrathin vitrified ice layer embedded most protein particles at the graphene-water interface, which facilitates cryo-EM 3D reconstruction of archaea 20S proteasomes at a record high resolution of ~2.36 Å. Our results demonstrate the significant improvements in image quality using the graphene grids and expand the scope of EM imaging.

Date: 2020
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DOI: 10.1038/s41467-020-14359-0

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