Cascaded compression of size distribution of nanopores in monolayer graphene

Jiangtao Wang (), Chi Cheng (), Xudong Zheng, Juan Carlos Idrobo, Ang-Yu Lu, Ji-Hoon Park, Bong Gyu Shin, Soon Jung Jung, Tianyi Zhang, Haozhe Wang, Guanhui Gao, Bongki Shin, Xiang Jin, Long Ju, Yimo Han, Lain-Jong Li, Rohit Karnik and Jing Kong ()
Additional contact information
Jiangtao Wang: Massachusetts Institute of Technology
Chi Cheng: University of Melbourne
Xudong Zheng: Massachusetts Institute of Technology
Juan Carlos Idrobo: University of Washington
Ang-Yu Lu: Massachusetts Institute of Technology
Ji-Hoon Park: Massachusetts Institute of Technology
Bong Gyu Shin: Max Planck Institute for Solid State Research
Soon Jung Jung: Max Planck Institute for Solid State Research
Tianyi Zhang: Massachusetts Institute of Technology
Haozhe Wang: Duke University
Guanhui Gao: Rice University
Bongki Shin: Rice University
Xiang Jin: Tsinghua University
Long Ju: Massachusetts Institute of Technology
Yimo Han: Rice University
Lain-Jong Li: University of Hong Kong
Rohit Karnik: Massachusetts Institute of Technology
Jing Kong: Massachusetts Institute of Technology

Nature, 2023, vol. 623, issue 7989, 956-963

Abstract: Abstract Monolayer graphene with nanometre-scale pores, atomically thin thickness and remarkable mechanical properties provides wide-ranging opportunities for applications in ion and molecular separations1, energy storage2 and electronics3. Because the performance of these applications relies heavily on the size of the nanopores, it is desirable to design and engineer with precision a suitable nanopore size with narrow size distributions. However, conventional top-down processes often yield log-normal distributions with long tails, particularly at the sub-nanometre scale4. Moreover, the size distribution and density of the nanopores are often intrinsically intercorrelated, leading to a trade-off between the two that substantially limits their applications5–9. Here we report a cascaded compression approach to narrowing the size distribution of nanopores with left skewness and ultrasmall tail deviation, while keeping the density of nanopores increasing at each compression cycle. The formation of nanopores is split into many small steps, in each of which the size distribution of all the existing nanopores is compressed by a combination of shrinkage and expansion and, at the same time as expansion, a new batch of nanopores is created, leading to increased nanopore density by each cycle. As a result, high-density nanopores in monolayer graphene with a left-skewed, short-tail size distribution are obtained that show ultrafast and ångström-size-tunable selective transport of ions and molecules, breaking the limitation of the conventional log-normal size distribution9,10. This method allows for independent control of several metrics of the generated nanopores, including the density, mean diameter, standard deviation and skewness of the size distribution, which will lead to the next leap in nanotechnology.

Date: 2023
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DOI: 10.1038/s41586-023-06689-y

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