@article{80e9f7f732cc49d98fedab24d5e6c986,
title = "Achieving high permeability and enhanced selectivity for Angstrom-scale separations using artificial water channel membranes",
abstract = "Synthetic polymer membranes, critical to diverse energy-efficient separations, are subject to permeability-selectivity trade-offs that decrease their overall efficacy. These trade-offs are due to structural variations (e.g., broad pore size distributions) in both nonporous membranes used for Angstrom-scale separations and porous membranes used for nano to micron-scale separations. Biological membranes utilize well-defined Angstrom-scale pores to provide exceptional transport properties and can be used as inspiration to overcome this trade-off. Here, we present a comprehensive demonstration of such a bioinspired approach based on pillar[5]arene artificial water channels, resulting in artificial water channel-based block copolymer membranes. These membranes have a sharp selectivity profile with a molecular weight cutoff of ~ 500 Da, a size range challenging to achieve with current membranes, while achieving a large improvement in permeability (~65 L m-2 h-1 bar-1 compared with 4-7 L m-2 h-1 bar-1) over similarly rated commercial membranes.",
author = "Shen, {Yue Xiao} and Song, {Woochul C.} and {Ryan Barden}, D. and Tingwei Ren and Chao Lang and Hasin Feroz and Henderson, {Codey B.} and Saboe, {Patrick O.} and Daniel Tsai and Hengjing Yan and Butler, {Peter J.} and Bazan, {Guillermo C.} and Phillip, {William A.} and Hickey, {Robert J.} and Cremer, {Paul S.} and Harish Vashisth and Manish Kumar",
note = "Funding Information: We acknowledge financial support from the National Science Foundation CAREER grant (CBET-1552571) to MK for this work. Support was also provided through CBET-1705278 and DMR-1709522 for various aspects of this work. Computations for simulations were performed on Trillian, a Cray XE6m-200 supercomputer at the University of New Hampshire supported by the NSF MRI program under grant PHY-1229408 (PI: Joachim Raeder), and on NSF-supported (ACI-1053575) Extreme Science and Engineering Discovery Environment (XSEDE) under grant TG-MCB140029 (PI: Harish Vashisth). Research in the Bazan lab was supported by the Institute of Collaborative Biotechnologies through grant W911NF-09-0001 from the U.S. Army Research Office. We thank Professor Jun-li Hou and Dr. Wen Si from the Department of Chemistry at Fudan University for their help on channel synthesis. We thank Dr. Ian T. Sines for the synthesis of some of the PB-PEO BCPs used in this work. Figure 1e, f were kindly provided by Dr. Karl Decker and Professor Aleksei Aksimentiev from the Department of Physics at University of Illinois at Urbana–Champaign. The authors thank Jennifer Grey from the Materials Characterization Lab at Penn State for energy filtered TEM and STEM with EDS imaging and post analysis and Dr. Nichole M. Wonderling for XRD experiments. Funding Information: We acknowledge financial support from the National Science Foundation CAREER grant (CBET-1552571) to MK for this work. Support was also provided through CBET-1705278 and DMR-1709522 for various aspects of this work. Computations for simulations were performed on Trillian, a Cray XE6m-200 supercomputer at the University of New Hampshire supported by the NSF MRI program under grant PHY-1229408 (PI: Joachim Raeder), and on NSF-supported (ACI-1053575) Extreme Science and Engineering Discovery Environment (XSEDE) under grant TG-MCB140029. Publisher Copyright: {\textcopyright} 2018 The Author(s).",
year = "2018",
month = dec,
day = "1",
doi = "10.1038/s41467-018-04604-y",
language = "English",
volume = "9",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "NATURE COMMUNICATIONS",
number = "1",
}