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Author Ghorbanfekr, H.; Behler, J.; Peeters, F.M. pdf  doi
openurl 
  Title Insights into water permeation through hBN nanocapillaries by ab initio machine learning molecular dynamics simulations Type A1 Journal article
  Year (down) 2020 Publication Journal Of Physical Chemistry Letters Abbreviated Journal J Phys Chem Lett  
  Volume 11 Issue 17 Pages 7363-7370  
  Keywords A1 Journal article; Engineering sciences. Technology; Condensed Matter Theory (CMT); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)  
  Abstract Water permeation between stacked layers of hBN sheets forming 2D nanochannels is investigated using large-scale ab initio-quality molecular dynamics simulations. A high-dimensional neural network potential trained on density-functional theory calculations is employed. We simulate water in van der Waals nanocapillaries and study the impact of nanometric confinement on the structure and dynamics of water using both equilibrium and nonequilibrium methods. At an interlayer distance of 10.2 A confinement induces a first-order phase transition resulting in a well-defined AA-stacked bilayer of hexagonal ice. In contrast, for h < 9 A, the 2D water monolayer consists of a mixture of different locally ordered patterns of squares, pentagons, and hexagons. We found a significant change in the transport properties of confined water, particularly for monolayer water where the water-solid friction coefficient decreases to half and the diffusion coefficient increases by a factor of 4 as compared to bulk water. Accordingly, the slip-velocity is found to increase under confinement and we found that the overall permeation is dominated by monolayer water adjacent to the hBN membranes at extreme confinements. We conclude that monolayer water in addition to bilayer ice has a major contribution to water transport through 2D nanochannels.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 000569375400061 Publication Date 2020-08-10  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1948-7185 ISBN Additional Links UA library record; WoS full record; WoS citing articles  
  Impact Factor 5.7 Times cited 24 Open Access  
  Notes ; This work was supported by the Flemish Science Foundation (FWO-Vl) and the Methusalem program (Grant Number: G099219N). The authors thank Arham Amouei for the helpful discussion regarding MD simulations. ; Approved Most recent IF: 5.7; 2020 IF: 9.353  
  Call Number UA @ admin @ c:irua:171996 Serial 6546  
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