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SUMMARY:Water transport in boron nitride nanotube membranes - Sritay Mistr
 y\, University of Edinburgh
DTSTART:20220509T130000Z
DTEND:20220509T133000Z
UID:TALK172883@talks.cam.ac.uk
CONTACT:Dr Stephen Cox
DESCRIPTION:Carbon nanotubes (CNTs) have been heralded as the material of 
 choice for next-generation membranes for more than a decade. Meanwhile\, s
 imulation studies on BNNTs showed they potentially offer faster water tran
 sport than CNTs\, contradicting the few recent experiments and simulations
  which claim the opposite. We use a combination of simulations and experim
 ental data to address the causes of these contra-indications in literature
  by analysing BNNTs through the framework of resistance to flow. Dividing 
 the resistance into the components of end resistance and nanotube flow res
 istance\, the role of factors\, such as pore end configuration\, membrane 
 length\, and BNNT atom partial charges\, affecting both the resistance ter
 ms can be studied independently. Molecular simulations of nanotube membran
 es in literature often use very short nanotubes connected to high and low-
 pressure reservoirs\, to reduce computational time. Resistance in these sh
 ort nanotubes is found to be dominated by the end resistance arising at th
 e pore\, hiding the flow resistance within the nanotube. For microscale-th
 ick laboratory-scale membranes\, the flow resistance inside the nanotubes 
 dominates\, with the end resistance nearly negligible compared to the nano
 tube flow resistance. CNTs are found to consistently have a lower nanotube
  flow resistance\, indicating they will provide faster water transport at 
 the laboratory scale. The choice of partial charge on the BN atoms is also
  shown to play a large role in determining the nanotube flow resistance\, 
 with higher charges presenting higher resistance. A more accurate approach
  to comparing simulation results with experiments for nanotube membranes i
 s highlighted.
LOCATION:https://zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT0
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