Fast reverse osmosis using boron nitride and carbon nanotubes
Applied Physics Letters 92, 133120 (2008)
M. E. Suk, A. V. Raghunathan, and N. R. Aluru
Department of Mechanical Science and Engineering, Beckman Institute for Advanced Science and
Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
Reverse osmosis through carbon nanotube (CNT), boron nitride nanotube (BNNT), and polymethyl methacrylate (PMMA) were simulated using nonequilibrium molecular dynamics.
The simulation setup consists of a pure water chamber and a potassium chloride solution chamber. The nanotubes were (6,6) armchair type, having diameters of around 8-11 ? and lengths of around 18-22 ?. Water model used was SPC/E and ions were modeled as charged LJ atoms. Pressure pistons initially placed at two ends of the setup were made of silicon atoms and were made rigid. Simulation was run until 180 water molecules have passed through.
Because of the osmotic pressure gradient, water molecules move from the solution chamber to the pure water chamber. Ions couldn’t go through the membrane because of steric hindrance and large energy barrier at the opening. Permeation coefficient (# of molecules per ns) was calculated from the relation between flux, chemical potential and temperature. Chemical potential gradient can be obtained from the pressure gradient and concentration gradient of the solute.
The permeation coefficients found for BNNT, CNT, and PMMA were 14.7, 13.4, and 5.6 #/ns, respectively. Obviously, this implies higher water flux through the nanotubes compared with the polymeric membrane. The permeation coefficients were brought about by the “hopping” events observed. By analyzing the potential of mean force, it was found that the reason for the decreased flux through PMMA is the irregular nature of the PMMA pore surface, which increases the local energy barriers inside the pore. On the other hand, for both nanotubes, there are lower energy barriers at the pore mouths.
Contribution and application:
This paper describes the relation between flux and chemical potential gradient on a molecular level as it used molecular concepts such as Boltzmann constant and Avogadro’s number. This is helpful for understanding the relationship between micro- and macro-level quantities.
By: Hannah Ebro