Brownian dynamics simulations of single-wall carbon nanotube separation by type using dielectrophoresis

We theoretically investigate the separation of individualized metallic and semiconducting single-wall carbon nanotubes (SWNT) in a dielectrophoretic (DEP) flow device.; The SWNTs motion is simulated by a Brownian Dynamics (BD) algorithm which includes the translational and rotational effects of hydrodynamic, Brownian, dielectrophoretic, and electrophoretic forces. The device geometry is chosen to be a coaxial cylinder, because it yields effective flow throughput, the DEP and flow fields are orthogonal to each other, and all the fields can be described analytically everywhere. We construct a flow-DEP phase map, showing different regimes depending on the relative magnitudes of the forces in play.; The BD code is combined with an optimization algorithm that searches for the conditions which maximize the separation performance. The optimization results show that a 99% sorting performance can be achieved with typical SWNT parameters by operating in a region of the phase map where the metallic SWNTs completely orient with the field, whereas the semiconducting SWNTs partially flow align.