Biomolecule Separation, Concentration, and Detection using Nanofluidic Channels - Nanofluidics: Nanoscience and Nanotechnology - page 37

For example, Fu and co-workers demonstrated a continuous-flow nanofilter array
system, where proteins and DNA molecules may be separated using many different sieving
mechanisms including Ogston sieving, entropic trapping, and electrostatic sieving. 26
(Figure 2.2) Electrostatic sieving occurs when the Debye layer essentially spans the entire
depth of a nanochannel, by decreasing the ionic strength. Then molecular transport through
the nanochannel will be perm-selective, meaning that a protein's mobility through the
nanochannel will depend on the charge density (or pI value of the protein). A similar idea
can also be used to decrease the effective size of the nanofilter (therefore leading to higher
selectivity), since counter-ions (negatively charged proteins) will be prohibited from
entering the non-electroneutral Debye layer.
2.3.2 Computational Modelling of Nanofilter Sieving Phenomena
When using regular nanofilters, one can study the detailed physical phenomena of
molecular sieving in a controlled experiment. The results of molecular sieving studies
involving nanofilter-generated data often surprise researchers, signifying that the physical
problem at hand is not as simple as the intuitive filtration model. This is especially true for
long polymeric biomolecules, where conformational degrees of freedom complicate the
molecular interaction with the nanofilter. 19,27 Due to this complexity, there have been many
attempts to simulate or model polymer interactions with nanofilter sieving structures.
Techniques used range from simple analytical models such as Transition State Theory, 19, 24
Monte Carlo simulations 28 and Brownian Dynamics simulations. 29,30 While these models
reproduce and simulate molecular sieving events in nanofilters, we have yet to see the
development of numerical models that can be used for predicting and optimizing nanofilter
sieving systems.
The main difficulty in computational modelling is that accurate description of the
problem requires the modelling of both stochastic dynamics of biomolecules and molecular
hydrodynamics. While most simulations (Brownian Dynamics and Molecular Dynamics)
focus on stochastic motion of biomolecules near the nanofilter, it is well known that
charged molecules trapped in the nanofilter will generate local electroosmotic flow, due to
the presence of counterions. 25 Such local molecular hydrodynamics is also important in
determining the diffusivity of the molecules (Zimm diffusivity), as well as band dispersion
of the system.
Two recent approaches are noteworthy in this respect. Li et al. recently developed
a continuum transport model for Ogston sieving, where the detailed Brownian dynamics of
rigid biomolecules near a nanofilter were averaged into an effective entropic potential
term, in order to simplify the model by eliminating the need for stochastic simulation. 31 In
this situation, one can simply solve a standard continuum transport equation, with full
consideration of any hydrodynamic flow in the system. As a result, both separation
selectivity and peak dispersion can be modelled for system optimization. Moreover,
Duong-Hong et al. applied Dissipative Particle Dynamics to model both the stochastic
motion of DNA and its hydrodynamics in entropic trapping system. 32,33 Such coarse-
grained stochastic simulation tools include all the relevant physics of the problem, whilst
allowing one to analyze even mesoscale nanofilter devices, which are too expensive to
model in standard molecular dynamics techniques.