We present a theoretical model describing Ogston ͑pore size comparable to or larger than the characteristic molecular dimension͒ sieving of rigid isotropic and anisotropic biomolecules in nanofluidic molecular filter arrays comprising of alternating deep and shallow regions. Starting from a quasi-one-dimensional driftdiffusion description, which captures the interplay between the driving electric force, entropic barrier and molecular diffusion, we derive explicit analytical results for the effective mobility and trapping time. Our results elucidate the effects of field strength, device geometry and entropic barrier height, providing a robust tool for the design and optimization of nanofilter/nanopore systems. Specifically, we show that Ogston sieving becomes negligible when the length of shallow region becomes sufficiently small, mainly due to efficient diffusional transport through the short shallow region. Our theoretical results are in line with experimental observations and provide important design insight for nanofluidic systems.

This article proposes a simple computational transport model of rod-like short dsDNA molecules through a microfabricated nanofilter array. Using a nanochannel consisting of alternate deep wells and shallow slits, it is demonstrated that the complex partitioning of rod-like DNA molecules of different sizes over the nanofilter array can be well described by continuum transport theory with the orientational entropy and anisotropic transport parameters properly quantified. In this model, orientational entropy of the rod-like DNA is calculated from the equilibrium distribution of rigid cylindrical rod near the solid wall. The flux caused by entropic differences is derived from the interaction between the DNA rods and the solid channel wall during rotational diffusion. In addition to its role as an entropic barrier, the confinement of the DNA in the shallow channels also induces large changes in the effective electrophoretic mobility for longer molecules in the presence of EOF. In addition to the partitioning/selectivity of DNA molecules by the nanofilter, this model can also be used to estimate the dispersion of separated peaks. It allows for fast optimization of nanofilter separation devices, without the need of stochastic modeling techniques that are usually required.

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