Emerging applications require single-wall carbon nanotubes (SWCNTs) of well-defined length. Yet the use of length-defined SWCNTs is limited, in part due to the lack of an easily accessible materials preparation method. Here, we present a new strategy for SWCNT length fractionation based on molecular crowding induced cluster formation. We show that the addition of polyethylene glycol (PEG) as a crowding agent into DNA-wrapped SWCNT dispersion leads to the formation of reversible, nematic, and rodlike microclusters, which can be collected by gentle centrifugation. Since shorter SWCNTs form clusters at higher polyethylene glycol concentration, gradual increase in PEG concentration results in length fractionated SWCNTs. Using atomic force microscopy (AFM) we show that fractions with average lengths of 60-500 nm and standard deviations of 30-40% can be obtained. The concept of molecular-crowding-based fractionation should be applicable to other nanoparticle dispersions.

Abstract

Computationally efficient modeling of gas turbine combustion is challenging due to the chaotic multi-scale physics and the complex non-linear interactions between acoustic, hydrodynamic, and chemical processes. A large-eddy simulation, referred to as the full order model (FOM), is performed for a gas turbine model combustor with turbulent combustion effects modeled using a flamelet-based method. Modal analysis reveals a high degree of correlation with averaged and instantaneous high-frequency particle image velocimetry fields. The dynamics of the precessing vortex core is quantitatively characterized using dynamic mode decomposition. The governing equations of the FOM are projected onto a low-dimensional linear manifold to construct a reduced-order model (ROM). A discretely-consistent least squares projection is used to guarantee global stability. The ROM provides an accurate reconstruction of the combustion dynamics within the training region, but faces a significant challenge in future state predictions. This limitation is mainly due to the increased projection error, which in turn is a direct consequence of the highly chaotic nature of the flow field, involving a wide range of dispersed coherent structures. This shortcoming is overcome using an adaptive basis method which yields accurate predictions of dynamics beyond the training region consistent with the FOM. Formal projection-based ROMs have not been applied to a problem of this scale and complexity, and achieving accurate and efficient ROMs is a grand challenge problem. A production-ready ROM method will significantly decrease the computational cost of the flame dynamics as well as the portability of this prediction to smaller-scale computers.

No abstract

The turbulent, reacting flow field of a Scramjet combustor is investigated using flameletbased Reynolds Averaged Navier-Stokes computations. The simulations target the model combustor configuration of Gamba et al. (2011, 2012), which includes a single injector, an inlet-induced shock train and shock/boundary layer/combustion interactions. Multiple fuel injection rates are considered and the impact of the equivalence ratio on the flow structure, heat release and flame properties is examined. The effect of the shock system on the reacting layers and heat release is examined. The computed results are in excellent qualitative agreement with Schlieren, Planar Laser-induced fluorescence imagery and chemiluminescence results. Comparisons with pressure measurements again show a good degree of correlation apart from a small constant offset.