Spectral collocation methods for polymer brushes

We provide an in-depth study of pseudo-spectral numerical methods associated with modeling the self-assembly of molten mixed polymer brushes in the framework of self-consistent field theory (SCFT). SCFT of molten polymer brushes has proved numerically challenging in the past because of sharp features that arise in the self-consistent pressure field at the grafting surface due to the chain end tethering constraint. We show that this pressure anomaly can be reduced by smearing the grafting points over a narrow zone normal to the surface in an incompressible model, and/or by switching to a compressible model for the molten brush. In both cases, we use results obtained from a source (delta function) distribution of grafting points as a reference. At the grafting surface, we consider both Neumann and Dirichlet conditions, where the latter is paired with a masking method to mimic a confining surface. When only the density profiles and relative free energies of two comparison phases are of interest, either source or smeared distributions of grafting points can be used, but a smeared distribution of grafting points exhibits faster convergence with respect to the number of chain contour steps. Absolute free energies converge only within the smeared model. In addition, when a sine basis is used with the masking method and a smeared distribution, fewer iterations are necessary to converge the SCFT fields for the compressible model. The numerical methods described here and investigated in one-dimension will provide an enabling platform for computationally more demanding three-dimensional SCFT studies of a broad range of mixed polymer brush systems.     

Determination of binding energy and solubility parameters for functionalized gold nanoparticles by molecular dynamics simulation

The binding energy, density, and solubility of functionalized gold nanoparticles in a vacuum are computed using molecular dynamics simulations. Numerous parameters including surface coverage fraction, functional group (-CH(3), -OH, -NH(2)), and nanoparticle orientation are considered. The analysis includes computation of minimum interparticle binding distances and energies and an analysis of mechanisms that may contribute to changes in system potential energy. A number of interesting trends and results are observed, such as increasing binding distance with higher terminal group electronegativity and a minimum particle-particle binding energy (solubility parameter) based upon surface coverage. These results provide a fundamental understanding of ligand-coated nanoparticle interactions required for the design and processing of high-density polymer composites. The computational model and results are presented as support for these conclusions.     

Raman spectral analysis of renal tissue: a novel application

Renal cell carcinoma (RCC) accounts for 85% of all primary renal cancers. The definitive diagnosis of RCC relies exclusively on the subjective pathological interpretation of the surgical specimen. In this study, we aimed to analyze renal tissue using objective Raman spectroscopy (RS). We obtained 15 pairs of RCC (T) and corresponding normal renal parenchymal tissues (N) from our biobank. There are three subtypes of RCC: clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (cRCC). Five pairs of tissue of each subtype were enrolled. Fresh‐frozen sliced tissues were used for the RS detection. The Raman spectra between T and N were compared and analyzed using partial least squares (PLS) regression. Data for a total of 55 T and 58 N analyzable RS samples were obtained. The spectra were normalized by dividing the intensity of the characteristic peak at 1003 cm⁻¹ using phenylalanine's Raman peak. After further analysis with PLS, the sensitivity and specificity for discriminating T from N were 95% and 93%, respectively. The RCC subtypes can be discriminated at an accuracy of 72% for ccRCC, 88% for cRCC, and 86% for pRCC. This study demonstrates the feasibility of analyzing renal tissue using RS. RS, with its advantages of easy and objective tissue assessment, may be applied to aid intraoperative decision making and pathological tissue assessment. Copyright © 2014 John Wiley & Sons, Ltd.