We prepare a series of mixed brushes of two incompatible polymers, polystyrene (PS) and poly(2-vinylpyridine) (P2VP) grafted by end groups to Si wafers from carboxyl-terminated P2VP (M W-(P2VP) 42 kg/mol) and carboxyl-terminated PS. The molecular mass of PS ranged from 2.98 to 75 kg/ mol. The mixed brushes are bidisperse (asymmetric) with respect to the difference of molecular mass of P2VP and PS while the polydispersity of PS and P2VP is narrow. We expose the mixed brushes to selective solvents (toluene for PS and ethanol for P2VP). The morphology and surface chemical composition are investigated using scanning probe microscopy and contact angle measurements. For small chain length asymmetry, the brushes exhibit lateral and perpendicular segregation, and the structure depends on the solvent quality. Upon increasing the molecular weight asymmetry, we encounter the transition from a morphology of laterally segregated domains to a layered (sandwich-like) structure. The location of this transition can be tuned by changing the solvent selectivity. We find qualitative agreement between experiments and self-consistent-field calculations.
The paper presents an algorithm for calculating the three-dimensional Voronoi-Delaunay tessellation for an ensemble of spheres of different radii (additively-weighted Voronoi diagram). Data structure and output of the algorithm is oriented toward the exploration of the voids between the spheres. The main geometric construct that we develop is the Voronoi S-network (the network of vertices and edges of the Voronoi regions determined in relation to the surfaces of the spheres). General scheme of the algorithm and the key points of its realization are discussed. The principle of the algorithm is that for each determined site of the network we find its neighbor sites. Thus, starting from a known site of the network, we sequentially find the whole network. The starting site of the network is easily determined based on certain considerations. Geometric properties of ensembles of spheres of different radii are discussed, the conditions of applicability and limitations of the algorithm are indicated. The algorithm is capable of working with a wide variety of physical models, which may be represented as sets of spheres, including computer models of complex molecular systems. Emphasis was placed on the issue of increasing the efficiency of algorithm to work with large models (tens of thousands of atoms). It was demonstrated that the experimental CPU time increases linearly with the number of atoms in the system, O(n).
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