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Abstract A direct way to spot structural features that are universally shared among proteins is to find analogues from simpler condensed matter systems. In the current study, the feasibility of creating ensembles of artificial structures that can automatically reproduce a large number of geometrical and topological descriptors of globular proteins is investigated. Towards this aim, a simple cubic (SC) arrangement is shown to provide the best background lattice after a careful analysis of the residue packing trends from 210 globular proteins. It is shown that a minimalistic set of rules imposed on this lattice is sufficient to generate structures that can mimic real proteins. In the proposed method, 210 such structures are generated by randomly removing residues (beads) from clusters that have a SC lattice arrangement such that all the generated structures have single connected components. Two additional sets are prepared from the initial structures via random relaxation and a reverse Monte Carlo simulated annealing algorithm, which targets the average radial distribution function (RDF) of 210 globular proteins. The initial and relaxed structures are compared to real proteins via RDF, bond orientational order parameters and several descriptors of network topology. Based on these features, results indicate that the structures generated with 40% occupancy closely resemble real residue networks. The structure generation mechanism automatically produces networks that are in the same topological class as globular proteins and reproduce small-world characteristics of high clustering and small shortest path lengths. Most notably, the established correspondence rules out icosahedral order as a relevant structural feature for residue networks in contrast to other amorphous systems where it is an inherent characteristic. The close correspondence is also observed in the vibrational characteristics as computed from the Anisotropic Network Model, therefore hinting at a non-superficial link between the proteins and the defect laden cubic crystalline order. 

This work describes how a solid-state blending method such as jet milling can be used to successfully prepare polysulfone (PSU)/ γ -alumina nanocomposites. For comparison purposes, conventional melt extrusion was used as well. Morphological analysis revealed how jet mill blending allows obtaining well-dispersed γ -alumina nanoparticles within a polysulfone matrix without any surface treatment, with an important decrease of particle size promoted by the breakup of agglomerates and aggregates due to the particle-particle impacts during processing, which was not observed in the extruded nanocomposites. DSC analysis demonstrated that jet-milling processing promoted T g enhancements with alumina addition, while TGA experiments confirmed the increment of thermal stability of the nanocomposites prepared by jet milling when compared with the composites prepared by extrusion. The tensile tests showed that ductility remains at a high value for milled nanocomposites, which agreed with the fracture surface images revealing large plastic deformation as a function of the alumina content. This comparative study indicates that the dispersion of nanoparticles in PSU was more homogeneous, with smaller nanoparticles when preparing nanocomposites using jet milling, showing a strong correlation with the enhanced final properties of the nanocomposites.