Scaling aspects of block co-polymer adsorption on curved surfaces from nonselective solvents

Efficient encapsulation of proteins with random copolymers

Membraneless organelles are aggregates of disordered proteins that form spontaneously to promote specific cellular functions in vivo. The possibility of synthesizing membraneless organelles out of cells will therefore enable fabrication of protein-based materials with functions inherent to biological matter. Since random copolymers contain various compositions and sequences of solvophobic and solvophilic groups, they are expected to function in nonbiological media similarly to a set of disordered proteins in membraneless organelles. Interestingly, the internal environment of these organelles has been noted to behave more like an organic solvent than like water. Therefore, an adsorbed layer of random copolymers that mimics the function of disordered proteins could, in principle, protect and enhance the proteins' enzymatic activity even in organic solvents, which are ideal when the products and/or the reactants have limited solubility in aqueous media. Here, we demonstrate via multiscale simulations that random copolymers efficiently incorporate proteins into different solvents with the potential to optimize their enzymatic activity. We investigate the key factors that govern the ability of random copolymers to encapsulate proteins, including the adsorption energy, copolymer average composition, and solvent selectivity. The adsorbed polymer chains have remarkably similar sequences, indicating that the proteins are able to select certain sequences that best reduce their exposure to the solvent. We also find that the protein surface coverage decreases when the fluctuation in the average distance between the protein adsorption sites increases. The results herein set the stage for computational design of random copolymers for stabilizing and delivering proteins across multiple media.

Morphological transformations in polymer brushes in binary mixtures: DPD study

Morphological transformations in polymer brushes in a binary mixture of good and bad solvents are studied using dissipative particle dynamics simulations drawing on a characteristic example of polyisoprene natural rubber in an acetone-benzene mixture. A coarse-grained DPD model of this system is built based on the experimental data in the literature. We focus on the transformation of dense, collapsed brush in bad solvent (acetone) to expanded brush solvated in good solvent (benzene) as the concentration of benzene increases. Compared to a sharp globule-to-coil transition observed in individual tethered chains, the collapsed-to-expanded transformation in brushes is found to be gradual without a prominent transition point. The transformation becomes more leveled as the brush density increases. At low densities, the collapsed brush is highly inhomogeneous and patterned into bunches composed of neighboring chains due to favorable polymer-polymer interaction. At high densities, the brush is expanded even in bad solvent due to steric restrictions. In addition, we considered a model system similar to the PINR-acetone-benzene system, but with the interactions between the solvent components worsened to the limit of miscibility. Enhanced contrast between good and bad solvents facilitates absorption of the good solvent by the brush, shifting the collapsed-to-expanded transformation to lower concentrations of good solvent. This effect is especially pronounced for higher brush densities.

Reactive adsorption of PS-PMMA block copolymers on concave alumina surfaces

The influence of pore size, relative block size, and solvent quality on the extent of diblock copolymer adsorption on alumina surfaces was determined. To this end, the block copolymer that was chosen was poly(styrene)-b-poly(methyl methacrylate) (PS-b-PMMA), in which the PMMA block strongly chemisorbs to the surface and the PS block weakly physisorbs. Several architectures (i.e., different ratios of M(n(PMMA)) and M(n)((PS))) of the PS-b-PMMA copolymers were adsorbed from various solvents onto porous alumina membranes with various pore sizes. It was determined that the diblock copolymer coverage decreased significantly as the pore size decreased, similar to the behavior of the PMMA homopolymer under the same conditions. However, the coverage decreased as the molecular weight of the anchoring block (PMMA) increased for all pore sizes, which is in contrast to the behavior of the PMMA homopolymer under the same conditions. The dependence of the coverage on the relative block size and solvent quality is analyzed on the basis of the anchor-buoy model and the deviation from it in a nonideal system. The results presented in this work are relevant to the study of block copolymer conformation in solutions and on surfaces, adsorption chromatography, and solvent sensors and controls.

Measuring the grafting density of nanoparticles in solution by analytical ultracentrifugation and total organic carbon analysis

Many of the solution phase properties of nanoparticles, such as their colloidal stability and hydrodynamic diameter, are governed by the number of stabilizing groups bound to the particle surface (i.e., grafting density). Here, we show how two techniques, analytical ultracentrifugation (AUC) and total organic carbon analysis (TOC), can be applied separately to the measurement of this parameter. AUC directly measures the density of nanoparticle-polymer conjugates while TOC provides the total carbon content of its aqueous dispersions. When these techniques are applied to model gold nanoparticles capped with thiolated poly(ethylene glycol), the measured grafting densities across a range of polymer chain lengths, polymer concentrations, and nanoparticle diameters agree to within 20%. Moreover, the measured grafting densities correlate well with the polymer content determined by thermogravimetric analysis of solid conjugate samples. Using these tools, we examine the particle core diameter, polymer chain length, and polymer solution concentration dependence of nanoparticle grafting densities in a gold nanoparticle-poly(ethylene glycol) conjugate system.

Adsorption of poly(methyl methacrylate) on concave Al2O3 surfaces in nanoporous membranes

The objective of this study was to determine the influence of polymer molecular weight and surface curvature on the adsorption of polymers onto concave surfaces. Poly(methyl methacrylate) (PMMA) of various molecular weights was adsorbed onto porous aluminum oxide membranes having various pore sizes, ranging from 32 to 220 nm. The surface coverage, expressed as repeat units per unit surface area, was observed to vary linearly with molecular weight for molecular weights below approximately 120,000 g/mol. The coverage was independent of molecular weight above this critical molar mass, as was previously reported for the adsorption of PMMA on convex surfaces. Furthermore, the coverage varied linearly with pore size. A theoretical model was developed to describe curvature-dependent adsorption by considering the density gradient that exists between the surface and the edge of the adsorption layer. According to this model, the density gradient of the adsorbed polymer segments scales inversely with particle size, while the total coverage scales linearly with particle size, in good agreement with experiment. These results show that the details of the adsorption of polymers onto concave surfaces with cylindrical geometries can be used to calculate molecular weight (below a critical molecular weight) if pore size is known. Conversely, pore size can also be determined with similar adsorption experiments. Most significantly, for polymers above a critical molecular weight, the precise molecular weight need not be known in order to determine pore size. Moreover, the adsorption developed and validated in this work can be used to predict coverage also onto surfaces with different geometries.