Tacticity is one of the most important features of stereoregular polymers, with significant impact on morphology and on a variety of properties such as conformational, thermal, rheological, mechanical, etc. In this work we focus on tacticity effects on the conformations and more specifically on the unperturbed dimensions of single polypropylene (PP) homopolymer and both block and random poly(ethylene−propylene) copolymer chains. The equilibration of all chains is achieved by applying the single-chain Monte Carlo algorithm of Tzounis et al. [Macromolecules 2017, 50, 4575−4587]. In agreement with past studies, we find that tacticity has a significant effect on the stiffness of PP homopolymer. The characteristic ratio exhibits a nonmonotonic dependence on the fraction of meso dyads along the PP chains, which results from two competing mechanisms, revealed by analysis of the torsional states of the PP chain backbones. A simple theoretical model is developed to describe the dependence of the stiffness of poly(ethylene-block-propylene) copolymer on its propylene content and on the tacticity of its PP block. Finally, the effect of both tacticity and propylene content on the stiffness of poly(ethylene-randompropylene) chains, used to model ethylene−propylene monomer (EPM) materials, is found to be in very good qualitative agreement with available rotational isomeric state (RIS) model predictions.

The spatial dimensions and the stiffness (characteristic ratio, C ∞) of polymer chains are intimately related to key macroscopic properties such as the plateau modulus and the melt viscosity. Furthermore, these molecular features are very important in the selection and design of copolymer species used in directed self-assembly lithographic processes. We have developed a general methodology for predicting the chain dimensions of any polymer chain in the unperturbed state starting from its detailed atomistic structure. The methodology is based on performing Metropolis Monte Carlo (MC) simulation, leading to equilibration of the conformational distribution of a single unperturbed polymer chain, subject only to local interactions along its backbone. To define what constitutes local interactions, the maximal topological distance of repeat units between which nonbonded forces are active is varied systematically, until a maximum in stiffness is achieved. Our methodology was validated by comparing the predicted characteristic ratios for a series of polymers against the corresponding values estimated from MC simulations of the same polymers in the melt state based on the same force field. Furthermore, we have predicted the characteristic ratios for three polymers used in directed self-assembly lithographic processes and shown that they are in good agreement with reported experimental values.

A complete thermodynamic analysis of mixtures consisting of molecules with complex chemical constitution can be rather demanding. The Kirkwood–Buff theory of solutions allows the estimation of thermodynamic properties, which cannot be directly extracted from atomistic simulations, such as the Gibbs energy of mixing (Δmix G). In this work, we perform molecular dynamics simulations of n-hexane–ethanol binary mixtures in the liquid state under two temperature–pressure conditions and at various mole fractions. On the basis of the recently published methodology of Galata Galata Fluid Phase Equilib.20184702537, we first calculate the Kirkwood–Buff integrals in the isothermal–isobaric (NpT) ensemble, identifying how system size affects their estimation. We then extract the activity coefficients, excess Gibbs energy, excess enthalpy, and excess entropy for the n-hexane–ethanol binary mixtures we simulate. We employ two approaches for quantifying composition fluctuations: one based on counting molecular centers of mass and a second one based on counting molecular segments. Results from the two approaches are practically indistinguishable. We compare our results against predictions of vapor–liquid equilibria obtained in a previous simulation work using the same force field, as well as with experimental data, and find very good agreement. In addition, we develop a simple methodology to identify the hydrogen bonds between ethanol molecules and analyze their effects on mixing properties.

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