Prediction of Infinite Dilution Benzene Solubility in Linear Polyethylene Melts via the Direct Particle Deletion Method

Chemical Potential of a Flexible Polymer Liquid in a Coarse-Grained Representation

While the excess chemical potential is the key quantity in determining phase diagrams, its direct computation for high-density liquids of long polymer chains has posed a significant challenge. Computationally, the excess chemical potential is calculated using the Widom insertion method, which involves monitoring the change in internal energy as one incrementally introduces individual molecules into the liquid. However, when dealing with dense polymer liquids, inserting long chains requires generating trial configurations with a bias that favors those at low energy on a unit-by-unit basis: a procedure that becomes more challenging as the number of units increases. Thus, calculating the excess chemical potential of dense polymer liquids using this method becomes computationally intractable as the chain length exceeds N ≥ 30. Here, we adopt a coarse-grained model derived from the integral equation theory for which inserting long polymer chains becomes feasible. The integral equation theory of coarse graining (IECG) represents a polymer as a sphere or a collection of blobs interacting through a soft potential. We employ the IECG approach to compute the excess chemical potential using Widom's method for polymer chains of increasing lengths, extending up to N = 720 monomers, and at densities reaching up to ρ = 0.767 g/cm3. From a fundamental perspective, we demonstrate that the excess chemical potentials remain nearly constant across various levels of coarse graining, offering valuable insights into the consistency of this type of procedure. Ultimately, we argue that current Monte Carlo algorithms, originally designed for atomistic simulations, such as configurational bias Monte Carlo (CBMC) methods, can significantly benefit from the integration of the IECG approach, thereby enhancing their performance in the study of phase diagrams of polymer liquids.

Accessible Molecular System Creator: Building Molecular Configurations Based on the Inaccessible Molecular Volume and Accessible Molecular Surface via Static Monte Carlo Sampling

Monte Carlo (MC) stochastic sampling is a powerful tool in classical molecular simulations that directly connects the observable macroscopic properties of matter and the underlying atomistic interactions. This connection operates within the framework of the statistical mechanics proposed by Gibbs. Most MC simulations are "dynamic," creating statistical ensembles of microstates via a Markovian chain, where each microstate in the ensemble depends only on its previous microstate. Herein, we re-examine an alternative form of MC that generates ensemble members through a "static" approach, building molecular systems stepwise. The basic theory for such an approach traces back to Rosenbluth and Rosenbluth, who proposed "static" stepwise sampling of a polymeric chain. It is almost as old as the Metropolis importance sampling approach used in dynamic MC, although the latter has been considerably more popular than the former. Herein, we address the main obstacle in static MC that has hindered the widespread adoption of Rosenbluth-based approaches in atomistic simulations. The obstacle lies in mapping the molecular accessible volume for adding a molecule in a Rosenbluth-like static sampling of atomistic configurations. We demonstrate a breakthrough by leveraging the ability to analytically map the inaccessible molecular volume and the accessible molecular surface owing to interatomically excluded volume interactions. This advance substantially enhances the ability to create molecular samples using a Rosenbluth-like static building process. The proposed approach can be used as a tool for creating initial configurations in MC or molecular dynamics simulations─a field where Rosenbluth-like static building has been applied. Additionally, this approach can be used as the first step in a perturbation scheme that accurately estimates free energy differences by estimating the chemical work related to molecule addition, removal, or reinsertion within the context of free energy perturbation schemes employed in molecular simulations.

Molecular thermodynamics for food science and engineering

We argue that thanks to molecular modeling approaches, many thermodynamic properties required in Food Science and Food Engineering will be calculable within a few hours from first principles in a near future. These new possibilities will enable to bridge via multiscale modeling composition, process and storage effects to reach global optimization, innovative concepts for food or its packaging. An outlook of techniques and a series of examples are given in this perspective. We emphasize solute chemical potentials in polymers, liquids and their mixtures as they cannot be understood and estimated without theory. The presented atomistic and coarse-grained methods offer a natural framework to their conceptualization in polynary systems, entangled or crosslinked homo- or heteropolymers.

Predicting diffusion coefficients of chemicals in and through packaging materials

Most of the physicochemical properties in polymers such as activity and partition coefficients, diffusion coefficients, and their activation with temperature are accessible to direct calculations from first principles. Such predictions are particularly relevant for food packaging as they can be used (1) to demonstrate the compliance or safety of numerous polymer materials and of their constitutive substances (e.g. additives, residues…), when they are used: as containers, coatings, sealants, gaskets, printing inks, etc. (2) or to predict the indirect contamination of food by pollutants (e.g. from recycled polymers, storage ambiance…) (3) or to assess the plasticization of materials in contact by food constituents (e.g. fat matter, aroma…). This review article summarizes the classical and last mechanistic descriptions of diffusion in polymers and discusses the reliability of semi-empirical approaches used for compliance testing both in EU and US. It is concluded that simulation of diffusion in or through polymers is not limited to worst-case assumptions but could also be applied to real cases for risk assessment, designing packaging with low leaching risk or to synthesize plastic additives with low diffusion rates.

Calculations of the light absorption spectra of porphyrinoid chromophores for dye-sensitized solar cells

Solar power is a strong alternative to the currently used fossil fuels in order to satisfy the world's energy needs. Among them, dye-sensitized solar cells (DSSC) represent a low-cost option. Efficient and cheap dyes are currently needed to make DSSCs competitive. Computational chemistry can be used to guide the design of new light-absorbing chromophores. Here, we have computationally studied the lowest excited states of ZnPBAT, which is a recently synthesized porphyrinoid chromophore with high light-absorption efficiency. The calculations have been performed at ab initio correlated levels of theory employing second-order coupled clusters (CC2) and algebraic diagrammatic construction using second order (ADC(2)) methods and by performing density functional theory (DFT) calculations using the time-dependent DFT (TDDFT) approach for excitation energies. The ultraviolet-visible (UV-vis) spectrum calculated at the ADC(2) and CC2 levels agrees well with the experimental one. The calculations show that ZnPBAT has six electronic transitions in the visible range of the absorption spectrum. The ab initio correlated calculations and previously reported experimental data have been used to assess the performance of several well-known density functionals that have been employed in the present TDDFT study. Solvent effects have been estimated by using the conductor-like screening model (COSMO). The influence of the addition of a TiO₂ cluster to the chromophore systems has also been investigated. The results indicate that both CAM-B3LYP and Becke's "half-and-half" (BHLYP) density functionals are appropriate for the studies of excitation energies in the blue range of the visible spectrum for these kinds of porphyrinoid chromophores, whereas the excitation energies of the Q band calculated at the ab initio correlated level are more accurate than those obtained in the present TDDFT calculations. The inclusion of solvent effects has a modest influence on the spectrum of the protonated form of the studied chromophores, whereas solvent models are crucial when studying the absorption spectrum of the anionic chromophore. The calculated UV-vis spectrum for the chromophore anion is not significantly affected by attaching a TiO₂ cluster to it.

Multidimensional direct free energy perturbation

In this work we propose a multidimensional free energy perturbation scheme that allows the evaluation of the free energy difference between a state sampled based on importance sampling and almost any state that can be constructed by the reduction of the number of molecules in the system and the change of either the interaction energy or the thermodynamic state variable (e.g., the temperature) of the system. We show that via this approach it is possible to evaluate any thermodynamic property included but not limited to free energy, chemical potential, and pressure, along a series of isotherms from a single molecular simulation.

Solubility of Gases and Liquids in Glassy Polymers

This review discusses a macroscopic thermodynamic procedure to calculate the solubility of gases, vapors, and liquids in glassy polymers that is based on the general procedure provided by the nonequilibrium thermodynamics for glassy polymers (NET-GP) method. Several examples are presented using various nonequilibrium (NE) models including lattice fluid (NELF), statistical associating fluid theory (NE-SAFT), and perturbed hard sphere chain (NE-PHSC). Particular applications illustrate the calculation of infinite-dilution solubility coefficients in different glassy polymers and the prediction of solubility isotherms for different gases and vapors in pure polymers as well as in polymer blends. The determination of model parameters is discussed, and the predictive abilities of the models are illustrated. Attention is also given to the solubility of gas mixtures and solubility isotherms in nanocomposite mixed matrices. The fractional free volume determined from solubility data can be used to correlate solute diffusivities in mixed matrices.