Coarse-Grained Molecular Dynamics Modeling of a Branched Polyetherimide

Polyimide Polymer Simulations through Coarse-Grained Modeling: Prediction of Structure, Physical Properties, and Gas Separation Properties

In this study, we introduce a set of coarse-grained (CG) force field parameters for simulating a series of 6FDA-based polyimides. Utilizing atomistic descriptors, we developed CG models that accurately predict the specific volume of the polymers under investigation. Our findings suggest that certain parameters, particularly those associated with specific diamines, can be employed to predict properties such as density using a multiple linear regression. Our study further explores the halogenation of diamines and proposes methods for estimating intermolecular interaction parameters. Our calculations refer to various structural properties, including the radius of gyration, end-to-end distance, glass transition temperature, and diffusion coefficients. Utilizing the newly developed CG force field parameters, we conducted gas separation simulations for 6FDA-DAM polyimide, particularly to predict both sorption- and diffusion-separation mechanisms within the polymer. These simulations provided excellent agreement with experimental data on solubility, diffusion, and permeability selectivity for CO2/CH4, O2/N2, and propylene/propane. The results contribute significantly to our understanding of polyimide behavior, and the parameters proposed here offer a promising tool for the development of new materials with tailored properties for targeted applications.

The Transport Properties of Semi-Crystalline Polyetherimide BPDA-P3 in Amorphous and Ordered States: Computer Simulations

The effect of polymer chain ordering on the transport properties of the polymer membrane was examined for the semi-crystalline heterocyclic polyetherimide (PEI) BPDA-P3 based on 3,3',4,4'-biphenyltetracarboxylic dianhydride (BPDA) and diamine 1,4-bis [4-(4-aminophenoxy)phenoxy]benzene (P3). All-atom Molecular Dynamics (MD) simulations were used to investigate the gas diffusion process carried through the pores of a free volume several nanometers in size. The long-term (~30 μs) MD simulations of BPDA-P3 were performed at T = 600 K, close to the experimental value of the melting temperature (Tm ≈ 577 K). It was found during the simulations that the transition of the PEI from an amorphous state to an ordered one occurred. We determined a decrease in solubility for both the gases examined (CO2 and CH4), caused by the redistribution of free volume elements occurring during the structural ordering of the polymer chains in glassy state (Tg ≈ 487 K). By analyzing the diffusion coefficients in the ordered state, the presence of gas diffusion anisotropy was found. However, the averaged values of the diffusion coefficients did not differ from each other in the amorphous and ordered states. Thus, permeability in the observed system is primarily determined by gas solubility, rather than by gas diffusion.

Hebbian Learning on Small Data Enables Experimental Discovery of High Tg Polyimides

We report a study combining computational design and experimental evaluation of polyimides with high glass transition temperatures: T_g between 220 °C and 500 °C. The computational approach is based on the recently introduced competitive learning algorithm, supervised self-organizing maps (SUSI), which we recast as an ensemble method, e-SUSI. We use e-SUSI to solve both unsupervised and supervised/semisupervised learning tasks capturing structure-property relationships of high-T_g polyimides historically studied at Almaden Research Center. Predictors trained on historical data were applied to the combinatorial library of novel polyimides and informed selection of the candidates for synthesis and characterization. In this manner, three new polyimides were prepared with T_g values 281 °C, 282 °C, and 331 °C. The measured values closely agree with the predicted values 273 °C, 311 °C, and 335 °C, respectively. We discuss specific reasons that make the proposed computational design strategy attractive in rapid, deliverable-driven efforts with limited, small-batch data sets.

An Enhanced Scheme for Multiscale Modeling of Thermomechanical Properties of Polymer Bulks

While multiscale modeling significantly enhances the capability of molecular simulations of polymer systems, it is well realized that the systematically derived coarse-grained (CG) models generally underestimate the thermomechanical properties. In this work, a charge-based mapping scheme has been adopted to include explicit electrostatic interactions and benchmarked against two typical polymers, atactic poly(methyl methacrylate) (PMMA) and polystyrene (PS). The CG potentials are parameterized against the oligomer bulks of nine monomers per chain to match the essential structural features and the two basic pressure-volume-temperature (PVT) properties, which are obtained from the all-atomistic (AA) molecular dynamics (MD) simulations at a single elevated temperature. The so-parameterized CG potentials are extended with the MD method to simulate the two polymer bulks of one hundred monomers per chain over a wide temperature range. Without any scaling, all the simulated results, including mass densities and bulk moduli at room temperature, thermal expansion coefficients at rubbery and glassy states, and glass transition temperatures (T_g), compare well with the corresponding experimental data. The proposed scheme not only contributes to realistically simulating various thermomechanical properties of both apolar and polar polymers but also allows for directly simulating their electrical properties.