Molecular signatures of the glass transition in polymers

Temperature-Transferable Coarse-Grained Models for Volumetric Properties of Poly(lactic Acid)

A new coarse-grained (CG) model, for which each monomer is mapped as one bead at its center of mass, was developed for simulating the volumetric properties of the polylactide (PLA) bulk. The three bonded CG potentials are first parametrized against the strain energies of the dimer, trimer, and tetramer, and the nonbonded CG potentials are then optimized to match the melt densities of the decamer. With the derived CG potentials, molecular dynamics (MD) simulations are found to reproduce thermal expansion and glass transition. By rescaling the dihedral and nonbonded potentials with temperature-independent factors, the glass transition temperature (Tg) is also satisfactorily restored with little modifications on the volumetric expansive coefficients at both rubbery and glassy states. Therefore, the finally optimized CG potentials exhibit excellent temperature transferability, as rationalized by the Simha-Boyer relation. Furthermore, it is confirmed that the dihedral torsions and nonbonded interactions play key roles in glass transition. Also, the simulated bulk moduli and conformational properties in a wide temperature range compare well with the referenced data. The proposed multiscale scheme has great potential in simulating thermo-mechanical properties of PLA and other polymers.

A Computationally Informed Unified View on the Effect of Polarity and Sterics on the Glass Transition in Vinyl-based Polymer Melts

We unveil a unified view on the effect of side chains on the glass transition temperatures (Tg) in polymer melts by using molecular dynamics simulations, density functional theory calculations, and available experimental data. We use acrylates as a model system and evaluate the effect of n-alkyl side chains on Tg. We find that backbone dihedral angle fluctuations follow established patterns due to sterics, as expected. However, we also find that the dihedral angle orthogonal to the backbone, which normally is neglected when discussing the effect on Tg, introduces a secondary rotational degree of freedom which strongly impacts Tg. These results are in agreement with experiments and generalize to multiple other polymer systems, as is demonstrated using available experimental data. Conversely, n-alkyl pendant groups attached to the side group reduce Tg. Our work establishes a coherent framework that unifies previously established trends, emphasizing the polarity and size effects of n-alkyl chains on Tg.

Determining glass transition in all-atom acrylic polymeric melt simulations using machine learning

The functionality of many polymeric materials depends on their glass transition temperatures (Tg). In computer simulations, Tg is often calculated from the gradual change in macroscopic properties. Precise determination of this change depends on the fitting protocols. We previously proposed a robust data-driven approach to determine Tg from the molecular dynamics simulation data of a coarse-grained semiflexible polymer model. In contrast to the global macroscopic properties, our method relies on high-resolution microscopic details. Here, we demonstrate the generality of our approach by using various dimensionality reduction and clustering methods and apply it to an atomistic model of acrylic polymers. Our study reveals the explicit contribution of the side chain and backbone residues in influencing the determination of the glass transition temperature.

Data-Driven Identification and Analysis of the Glass Transition in Polymer Melts

Understanding the nature of glass transition, as well as the precise estimation of the glass transition temperature for polymeric materials, remains open questions in both experimental and theoretical polymer sciences. We propose a data-driven approach, which utilizes the high-resolution details accessible through the molecular dynamics simulation and considers the structural information on individual chains. It clearly identifies the glass transition temperature of polymer melts of weakly semiflexible chains. By combining principal component analysis and clustering, we identify the glass transition temperature in the asymptotic limit even from relatively short time trajectories, which just reach into the Rouse-like monomer displacement regime. We demonstrate that fluctuations captured by the principal component analysis reflect the change in a chain's behavior: from conformational rearrangement above to small fluctuations below the glass transition temperature. Our approach is straightforward to apply and should be applicable to other polymeric glass-forming liquids.