Thermoplastic polyurethanes (TPUs) are useful materials for numerous applications due in part to their outstanding resilience and ability to dissipate energy under large mechanical deformation. However, the mechanistic understanding of the origins of these mechanical properties at the molecular level remains elusive, largely due to the complex, heterogeneous structure of these materials, which arises from the segregation of chemically distinct segments into hard and soft domains. In this work, molecular simulations are used to identify the mechanism of mechanical response under large tensile deformation of a common thermoplastic polyurethane comprising 4,4′-diphenylmethane diisocyanate and n-butanediol (hard segment) and poly(tetramethylene oxide) (soft segment), with atomic resolution. The simulation employs a lamellar stack model constructed using the Interphase Monte Carlo method established previously for semicrystalline polymers, which models the interfacial zone between hard and soft domains with thermodynamically rigorous distributions of bridges, loops, and tails. Molecular-level mechanisms responsible for yield, toughening, and the Mullins effect are reported. We have found several distinct mechanisms for yield and plastic flow, which we categorize as (i) cavitation, (ii) chain pull-out, (iii) localized melting with shear band formation, and (iv) block slip. The activity of these mechanisms depends on the topology of chains in the soft domain and the direction of loading (e.g., parallel or perpendicular to the interface). Further insights regarding toughening mechanisms and the Mullins effect are obtained from cyclic loading, where mechanisms ii to iv were found to be irreversible and account for the superior resilience and dissipation at large tensile strains in thermoplastic polyurethanes.
In this work, we propose a highly parallelizable sampling scheme designed for atomistic simulations of glassy materials in the vicinity of the glass-transition temperature T g , based on the idea of inherent structures (IS). Glassy dynamics is envisioned as a combination of two types of motions: (a) an "in basin" vibrational motion in the vicinity of a potential energy minimum (IS), and (b) transitions from one basin to another. In order to perform efficient dynamical sampling in the vicinity of T g , we propose an "on the fly" definition of metabasins (i.e., collections of basins communicating via fast transitions in which the system spends a sufficient time before moving on to a neighboring collection). Our criterion for defining metabasins is based on the rate of identification of new basins in the course of a canonical molecular dynamics (MD) run. In order to compute individual rate constants between basins and metabasins, we propose to follow a swarm of microcanonical MD trajectories initiated at phasespace points sampled by a canonical MD run that is artificially trapped within a metabasin. The execution time required by this highly parallelizable scheme is reduced dramatically, since no information exchange takes place between the microcanonical trajectories. Results from our parallel methodology are compared against results from artificially trapped canonical MD runs, in terms of the evaluated rate constants, and found to be in very good agreement. Parallel simulations have been conducted on up to 250 processors, achieving almost linear scaling. The validity of our definition of metabasins is confirmed by analysis of the resulting network of basins.
We report the use of atomistic simulation to study semicrystalline poly(tetramethylene oxide) (PTMO), which is one of the major components of thermoplastic polyurethanes. This work reports the first application of an Interphase Monte Carlo model previously developed for polyethylene to a more complex chemistry involving heteroatoms, about which much less is known experimentally. The interface between the crystalline and amorphous domains of PTMO has been modeled in detail, complete with the equilibrium distributions of tails, loops and bridges. In doing so, a criterion has been established for selecting the relevant interface between domains, and a methodology developed that identifies the energetically most favorable interface in a heterogeneous material. A representative sample of configurations was then simulated by molecular dynamics, and analysis of deformation to small strains at different strain rates is described. Estimation of the full stiffness matrix of semicrystalline PTMO is reported for the first time.
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