Accelerated ReaxFF Simulations for Describing the Reactive Cross-Linking of Polymers

Abstract

Various methods have been developed to perform atomistic-scale simulations for the cross-linking of polymers. Most of these methods involve connecting the reactive sites of the monomers, but these typically do not capture the entire reaction process from the reactants to final products through transition states. Experimental time scales for cross-linking reactions in polymers range from minutes to hours, which are time scales that are inaccessible to atomistic-scale simulations. Because simulating reactions on realistic time scales is computationally expensive, in this investigation, an accelerated simulation method was developed within the ReaxFF reactive force field framework. In this method, the reactants are tracked until they reach a nonreactive configuration that provides a good starting point for a reactive event. Subsequently, the reactants are provided with a sufficient amount of energy-equivalent or slightly larger than their lowest-energy reaction barrier-to overcome the barrier for the cross-linking process and form desired products. This allows simulation of cross-linking at realistic, low temperatures, which helps to mimic chemical reactions and avoids unwanted high-temperature side reactions and still allows us to reject high-barrier events. It should be noted that not all accelerated events are successful as high local strain can lead to reaction rejections. The validity of the ReaxFF force field was tested for three different types of transition state, possibly for polymerization of epoxides, and good agreement with quantum mechanical methods was observed. The accelerated method was further implemented to study the cross-linking of diglycidyl ether of bisphenol F (bis F) and diethyltoluenediamine (DETDA), and a reasonably high percentage (82%) of cross-linking was obtained. The simulated cross-linked polymer was then tested for density, glass transition temperature, and modulus and found to be in good agreement with experiments. Results indicate that this newly developed accelerated simulation method in ReaxFF can be a useful tool to perform atomistic-scale simulations on polymerization processes that have a relatively high reaction barrier at a realistic, low temperature.

Tribochemistry: A Review of Reactive Molecular Dynamics Simulations

“…Another approach is to use accelerated molecular dynamics methods that use numerical tricks to encourage reactions to happen sooner. The timescale of reactive molecular dynamics simulations has been extended with multiple accelerated simulation methods [94][95][96][97]. Most of these methods are limited to physical phenomena that occur through rare events [98], such as stick-slip friction where very fast slip events are separated by relatively long periods of stick [99] but they do not offer any speed-up for continuous processes.…”

Exploring the Chemistry of Low‐Temperature Ignition by Pressure‐Accelerated Dynamics

“…[29] They have been shown to be applicable to a great variety of problems. [37][38][39][40][41][42][43][44][45] Still, there are limitations to these methods. It has been found, for example, that the construction of bias potentials is not trivial.…”

“…[47] Originally, the bond-boost method was designed to accelerate bond breaking, [28] but the method has been extended to accelerate both bond breaking and forming of pre-defined atoms. [45] In processes, such as low-temperature ignition, in which the reactivity is determined by meta-stable reaction equilibria (O 2 -addition), and slow subsequent reactions (internal H-atom abstraction, cf. Figure 1), acceleration methods should push the reaction equilibrium to the product side to increase the probability of observing subsequent reactions, which the bond-boost method does not achieve.…”

A Theoretical Study on Trehalose + Water Mixtures for Dry Preservation Purposes

“…Subsequently, the evolution of the predicted density for the different trehalose-water mixture at temperature range between 100-400 K, allows to infer T g values for each solution concentration. The T g values were determined from the temperature evolution of density for each mixture composition, although the most common approaches for the determination of T g stand on the evolution of properties such as heat capacity, thermal expansion coefficient, diffusion coefficient or specific volume [29]; the use of density has also been considered in the literature [39].…”