Determination of interaction parameters in a bottom-up approach employed in reactive dissipative particle dynamics simulations for thermosetting polymers

The limitations in previous dissipative particle dynamics (DPD) studies confined simulations to a narrow resin range. This study refines DPD parameter calculation methodology, extending its application to diverse polymer materials. Using a bottom-up approach with molecular dynamics (MD) simulations, we evaluated solubility parameters and bead number density governing nonbonded interactions via the Flory-Huggins parameter and covalent-bonded interactions. Two solubility parameter methods, Hildebrand and Krevelen-Hoftyzer, were compared for DPD simulations. The Hildebrand method, utilizing MD simulations, demonstrates higher consistency and broader applicability in determining solubility parameters for all DPD particles. The DPD/MD curing reaction process was examined in three epoxy systems: DGEBA/4,4'-DDS, DGEBA/MPDA and DGEBA/DETA. Calculations for the curing profile, gelation point, radial distribution function and branch ratio were performed. Compared to MD data for DGEBA/4,4'-DDS, the maximum deviation in secondary reactions between epoxy and amine groups according to DPD simulations with Krevelen-Hoftyzer was 14.8%, while with the Hildebrand method, it was 1.7%. The accuracy of the DPD curing reaction in reproducing the structural properties verifies its expanded application to general polymeric material simulations. The proposed curing DPD simulations, with a short run time and minimal computational resources, contributes to high-throughput screening for optimal resins and investigates mesoscopic inhomogeneous structures in large resin systems.

Dissipative Particle Dynamics Simulation for Reaction-Induced Phase Separation of Thermoset/Thermoplastic Blends

Reaction-induced phase separation occurs during the curing reaction when a thermoplastic resin is dissolved in a thermoset resin, which enables toughening of the thermoset resin. As resin properties vary significantly depending on the morphology of the phase-separated structure, controlling the morphology formation is of critical importance. Reaction-induced phase separation is a phenomenon that ranges from the chemical reaction scale to the mesoscale dynamics of polymer molecules. In this study, we performed curing simulations using dissipative particle dynamics (DPD) coupled with a reaction model to reproduce reaction-induced phase separation. The curing reaction properties of the thermoset resin were determined by ab initio quantum chemical calculations, and the DPD parameters were determined by all-atom molecular dynamics simulations. This enabled mesoscopic simulations, including reactions that reflect the intrinsic material properties. The effects of the thermoplastic resin concentration, molecular weight, and curing conditions on the phase-separation morphology were evaluated, and the cure shrinkage and stiffness of each cured resin were confirmed to be consistent with the experimental trends. Furthermore, the local strain field under tensile deformation was visualized, and the inhomogeneous strain field caused by the phase-separated structures of two resins with different stiffnesses was revealed. These results can aid in understanding the toughening properties of thermoplastic additives at the molecular level.

Reaction-induced morphological transitions in a blend of diblock copolymers and reactive monomers: dissipative particle dynamics simulation

The dissipative particle dynamics (DPD) method is applied to the morphological transitions of microphase-separated domains in a mixture of symmetric AB-diblock copolymers and reactive C-monomers, where polymerization and cross-linking reactions take place among C-monomers. The initial structure for the DPD simulation is an equilibrated cylindrical domain structure prepared by the density-biased Monte Carlo method with density profiles obtained from the self-consistent field theory. By introducing a cross-linking reaction among reactive C-monomers, we confirmed that the DPD simulation reproduces the morphological transitions observed in experiments, where the domain morphology changes due to segregation between A-blocks of diblock copolymers and cross-linking networks of C-monomers. When the cross-linking reaction of C-monomers is sufficiently fast compared to the deformation of the domains, the initial cylindrical domains are preserved, while the distance between the domains increases. On the other hand, when the formation of the cross-linking network is slow, the domains can deform and reconnect with each other in the developing cross-linking network. In this case, we observe morphological transitions from the initial domain morphology with a large-curvature interface to another domain morphology with a smaller-curvature interface, such as the transition from the cylindrical phase to the lamellar phase. We calculated the spatial correlations in the microphase-separated domains and found that such correlations are affected by the speed of the formation of the cross-linking network depending on whether the bridging between microphase-separated domains occurs in a nucleation and growth process or in a spinodal decomposition process.

Mesoscale molecular assembly is favored by the active, crowded cytoplasm

The mesoscale organization of molecules into membraneless biomolecular condensates is emerging as a key mechanism of rapid spatiotemporal control in cells1. Principles of biomolecular condensation have been revealed through in vitro reconstitution2. However, intracellular environments are much more complex than test-tube environments: They are viscoelastic, highly crowded at the mesoscale, and are far from thermodynamic equilibrium due to the constant action of energy-consuming processes3. We developed synDrops, a synthetic phase separation system, to study how the cellular environment affects condensate formation. Three key features enable physical analysis: synDrops are inducible, bioorthogonal, and have well-defined geometry. This design allows kinetic analysis of synDrop assembly and facilitates computational simulation of the process. We compared experiments and simulations to determine that macromolecular crowding promotes condensate nucleation but inhibits droplet growth through coalescence. ATP-dependent cellular activities help overcome the frustration of growth. In particular, actomyosin dynamics potentiate droplet growth by reducing confinement and elasticity in the mammalian cytoplasm, thereby enabling synDrop coarsening. Our results demonstrate that mesoscale molecular assembly is favored by the combined effects of crowding and active matter in the cytoplasm. These results move toward a better predictive understanding of condensate formation in vivo.

Block Chemistry for Accurate Modeling of Epoxy Resins

Accurate molecular modeling of the physical and chemical behavior of highly cross-linked epoxy resins at the atomistic scale is important for the design of new property-optimized materials. However, a systematic approach to parametrizing and characterizing these systems in molecular dynamics is missing. We therefore present a unified scheme to derive atomic charges for amine-based epoxy resins, in agreement with the AMBER force field, based on defining reactive fragments─blocks─building the network. The approach is applicable to all stages of curing from pure liquid to gelation to fully cured glass. We utilize this approach to study DGEBA/DDS epoxy systems, incorporating dynamic topology changes into atomistic molecular dynamics simulations of the curing reaction with 127,000 atoms. We study size effects in our simulations and predict the gel point utilizing a rigorous percolation theory to recover accurately the experimental data. Furthermore, we observe excellent agreement between the estimated and the experimentally determined glass transition temperatures as a function of curing rate. Finally, we demonstrate the quality of our model by the prediction of the elastic modulus based on uniaxial tensile tests. The presented scheme paves the way for a broadly consistent approach for modeling and characterizing all amine-based epoxy resins.

Addressing diffusion behavior and impact in an epoxy-amine cure system using molecular dynamics simulations

To deepen understanding of diffusion-controlled crosslinking, molecular dynamics (MD) simulations are carried out by taking the diffusion image of 3,3'-diamino diphenyl sulfone (3,3'-DDS) and polyethersulfone (PES) with epoxy resin varying temperatures from 393.15 to 473.15 K over crosslinking conversion of 0-85%. The diffusion of PES and 3,3'-DDS into the bulk increased with increasing the temperature as a result of enhanced mobility of the molecules when the difference between the glass-transition temperature (T_g) and the curing temperature. Beyond the onset points of the converged crosslinking conversion ratio of 3,3'-DDS and PES, their diffusion properties are obviously restricted with crosslinking conversion ratio. At low crosslinking conversion ratios (> 10%), the diffusion coefficients of triglycidyl p-aminophenol (TGAP) were 1.1 times higher than those of diglycidyl ether of bisphenol F (DGEBF) because of the lower molecular weight of TGAP. On the other hand, the diffusion coefficients of TGAP decreased when the crosslinking ratio was up to ~ 60% because, compared with DGEBF, it had more functional groups available to react with the curing agent. At higher crosslinking ratios, the diffusion coefficients of both resins converged to zero as a result of their highly crosslinked structures.

Thermoset resin curing simulation using quantum-chemical reaction path calculation and dissipative particle dynamics

Thermoset resin, which is commonly used as a matrix in carbon-fiber-reinforced plastic, requires curing procedures. We propose a curing simulation technique involving a dissipative particle dynamics (DPD) simulation, which can simulate a larger system and longer time period than those of conventional all-atom molecular dynamics (AA-MD) simulations. The proposed curing DPD simulation can represent the thermoset resin exothermic reaction process precisely by considering each reactivity according to the reaction types calculated via quantum-chemical reaction path calculations. The cure reaction process given by the curing DPD simulation agrees well with that given by a conventional curing AA-MD simulation, but with run-time and computational-resource reductions of 1/480 and 1/10 times, respectively. We also conduct reverse mapping, through which the AA-MD system can be reconstructed from the DPD system, to evaluate the structural and thermomechanical properties. The X-ray diffraction pattern and thermomechanical properties of the reconstructed system agree well with those of the systems derived from the curing AA-MD simulation and experimental setup. Therefore, a cured-resin AA-MD system can be obtained from a curing DPD simulation at an extremely low computational cost, and the thermomechanical properties can be evaluated precisely using this system. The proposed curing simulation technique can be applied in high-throughput screening for better materials properties and in large system calculations.

Closed-Form Coexistence Equation for Phase Separation of Polymeric Mixtures in Dissipative Particle Dynamics

To date, no extensive study of the phase diagram for binary fluid mixtures in dissipative particle dynamics (DPD) has been published. This is especially pertinent for newer parameterization schemes where the self-self interaction, or the effective volume, of different particle types is varied. This work presents an exhaustive study of the parameter space concerning DPD particles with soft interaction potentials. Moreover, we propose a closed-form coexistence equation or binodal curve that is inspired by the Flory-Huggins model. This equation describes the phase diagram of all binary mixtures made up out of monomers, homopolymers, and the mixtures thereof when self-self interactions are varied. The mean absolute percentage error (MAPE) of the equation on simulated data, including validation simulations, is 1.02%. The equation can a priori predict the phase separation of mixtures using only DPD interaction parameters. The proposed coexistence equation can therefore be used to directly validate interaction parameters resulting from novel parameterization schemes, including coarse graining and equations of state, without the need for additional simulations. Finally, it is shown that the choice of bond potential markedly influences phase behavior.

General-Purpose Coarse-Grained Toughened Thermoset Model for 44DDS/DGEBA/PES

The objective of this work is to predict the morphology and material properties of crosslinking polymers used in aerospace applications. We extend the open-source dybond plugin for HOOMD-Blue to implement a new coarse-grained model of reacting epoxy thermosets and use the 44DDS/DGEBA/PES system as a case study for calibration and validation. We parameterize the coarse-grained model from atomistic solubility data, calibrate reaction dynamics against experiments, and check for size-dependent artifacts. We validate model predictions by comparing glass transition temperatures measurements at arbitrary degree of cure, gel-points, and morphology predictions against experiments. We demonstrate for the first time in molecular simulations the cure-path dependence of toughened thermoset morphologies.