Simulations of the Biodegradation of Citrate-Based Polymers for Artificial Scaffolds Using Accelerated Reactive Molecular Dynamics

Molecular Simulations to Elucidate Transport Phenomena in Polymeric Membranes

Despite decades of dominance in separation technology, progress in the design and development of high-performance polymer-based membranes has been incremental. Recent advances in materials science and chemical synthesis provide opportunities for molecular-level design of next-generation membrane materials. Such designs necessitate a fundamental understanding of transport and separation mechanisms at the molecular scale. Molecular simulations are important tools that could lead to the development of fundamental structure-property-performance relationships for advancing membrane design. In this Perspective, we assess the application and capability of molecular simulations to understand the mechanisms of ion and water transport across polymeric membranes. Additionally, we discuss the reliability of molecular models in mimicking the structure and chemistry of nanochannels and transport pathways in polymeric membranes. We conclude by providing research directions for resolving key knowledge gaps related to transport phenomena in polymeric membranes and for the construction of structure-property-performance relationships for the design of next-generation membranes.

Molecular Alignment of a Meta-Aramid on Carbon Nanotubes by In Situ Interfacial Polymerization

Molecularly organized nanocomposites of polymers and carbon nanotubes (CNTs) have great promise as high-performance materials; in particular, conformal deposition of polymers can control interfacial properties for mechanical load transfer, electrical or thermal transport, or electro/chemical transduction. However, controllability of polymer-CNT interaction remains a challenge with common processing methods that combine CNTs and polymers in melt or in solution, often leading to nonuniform polymer distribution and CNT aggregation. Here, we demonstrate CNTs within net-shape sheets can be controllably coated with a conformal coating of meta-aramid by simultaneous capillary infiltration and interfacial polymerization. We determine that π-interaction between the polymer and CNTs results in chain alignment parallel to the CNT outer wall. Subsequent nucleation and growth of the precipitated aramid forms a smooth continuous layered sheath around the CNTs. These findings motivate future investigation of mechanical properties of the resulting composites, and adaptation of the in situ polymerization method to other substrates.

Machine Learning-Assisted Hybrid ReaxFF Simulations

We have developed a machine learning (ML)-assisted Hybrid ReaxFF simulation method ("Hybrid/Reax"), which alternates reactive and non-reactive molecular dynamics simulations with the assistance of ML models to simulate phenomena that require longer time scales and/or larger systems than are typically accessible to ReaxFF. Hybrid/Reax uses a specialized tracking tool during the reactive simulations to further accelerate chemical reactions. Non-reactive simulations are used to equilibrate the system after the reactive simulation stage. ML models are used between reactive and non-reactive stages to predict non-reactive force field parameters of the system based on the updated bond topology. Hybrid/Reax simulation cycles can be continued until the desired chemical reactions are observed. As a case study, this method was used to study the cross-linking of a polyethylene (PE) matrix analogue (decane) with the cross-linking agent dicumyl peroxide (DCP). We were able to run relatively long simulations [>20 million molecular dynamics (MD) steps] on a small test system (4660 atoms) to simulate cross-linking reactions of PE in the presence of DCP. Starting with 80 PE molecules, more than half of them cross-linked by the end of the Hybrid/Reax cycles on a single Xeon processor in under 48 h. This simulation would take approximately 1 month if run with pure ReaxFF MD on the same machine.

Simulation Study of the Effects of Interfacial Bonds on Adhesion and Fracture Behavior of Epoxy Resin Layers

The adhesion and fracture behavior of tetraglycidyl-4,4'-diaminodiphenylmethane (TGDDM)/4,4'-diaminodiphenyl sulfone (44DDS)-bisphenol A diglycidyl ether (DGEBA)/44DDS layer interfaces were investigated by molecular dynamics (MD) simulation, mainly focusing on the role of covalent and noncovalent interactions. To accurately investigate the bond dissociation processes, the force field parameters of several bond potentials of the epoxy resin polymers were optimized by density functional theory calculations. In the MD simulations under a tensile load, small voids gradually developed without covalent bond dissociation in the plateau region. In the final large strain region, the stress rapidly increased with bond breaking, leading to failure. When the chemical bonds across the interface between the two layers were removed, the stress-strain curve in the initial elastic region was almost the same as that with interfacial bonds. This showed that the nonbonded interactions governed adhesion strength in the initial elastic region. In contrast, the bonded interactions at interfaces played important roles in the hardening regions because the bonded interactions made the major contribution to the fracture energies. We also investigated the effect of the etherification reaction in cross-linking. It was found that the etherification reaction mainly contributed to the behavior in the late region with large strain. These simulation results revealed that the nonbonded interactions, especially, van der Waals interactions, are important factors for adhesion of the different polymer layers in the small strain region up to the yield point.

Thermophysical properties of water using reactive force fields

The widescale importance and rich phenomenology of water continue to motivate the development of computational models. ReaxFF force fields incorporate many characteristics desirable for modeling aqueous systems: molecular flexibility, polarization, and chemical reactivity (bond formation and breaking). However, their ability to model the general properties of water has not been evaluated in detail. We present comprehensive benchmarks of the thermophysical properties of water for two ReaxFF models, the water-2017 and CHON-2017_weak force fields. These include structural, electrostatic, vibrational, thermodynamic, coexistence, and transport properties at ambient conditions (300 K and 0.997 g cm^-3) and along the standard pressure (1 bar) isobar. Overall, CHON-2017_weak predicts more accurate thermophysical properties than the water-2017 force field. Based on our results, we recommend potential avenues for improvement: the dipole moment to quadrupole moment ratio, the self-diffusion coefficient, especially for water-2017, and the gas phase vibrational frequencies with the aim to improve the vibrational properties of liquid water.

CONI-Net: Machine Learning of Separable Intermolecular Force Fields

Noncovalent interactions (NCIs) play an essential role in soft matter and biomolecular simulations. The ab initio method symmetry-adapted perturbation theory allows a precise quantitative analysis of NCIs and offers an inherent energy decomposition, enabling a deeper understanding of the nature of intermolecular interactions. However, this method is limited to small systems, for instance, dimers of molecules. Here, we present a scale-bridging approach to systematically derive an intermolecular force field from ab initio data while preserving the energy decomposition of the underlying method. We apply the model in molecular dynamics simulations of several solvents and compare two predicted thermodynamic observables-mass density and enthalpy of vaporization-to experiments and established force fields. For a data set limited to hydrocarbons, we investigate the extrapolation capabilities to molecules absent from the training set. Overall, despite the affordable moderate quality of the reference ab initio data, we find promising results. With the straightforward data set generation procedure and the lack of target data in the fitting process, we have developed a method that enables the rapid development of predictive force fields with an extra dimension of insights into the balance of NCIs.

Chitin nanocrystals assisted 3D printing of polycitrate thermoset bioelastomers

Citrate-based thermoset bioelastomer has numerous tissue engineering applications. However, its insoluble and unmeltable features restricted processing techniques for fabricating complex scaffolds. Herein, direct ink writing (DIW) was explored for 3D printing of poly(1, 8-octanediol-co-Pluronic F127 citrate) (POFC) bioelastomer scaffolds considering that POFC prepolymer (pre-POFC) was waterborne and could form a stable emulsion. The pre-POFC emulsion couldn't be printed, however, chitin nanocrystal (ChiNC) could be as a rheological modifier to tune the flow behavior of pre-POFC emulsion, and thus DIW printing of POFC scaffolds was successfully realized; moreover, ChiNC was also as a supporting agent to prevent collapse of filaments during thermocuring, and simultaneously as a biobased nanofiller to reinforce scaffolds. The rheological analyses showed the pre-POFC/ChiNC inks fulfilled the requirements for DIW printing. The printed scaffolds exhibited low swelling, and good performances in strength and resilence. Furthermore, the entire process was easily performed and eco-friendly.