Harnessing entropy to enhance toughness in reversibly crosslinked polymer networks

Reversible crosslinking is a design paradigm for polymeric materials, wherein they are microscopically reinforced with chemical species that form transient crosslinks between the polymer chains. Besides the potential for self-healing, recent experimental work suggests that freely diffusing reversible crosslinks in polymer networks, such as gels, can enhance the toughness of the material without substantial change in elasticity. This presents the opportunity for making highly elastic materials that can be strained to a large extent before rupturing. Here, we employ Gaussian chain theory, molecular simulation, and polymer self-consistent field theory for networks to construct an equilibrium picture for how reversible crosslinks can toughen a polymer network without affecting its linear elasticity. Maximisation of polymer entropy drives the reversible crosslinks to bind preferentially near the permanent crosslinks in the network, leading to local molecular reinforcement without significant alteration of the network topology. In equilibrium conditions, permanent crosslinks share effectively the load with neighbouring reversible crosslinks, forming multi-functional crosslink points. The network is thereby globally toughened, while the linear elasticity is left largely unaltered. Practical guidelines are proposed to optimise this design in experiment, along with a discussion of key kinetic and timescale considerations

MOLECULAR MODELING OF HIGH-PERFORMANCE THERMOSET POLYMER MATRIX COMPOSITES FOR AEROSPACE APPLICATIONS

The global efforts from major space agencies to transport humans to Mars will require a novel lightweight and ultra-high strength material for the spacecraft structure. Three decades of research with the carbon nanotubes (CNTs) have proved that the material can be an ideal candidate for the composite reinforcement if certain shortcomings are overcome. Also, the rapid development of the polymer resin industry has introduced a wide range of high-performance resins that show high compatibility with the graphitic surface of the CNTs. This research explores the computational design of these materials and evaluates their efficacy as the next generation of aerospace structural materials. Process-induced residual stresses are a commonly observed phenomenon in composite structures during the manufacturing process. These are generated because of resin shrinkage and relative thermal contraction between the resin and reinforcement during the curing process. Experimental or computational characterization of these stresses can be a challenge due to their complex nature. Predictive models of the curing process require detailed knowledge of the resin thermo-mechanical property evolution during the cure. Molecular Dynamics (MD) is implemented to predict the resin properties of EPON 828-Jeffamine D230 as a function of the crosslink density at room temperature. The molecular models are developed using the Reactive Interface Forcefield (IFF-R). The physical, mechanical, and thermal properties are validated experimentally and using the literature data. The predicted progression of resin properties indicates that each property evolves distinctively. The next generation of ultra-high strength composites for structural components of vehicles for crewed missions to deep space will incorporate flattened carbon nanotubes (flCNTs). With a wide range of high-performance polymers to choose from as the matrix component, efficient and accurate computational modeling can be used to efficiently down-select compatible resins, drive the design of these composites by predicting interface behavior, and provide critical physical insight into the flCNT/polymer interface. In this study, molecular dynamics simulation is used to predict the interaction energy, frictional sliding resistance, and mechanical binding of flCNT/polymer interfaces for a high-performance epoxy resin. The results, when compared to the sister studies, indicate that the BMI has stronger interfacial interaction and transverse tension binding with flCNT interfaces, while the benzoxazine demonstrates the strongest levels of interfacial friction resistance. Epoxy dwells in the “Goldilocks” zone with neither superior nor inferior properties. Comparison of these results indicate that BMI demonstrates the best overall compatibility with flCNTs for use in high-performance structural composites. One critical factor limiting the potential of carbon-based composites in aerospace applications is the poor load transferability between the reinforcement and the polymer matrix, which arises due to low interfacial shear strength at molecular scale. Molecular dynamics (MD) simulations have been employed in several studies that investigate the interface, such simulations are computationally expensive. To efficiently explore and optimize the interfacial design space with the goal of improving the mechanical performance, it is important to develop a machine learning (ML) approach that can be used to assist in the identification of optimal combinations of interface variables. In this study, a MD-ML workflow is proposed to predict optimal functionalization strategies for a bismaleimide (BMI) and three-layer graphene nanoplatelet (GNP) nanocomposite with maximized interfacial shear strength. In turn, these predictions of pull-out force will be used to identify optimal surface functionalizations that maximize the pull-out force. The details on the MD modeling and training data generation for the ML model are discussed in this work

Numerical modelling of non-ionic microgels: an overview

Microgels are complex macromolecules. These colloid-sized polymer networks possess internal degrees of freedom and, depending on the polymer(s) they are made of, can acquire a responsiveness to variations of the environment (temperature, pH, salt concentration, etc.). Besides being valuable for many practical applications, microgels are also extremely important to tackle fundamental physics problems. As a result, these last years have seen a rapid development of protocols for the synthesis of microgels, and more and more research has been devoted to the investigation of their bulk properties. However, from a numerical standpoint the picture is more fragmented, as the inherently multi-scale nature of microgels, whose bulk behaviour crucially depends on the microscopic details, cannot be handled at a single level of coarse-graining. Here we present an overview of the methods and models that have been proposed to describe non-ionic microgels at different length-scales, from the atomistic to the single-particle level. We especially focus on monomer-resolved models, as these have the right level of details to capture the most important properties of microgels, responsiveness and softness. We suggest that these microscopic descriptions, if realistic enough, can be employed as starting points to develop the more coarse-grained representations required to investigate the behaviour of bulk suspensions

Computational Molecular Design Using Tabu Search

The focus of this project is the use of computational molecular design (CMD) in the design of novel crosslinked polymers. A design example was completed for a dimethacrylate as part of a comonomer used in dental restoration, with the goal to create a dental adhesive with a longer clinical lifetime than those already on the market. The CMD methodology begins with the calculation of molecular descriptors that describe the crosslinked polymer structure. Connectivity index are used as the primary set of descriptors, and have been used successfully in other CMD projects. Quantitative structure property relationships (QSPRs) were developed relating the structural descriptors to the experimentally collected property data. Models were chosen using Mallows' Cp with correlation coefficient significance. Desirable target property values were chosen which lead to an improved clinical lifetime. Structural constraints were defined to increase stability and ease of synthesis. The Tabu Search optimization algorithm was used to design polymers with desirable properties. Finally, a prediction interval was calculated for each candidate to represent the possible error in the predicted properties. The described methodology provides a list of candidate monomers with predicted properties near the desired target values, which are selected such that the adhesives will show improved propertoes relative to the standard HEMA/BisGMA formulation. The methodology can be easily altered to allow for additional property calculations and structural constraints. This methodology can also be used for molecular design projects beyond crosslinked polymers

Molecular Dynamics Simulations of Neat Vinyl Ester and Vapor-Grown Carbon Nanofiber/Vinyl Ester Resin Composites

Molecular dynamics (MD) simulations have been performed to investigate the system equilibrium through the atomic/molecular interactions of a liquid vinyl ester (VE) thermoset resin with the idealized surfaces of both pristine vapor-grown carbon nanofibers (VGCNFs) and oxidized VGCNFs. The VE resin has a mole ratio of styrene to bisphenol-A-diglycidyl dimethacrylate VE monomers consistent with a commercially available 33 wt% styrene VE resin (Derakane 441-400). The VGCNF-VE resin interactions may influence the distribution of the liquid VE monomers in the system and the formation of an interphase region. Such an interphase may possess a different mole ratio of VE resin monomers at the vicinity of the VGCNF surfaces compared to the rest of the system after resin curing. Bulk nano-reinforced material properties are highly dependent on the interphase features because of the high surface area to volume ratio of nano-reinforcements. For example, higher length scale micromechanical calculations suggest that the volume fraction and properties of the interphase can have a profound effect on bulk material properties. Interphase formation, microstructure, geometries, and properties in VGCNF-reinforced polymeric composites have not been well characterized experimentally, largely due to the small size of typical nano-reinforcements and interphases. Therefore, MD simulations offer an alternative means to probe the nano-sized formation of the interphase and to determine its properties, without having to perform fine-scale experiments. A robust crosslinking algorithm for VE resin was then developed as a key element of this research. VE resins are crosslinked via free radical copolymerization account for regioselectivity and monomer reactivity ratios. After the VE crosslinked network was created, the constitutive properties of the resin were calculated. This algorithm will be used to crosslink equilibrated VE resin systems containing both pristine and oxidized VGCNFs. An understanding of formation and kinematics of a crosslinked network obtained via MD simulations can facilitate nanomaterials design and can reduce the amount of nanocomposite experiments required. VGCNF pull-out simulations will then be performed to determine the interfacial shear strength between VGCNFs and the matrix. Interphase formation, thickness and interfacial shear strength can directly feed into higher length scale micromechanical models within a global multiscale analysis framework

From Experimental Studies to Coarse-Grained Modeling: Characterization of Surface Area to Volume Ratio Effects on the Swelling of Poly (Ethylene Glycol) Dimethacrylate Hydrogels

Understanding the performance of widely applied nanoscale hydrogel biomaterials is an unmet need within the biomedical field. The objective of this master’s thesis project was to evaluate the effects size and surface area has on the in vivo behavior of nanoscale hydrogels. The hypothesis tested was that at the nanoscale, the increased surface area to volume effects of nanoscale hydrogels play and important role in the overall swelling of hydrogels, such that nanoscale hydrogels swell to a greater degree than their bulk counterparts. To investigate this, the bulk swelling behavior of a series of neutral poly (ethylene glycol) di-methacrylate (PEGDMA) hydrogels was experimentally tested. Along with experimental studies, a computational model based on the experimental findings was developed to serve as a means of predicting nanoscale swelling and subsequent drug release behavior. The computational hydrogel model was validated with the experimental densities and swelling ratios calculated. The surfaces of swollen hydrogels had a density gradient until reaching a stabilized, core density. As the size of the hydrogel decreases, the surface area to volume ratio increases, which enhances surface effects for micro- and nanoscale hydrogels. This conclusion helps to confirm the hypothesis that the increased surface area to volume ratio of nanoscale hydrogels affects the overall swelling ratio in comparison to their bulk counter parts. Particle size should be considered when characterizing nanoscale hydrogels. In this thesis, a computational hydrogel model capable of simulating hydrogel swelling for hydrogels with a dry state diameter of 40 nm was created. In the future, this model would ideally be able to simulate hydrogels with a dry state diameter ≥ 100 nm to test the full range of nanoscale size effects on hydrogel swelling

Molecular Design of Crosslinked Copolymers

A complete methodology for the computational molecular design (CMD) of crosslinked polymers is developed and implemented. The methodology is applied to the design of novel polymers for restorative dental materials. The computational molecular design of crosslinked polymers using optimization techniques is a new area of research. The first part of this project seeks to develop a novel data structure capable of adequately storing a complete description of the crosslinked polymer structure. Numerical descriptors of polymer structure are then calculated from the data structure. Statistical methods are used to relate the structural descriptors to experimentally measured properties. An important part of this project is to show that useful property prediction models can be developed for crosslinked polymers. Desirable property target values are then set for a specific application. Finally, the structure-property relations are combined with a Tabu search optimization algorithm to design improved polymers. Tabu search allows much flexibility in the problem formulations, so a major goal of this project is to show that Tabu search is a effective method for crosslinked polymer design. To implement the molecular design procedure, a software package is developed. The software allows for easy graphical entry of polymer structures and property data, and contains a Tabu search optimization routine. Since computational molecular design of crosslinked polymers is a relatively new area of research, the software is designed to be easily modified to allow for extensive numerical experimentation. Finally, the computational design methodology is demonstrated for the design of polymers for restorative dental applications. Using the computational molecular design methodology developed in this project, several monomers are found that may offer a significant improvement over a standard HEMA/bisGMA formulation. The results of the case study show that the new data structure for crosslinked polymers is effective for calculation of topological descriptors and roperty models can be developed for crosslinked polymers. Tabu search is also shown to be an effective optimization method