Controlled patterning of crystalline domains by frontal polymerization.

Materials with hierarchical architectures that combine soft and hard material domains with coalesced interfaces possess superior properties compared with their homogeneous counterparts1-4. These architectures in synthetic materials have been achieved through deterministic manufacturing strategies such as 3D printing, which require an a priori design and active intervention throughout the process to achieve architectures spanning multiple length scales5-9. Here we harness frontal polymerization spin mode dynamics to autonomously fabricate patterned crystalline domains in poly(cyclooctadiene) with multiscale organization. This rapid, dissipative processing method leads to the formation of amorphous and semi-crystalline domains emerging from the internal interfaces generated between the solid polymer and the propagating cure front. The size, spacing and arrangement of the domains are controlled by the interplay between the reaction kinetics, thermochemistry and boundary conditions. Small perturbations in the fabrication conditions reproducibly lead to remarkable changes in the patterned microstructure and the resulting strength, elastic modulus and toughness of the polymer. This ability to control mechanical properties and performance solely through the initial conditions and the mode of front propagation represents a marked advancement in the design and manufacturing of advanced multiscale materials.

Frontal Polymerizations: From Chemical Perspectives to Macroscopic Properties and Applications.

The synthesis and processing of most thermoplastics and thermoset polymeric materials rely on energy-inefficient and environmentally burdensome manufacturing methods. Frontal polymerization is an attractive, scalable alternative due to its exploitation of polymerization heat that is generally wasted and unutilized. The only external energy needed for frontal polymerization is an initial thermal (or photo) stimulus that locally ignites the reaction. The subsequent reaction exothermicity provides local heating; the transport of this thermal energy to neighboring monomers in either a liquid or gel-like state results in a self-perpetuating reaction zone that provides fully cured thermosets and thermoplastics. Propagation of this polymerization front continues through the unreacted monomer media until either all reactants are consumed or sufficient heat loss stalls further reaction. Several different polymerization mechanisms support frontal processes, including free-radical, cat- or anionic, amine-cure epoxides, and ring-opening metathesis polymerization. The choice of monomer, initiator/catalyst, and additives dictates how fast the polymer front traverses the reactant medium, as well as the maximum temperature achievable. Numerous applications of frontally generated materials exist, ranging from porous substrate reinforcement to fabrication of patterned composites. In this review, we examine in detail the physical and chemical phenomena that govern frontal polymerization, as well as outline the existing applications.

Rapid energy-efficient manufacturing of polymers and composites via frontal polymerization.

Thermoset polymers and composite materials are integral to today's aerospace, automotive, marine and energy industries and will be vital to the next generation of lightweight, energy-efficient structures in these enterprises, owing to their excellent specific stiffness and strength, thermal stability and chemical resistance1-5. The manufacture of high-performance thermoset components requires the monomer to be cured at high temperatures (around 180 °C) for several hours, under a combined external pressure and internal vacuum 6 . Curing is generally accomplished using large autoclaves or ovens that scale in size with the component. Hence this traditional curing approach is slow, requires a large amount of energy and involves substantial capital investment6,7. Frontal polymerization is a promising alternative curing strategy, in which a self-propagating exothermic reaction wave transforms liquid monomers to fully cured polymers. We report here the frontal polymerization of a high-performance thermoset polymer that allows the rapid fabrication of parts with microscale features, three-dimensional printed structures and carbon-fibre-reinforced polymer composites. Precise control of the polymerization kinetics at both ambient and elevated temperatures allows stable monomer solutions to transform into fully cured polymers within seconds, reducing energy requirements and cure times by several orders of magnitude compared with conventional oven or autoclave curing approaches. The resulting polymer and composite parts possess similar mechanical properties to those cured conventionally. This curing strategy greatly improves the efficiency of manufacturing of high-performance polymers and composites, and is widely applicable to many industries.

Anisotropic frontal polymerization in a model resin-copper composite.

This work investigates experimentally and numerically frontal polymerization in a thermally anisotropic system with parallel copper strips embedded in 1,6-hexanediol diacrylate resin. Both experiments and multiphysics finite element analyses reveal that the front propagation in the thermally anisotropic system is orientation-dependent, leading to variations in the front shape and the front velocity due to the different front-metal strip interaction mechanisms along and across the metal strips. The parameters entering the cure kinetics model used in this work are chosen to capture the key characteristics of the polymerization front, i.e., the front temperature and velocity. Numerical parametric analyses demonstrate that the front velocity in the directions parallel and perpendicular to the metal strips increases as the system size decreases and approaches the analytical prediction for homogenized systems. A two-dimensional homogenized model for anisotropic frontal polymerization in the metal-resin system is proposed.

Controllable Frontal Polymerization and Spontaneous Patterning Enabled by Phase-Changing Particles.

Frontal polymerization provides a rapid, economic, and environmentally friendly methodology to manufacture thermoset polymers and composites. Despite its efficiency and reduced environmental impact, the manufacturing method is underutilized due to the limited fundamental understanding of its dynamic control. This work reports the control and patterning of the front propagation in a dicyclopentadiene resin by immersion of phase-changing polycaprolactone particles. Predictive and designed patterning is enabled by multiphysical numerical analyses, which reveal that the interplay between endothermic phase transition, exothermic chemical reaction, and heat exchange govern the temperature, velocity, and propagation path of the front via two different interaction regimes. To pattern the front, one can vary the size and spacing between the particles and increase the number of propagating fronts, resulting in tunable physical patterns formed due to front separation and merging near the particles. Both single- and double-frontal polymerization experiments in an open mold are performed. The results confirm the front-particle interaction mechanisms and the shapes of the patterns explored numerically. The present study offers a fundamental understanding of frontal polymerization in the presence of heat-absorbing second-phase materials and proposes a potential one-step manufacturing method for precisely patterned polymeric and composite materials without masks, molds, or printers.

Rapid frontal polymerization achieved with thermally conductive metal strips.

Frontal polymerization, which involves a self-propagating polymerizing reaction front, has been considered as a rapid, energy-efficient, and environmentally friendly methodology to manufacture lightweight, high-performance thermoset polymers, and composites. Previous work has reported that the introduction of thermally conductive elements can enhance the front velocity. As follow-up research, the present work investigates this problem more systemically using both numerical and experimental approaches by investigating the front shape, front width, and heat exchange when aluminum and cooper metal strips are embedded in the resin. The study reveals that the enhancement in the front velocity is mainly due to a preheating effect associated with the conductive element. Moreover, the numerical parametric study for the system size shows that the front speed increases as the system size decreases, ultimately approaching a prediction provided by a homogenized model for polymer-metal composites.

Interplay between Process Zone and Material Heterogeneities for Dynamic Cracks.

Using an elastodynamic boundary integral formulation coupled with a cohesive model, we study the problem of a dynamic rupture front propagating along an heterogeneous plane. We show that small-scale heterogeneities facilitate the supershear transition of a mode-II crack. The elastic pulses radiated during front accelerations explain how microscopic variations of fracture toughness change the macroscopic rupture dynamics. Perturbations of dynamic fronts are then systematically studied with different microstructures and loading conditions. The process zone size is the intrinsic length scale controlling heterogeneous dynamic rupture. The ratio of this length scale to asperity size is proposed as an indicator to transition from quasihomogeneous to heterogeneous fracture. Moreover, we discuss how the shortening of the process zone size with increasing crack speed brings the front to interact with smaller details of the microstructure. This study shines new light on recent experiments reporting perturbations of dynamic rupture fronts, which intensify with crack propagation speed.

Molecular tailoring of interfacial failure.

Self-assembled monolayers (SAMs) provide an enabling platform for molecular tailoring of the chemical and physical properties of an interface. In this work, we systematically vary SAM end-group functionality and quantify the corresponding effect on interfacial failure between a transfer printed gold (Au) film and a fused silica substrate. SAMs with four different end groups are investigated: 11-amino-undecyltriethoxysilane (ATES), dodecyltriethoxysilane (DTES), 11-bromo-undecyltrimethoxysilane (BrUTMS), and 11-mercapto-undecyltrimethoxysilane (MUTMS). In addition to these four end groups, mixed monolayers of increasing molar ratio of MUTMS to DTES in solution are investigated. The failure of each SAM-mediated interface is initiated by a noncontact laser-induced spallation method at strain rates in excess of 10(6) s(-1). By making multiple measurements at increasing stress amplitudes (controlled by the laser fluence), we measure interface strengths of 19 ± 1.7, 20 ± 1.3, 52 ± 5.4, and 80 ± 6.5 MPa for interfaces functionalized with ATES, DTES, BrUTMS, and MUTMS, respectively. The interface strength is effectively tuned between the low strength of DTES and the high strength of MUTMS by controlling the concentration of MUTMS in solution. X-ray photoelectron spectroscopy of the failed interfaces reveals the influence of end group functionality on molecular dissociation, which significantly alters the failure process.

Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene.

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. In this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

Spontaneous Patterning during Frontal Polymerization.

Complex patterns integral to the structure and function of biological materials arise spontaneously during morphogenesis. In contrast, functional patterns in synthetic materials are typically created through multistep manufacturing processes, limiting accessibility to spatially varying materials systems. Here, we harness rapid reaction-thermal transport during frontal polymerization to drive the emergence of spatially varying patterns during the synthesis of engineering polymers. Tuning of the reaction kinetics and thermal transport enables internal feedback control over thermal gradients to spontaneously pattern morphological, chemical, optical, and mechanical properties of structural materials. We achieve patterned regions with two orders of magnitude change in modulus in poly(cyclooctadiene) and 20 °C change in glass transition temperature in poly(dicyclopentadiene). Our results suggest a facile route to patterned structural materials with complex microstructures without the need for masks, molds, or printers utilized in conventional manufacturing. Moreover, we envision that more sophisticated control of reaction-transport driven fronts may enable spontaneous growth of structures and patterns in synthetic materials, inaccessible by traditional manufacturing approaches.

Rapid synchronized fabrication of vascularized thermosets and composites.

Bioinspired vascular networks transport heat and mass in hydrogels, microfluidic devices, self-healing and self-cooling structures, filters, and flow batteries. Lengthy, multistep fabrication processes involving solvents, external heat, and vacuum hinder large-scale application of vascular networks in structural materials. Here, we report the rapid (seconds to minutes), scalable, and synchronized fabrication of vascular thermosets and fiber-reinforced composites under ambient conditions. The exothermic frontal polymerization (FP) of a liquid or gelled resin facilitates coordinated depolymerization of an embedded sacrificial template to create host structures with high-fidelity interconnected microchannels. The chemical energy released during matrix polymerization eliminates the need for a sustained external heat source and greatly reduces external energy consumption for processing. Programming the rate of depolymerization of the sacrificial thermoplastic to match the kinetics of FP has the potential to significantly expedite the fabrication of vascular structures with extended lifetimes, microreactors, and imaging phantoms for understanding capillary flow in biological systems.

Manipulating Frontal Polymerization and Instabilities with Phase-Changing Microparticles.

Recently presented as a rapid and eco-friendly manufacturing method for thermoset polymers and composites, frontal polymerization (FP) experiences thermo-chemical instabilities under certain conditions, leading to visible patterns and spatially dependent material properties. Through numerical analyses and experiments, we demonstrate how the front velocity, temperature, and instability in the frontal polymerization of cyclooctadiene are affected by the presence of poly(caprolactone) microparticles homogeneously mixed with the resin. The phase transformation associated with the melting of the microparticles absorbs some of the exothermic reaction energy generated by the FP, reduces the amplitude and order of the thermal instabilities, and suppresses the front velocity and temperatures. Experimental measurements validate predictions of the dependence of the front velocity and temperature on the microparticle volume fraction provided by the proposed homogenized reaction-diffusion model.

ChemNet: A Deep Neural Network for Advanced Composites Manufacturing.

Among advanced manufacturing techniques for fiber-reinforced polymer-matrix composites (FRPCs) which are critical for aerospace, marine, automotive, and energy industries, frontal polymerization (FP) has been recently proposed to save orders of magnitude of time and energy. However, the cure kinetics of the matrix phase, usually a thermosetting polymer, brings difficulty to the design and control of the process. Here, we develop a deep learning model, ChemNet, to solve an inverse problem for predicting and optimizing the cure kinetics parameters of the thermosetting FRPCs for a desired fabrication strategy. ChemNet consists of a fully connected FeedForward 9 layer deep neural network trained on one million examples, and predicts activation energy and reaction enthalpy given the front characteristics such as speed and maximum temperature. ChemNet provides highly accurate predictions measured by the mean squared error (MSE) and by the maximum absolute error (MAE) metrics. ChemNet's performance on the "hidden" test data set had an MSE of 5.58 × 10-6 and a MAE of 1 × 10-3.

Frontal Polymerization of Dicyclopentadiene: A Numerical Study.

As frontal polymerization is being considered as a faster and more energy efficient manufacturing technique for polymer-matrix fiber-reinforced composites, we perform a finite-element-based numerical study of the initiation and propagation of a polymerization front in dicyclopentadiene (DCPD). The transient thermochemical simulations are complemented by an analytical study of the steady-state propagation of the polymerization front, allowing to draw a direct link between the cure kinetics model and the key characteristics of the front, i.e., front velocity and characteristic length scales. The second part of this study focuses on the prediction of the temperature spike associated with the merger of two polymerization fronts. The thermal peak, which might be detrimental to the properties of the polymerized material, is due to the inability of the heat associated with the highly exothermic reaction to be dissipated when the two fronts merge. The analysis investigates how the amplitude of the thermal spike is affected by the degree of cure at the time of the front merger.

Wave tailoring by precompression in confined granular systems.

We present a granular system whose response under an impact load can be varied from rapidly decaying to almost constant amplitude waves by an external regulator. The system consists of a granular chain of larger spheres surrounded by small spheres, confined in a hollow cylindrical tube and supporting wave propagation along the axis of the cylinder. We demonstrate using numerical simulations that the response can be controlled by applying radial precompression. These observations are then complemented by an asymptotic analysis, which shows that the decay in the leading wave is due to energy leakage to the oscillating small beads in the tail of the wave. This system has potential applications in systems requiring tuning of elastic waves.

Family of plane solitary waves in dimer granular crystals.

Uniform planar impact on a two-dimensional square packing of spheres with intruders at interstitial locations is investigated. An equivalent one-dimensional granular chain model is proposed with appropriate scaling and is verified numerically. Numerical observations demonstrate the existence of a new family of plane solitary waves with different profiles at unique combinations of material properties. In particular, a special case of a solitary wave whose profile is similar to that of the homogeneous chains is also reported. Material combinations that cause solitary waves are systematically extracted for a wide range of material properties. For the solitary wave similar to that of a homogeneous chain, a quasicontinuum approximation is employed to predict the shape and width of the solitary wave, showing good agreement with the numerical results. Finally, an asymptotic analysis is conducted to predict the solitary wave solutions.

Characterization of wave propagation in elastic and elastoplastic granular chains.

For short duration impulse loadings, elastic granular chains are known to support solitary waves, while elastoplastic chains have recently been shown to exhibit two force decay regimes [ Pal, Awasthi and Geubelle Granular Matter 15 747 (2013)]. In this work, the dynamics of monodisperse elastic and elastoplastic granular chains under a wide range of loading conditions is studied, and two distinct response regimes are identified in each of them. In elastic chains, a short loading duration leads to a single solitary wave propagating down the chain, while a long loading duration leads to the formation of a train of solitary waves. A simple model is developed to predict the peak force and wave velocity for any loading duration and amplitude. In elastoplastic chains, wave trains form even for short loading times due to a mechanism distinct from that in elastic chains. A model based on energy balance predicts the decay rate and transition point between the two decay regimes. For long loading durations, loading and unloading waves propagate along the chain, and a model is developed to predict the contact force and particle velocity.

Interfacial adhesive properties between a rigid-rod pyromellitimide molecular layer and a covalent semiconductor via atomistic simulations.

We conducted a comprehensive atomistic simulation study of the adhesive properties of aromatic rigid-rod poly-[(4,4'diphenylene) pyromellitimide] on a dimer-reconstructed silicon surface. We describe the structural developments within the adherent's interfacial region at the atomistic scale, and evaluate the energetics of the adhesive interactions between bimaterial constituents. In particular, we observe a transition between noncontact and contact adhesion regimes as a function of the interfacial bonding strength between the polyimide repeat units and the silicon substrate. This transition is manifest by a three- to four-fold increase in adhesive energy, which is entirely attributable to structural relaxation in the organic layer near the interface, revealing the importance of accurately describing structural details at interfaces for reliable interfacial strength predictions. The underlying molecular reconfigurations in the pyromellitimide layer include preferred orientation of the rigid-rod molecules, molecular stacking, ordering, and the local densification. The role of each of these factors in the adhesive behavior is analyzed and conclusively described. Where possible, simulation results are compared with theoretical model predictions or experimental data.

Wave propagation in random granular chains.

The influence of randomness on wave propagation in one-dimensional chains of spherical granular media is investigated. The interaction between the elastic spheres is modeled using the classical Hertzian contact law. Randomness is introduced in the discrete model using random distributions of particle mass, Young's modulus, or radius. Of particular interest in this study is the quantification of the attenuation in the amplitude of the impulse associated with various levels of randomness: two distinct regimes of decay are observed, characterized by an exponential or a power law, respectively. The responses are normalized to represent a vast array of material parameters and impact conditions. The virial theorem is applied to investigate the transfer from potential to kinetic energy components in the system for different levels of randomness. The level of attenuation in the two decay regimes is compared for the three different sources of randomness and it is found that randomness in radius leads to the maximum rate of decay in the exponential regime of wave propagation.