Chemical Reactions in Classical Molecular Dynamics

Topological Programmability of Isomerizable Polymers

Topology isomerizable networks (TINs) can be programmed into numerous polymers exhibiting unique and spatially defined (thermo-) mechanical properties. However, capturing the dynamics in topological transformations and revealing the intrinsic mechanisms of mechanical property modulation at the microscopic level is a significant challenge. Here, we use a combination of coarse-grained molecular dynamics simulations and reaction kinetic theory to reveal the impact of dynamic bond exchange reactions on the topology of branched chains. We find that, the grafted units follow a geometric distribution with a converged uniformity, which depends solely on the average grafted units of branched chains. Furthermore, we demonstrate that the topological structure can lead to spontaneous modulation of mechanical properties. The theoretical framework provides a research paradigm for studying the topology and mechanical properties of TINs.

Fracture of Epoxy Networks Using Atomistic Simulations

Predicting fracture properties through all-atomistic simulations poses challenges due to classical force field limitations in breaking covalent bonds and the computational demands of reactive force fields like ReaxFF. In addressing this, we propose a scale-bridging method for forecasting the fracture behavior of highly cross-linked epoxy combining classical force fields, the LAMMPS package REACTER, and for bond breaking a parameter based on experimental distance criterion. In our analysis, we anticipate the macroscopic fracture energy GC of the epoxy network through the application of a continuum fracture mechanics model developed for fibrils. In addition, we extract the value of the stress intensity factor KI. This modeling approach is specifically implemented for a frequently used epoxy system that consists of bisphenol F and DETDA hardener. Notably, our results demonstrate a robust correlation with existing literature and experimental studies. Moreover, our approach boasts a substantial computational time advantage, facilitating calculations that are significantly faster compared to those performed using reactive force fields.

LUNAR: Automated Input Generation and Analysis for Reactive LAMMPS Simulations

Generating simulation-ready molecular models for the LAMMPS molecular dynamics (MD) simulation software package is a difficult task and impedes the more widespread and efficient use of MD in materials design and development. Fixed-bond force fields generally require manual assignment of atom types, bonded interactions, charges, and simulation domain sizes. A new LAMMPS pre- and postprocessing toolkit (LUNAR) is presented that efficiently builds molecular systems for LAMMPS. LUNAR automatically assigns atom types, generates bonded interactions, assigns charges, and provides initial configuration methods to generate large molecular systems. LUNAR can also incorporate chemical reactivity into simulations by facilitating the use of the REACTER protocol. Additionally, LUNAR provides postprocessing for free volume calculations, cure characterization calculations, and property predictions from LAMMPS thermodynamic outputs. LUNAR has been validated via building and simulation of pure epoxy and cyanate ester polymer systems with a comparison of the corresponding predicted structures and properties to benchmark values, including experimental results from the literature. LUNAR provides the tools for the computationally driven development of next-generation composite materials in the Integrated Computational Materials Engineering (ICME) and Materials Genome Initiative (MGI) frameworks. LUNAR is written in Python with the usage of NumPy and can be used via a graphical user interface, a command line interface, or an integrated design environment. LUNAR is freely available via GitHub.

Molecular Dynamics Simulation of Silicone Oil Polymerization from Combined QM/MM Modeling

We outline a molecular simulation protocol for elucidating the formation of silicone oil from trimethlyl- and dimethlysilanediole precursor mixtures. While the fundamental condensation reactions are effectively described by quantum mechanical calculations, this is combined with molecular mechanics models in order to assess the extended relaxation processes. Within a small series of different precursor mixtures used as starting points, we demonstrate the evolution of the curing degree and heat formation in the course of polymer chain growth. Despite the increasing complexity of the amorphous agglomerate of polymer chains, our approach shows an appealing performance for tackling both elastic and viscous relaxation. Indeed, the finally obtained polymer systems feature 99% curing and thus offer realistic insights into the growth mechanisms of coexisting/competing polymer strands.

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.

Phase patterning of liquid crystal elastomers by laser-induced dynamic crosslinking

Liquid crystal elastomers hold promise in various fields due to their reversible transition of mechanical and optical properties across distinct phases. However, the lack of local phase patterning techniques and irreversible phase programming has hindered their broad implementation. Here we introduce laser-induced dynamic crosslinking, which leverages the precision and control offered by laser technology to achieve high-resolution multilevel patterning and transmittance modulation. Incorporation of allyl sulfide groups enables adaptive liquid crystal elastomers that can be reconfigured into desired phases or complex patterns. Laser-induced dynamic crosslinking is compatible with existing processing methods and allows the generation of thermo- and strain-responsive patterns that include isotropic, polydomain and monodomain phases within a single liquid crystal elastomer film. We show temporary information encryption at body temperature, expanding the functionality of liquid crystal elastomer devices in wearable applications.

Trade-off between Endocrine-Disrupting Compound Removal and Water Permeance of the Polyamide Nanofiltration Membrane: Phenomenon and Molecular Insights

The polyamide (PA) nanofiltration (NF) membrane has the potential to remove endocrine-disrupting compounds (EDCs) from water and wastewater to prevent risks to both the aquatic ecosystem and human health. However, our understanding of the EDC removal-water permeance trade-off by the PA NF membrane is still limited, although the salt selectivity-water permeance trade-off has been well illustrated. This constrains the precise design of a high-performance membrane for removing EDCs. In this study, we manipulated the PA nanostructures of NF membranes by altering piperazine (PIP) monomer concentrations during the interfacial polymerization (IP) process. The upper bound coefficient for EDC selectivity-water permeance was demonstrated to be more than two magnitudes lower than that for salt selectivity-water permeance. Such variations were derived from the different membrane-solute interactions, in which the water/EDC selectivity was determined by the combined effects of steric exclusion and the hydrophobic interaction, while the electrostatic interaction and steric exclusion played crucial roles in water/salt selectivity. We further highlighted the role of the pore number and residual groups during the transport of EDC molecules across the PA membrane via molecular dynamics (MD) simulations. Fewer pores decreased the transport channels, and the existence of residual groups might cause steric hindrance and dynamic disturbance to EDC transport inside the membrane. This study elucidated the trade-off phenomenon and mechanisms between EDC selectivity and water permeance, providing a theoretical reference for the precise design of PA NF membranes for effective removal of EDCs in water reuse.

Molecular Simulation of Covalent Adaptable Networks and Vitrimers: A Review

Covalent adaptable networks and vitrimers are novel polymers with dynamic reversible bond exchange reactions for crosslinks, enabling them to modulate their properties between those of thermoplastics and thermosets. They have been gathering interest as materials for their recycling and self-healing properties. In this review, we discuss different molecular simulation efforts that have been used over the last decade to investigate and understand the nanoscale and molecular behaviors of covalent adaptable networks and vitrimers. In particular, molecular dynamics, Monte Carlo, and a hybrid of molecular dynamics and Monte Carlo approaches have been used to model the dynamic bond exchange reaction, which is the main mechanism of interest since it controls both the mechanical and rheological behaviors. The molecular simulation techniques presented yield sufficient results to investigate the structure and dynamics as well as the mechanical and rheological responses of such dynamic networks. The benefits of each method have been highlighted. The use of other tools such as theoretical models and machine learning has been included. We noticed, amongst the most prominent results, that stress relaxes as the bond exchange reaction happens, and that at temperatures higher than the glass transition temperature, the self-healing properties are better since more bond BERs are observed. The lifetime of dynamic covalent crosslinks follows, at moderate to high temperatures, an Arrhenius-like temperature dependence. We note the modeling of certain properties like the melt viscosity with glass transition temperature and the topology freezing transition temperature according to a behavior ruled by either the Williams-Landel-Ferry equation or the Arrhenius equation. Discrepancies between the behavior in dissociative and associative covalent adaptable networks are discussed. We conclude by stating which material parameters and atomistic factors, at the nanoscale, have not yet been taken into account and are lacking in the current literature.

Optimal Molecular Dynamics System Size for Increased Precision and Efficiency for Epoxy Materials

Molecular dynamics (MD) simulation is an important tool for predicting thermo-mechanical properties of polymer resins at the nanometer length scale, which is particularly important for efficient computationally driven design of advanced composite materials and structures. Because of the statistical nature of modeling amorphous materials on the nanometer length scale, multiple MD models (replicates) are typically built and simulated for statistical sampling of predicted properties. Larger replicates generally provide higher precision in the predictions but result in higher simulation times. Unfortunately, there is insufficient information in the literature to establish guidelines between MD model size and the resulting precision in predicted thermo-mechanical properties. The objective of this study was to determine the optimal MD model size of epoxy resin to balance efficiency and precision. The results show that an MD model size of 15,000 atoms provides for the fastest simulations without sacrificing precision in the prediction of mass density, elastic properties, strength, and thermal properties of epoxy. The results of this study are important for efficient computational process modeling and integrated computational materials engineering (ICME) for the design of next-generation composite materials for demanding applications.

Dynamic Insights into the Growth Mechanisms of 2D Covalent Organic Frameworks on Graphene Surfaces

Producing high-quality two-dimensional (2D) covalent organic frameworks (COFs) is crucial for industrial applications. However, this remains significantly challenging with current synthetic techniques. A deep understanding of the intermolecular interactions, reaction temperature, and oligomers is essential to facilitate the growth of highly crystalline COF films. Herein, molecular dynamics simulations were employed to explore the growth of 2D COFs from monomer assemblies on graphene. Our results showed that chain growth reactions dominated the COF surface growth and that van der Waals (vdW) interactions were important in enhancing the crystallinity through monomer preorganization. Moreover, appropriately tuning the reaction temperature improved the COF crystallinity and minimized the effects of amorphous oligomers. Additionally, the strength of the interface between the COF and the graphene substrate indicated that the adhesion force was proportional to the crystallinity of the COF. This work reveals the mechanisms for nucleation and growth of COFs on surfaces and provides theoretical guidance for fabricating high-quality 2D polymer-based crystalline nanomaterials.

Structure-Property Relationships of Granular Hybrid Hydrogels Formed through Polyelectrolyte Complexation

Hybrid hydrogels are hydrogels that exhibit heterogeneity in the network architecture by means of chemical composition and/or microstructure. The different types of interactions, together with structural heterogeneity, which can be created on different length scales, determine the mechanical properties of the final material to a large extent. In this work, the microstructure-mechanical property relationships for a hybrid hydrogel that contains both electrostatic and covalent interactions are investigated. The hybrid hydrogel is composed of a microphase-separated polyelectrolyte complex network (PEC) made of poly(4-styrenesulfonate) and poly(diallyldimethylammonium chloride) within a soft and elastic polyacrylamide hydrogel network. The system exhibits a granular structure, which is attributed to the liquid-liquid phase separation into complex coacervate droplets induced by the polymerization and the subsequent crowding effect of the polyacrylamide chains. The coacervate droplets are further hardened into PEC granules upon desalting the hydrogel. The structure formation is confirmed by a combination of electron microscopic imaging and molecular dynamics simulations. The interpenetration of both networks is shown to enhance the toughness of the resulting hydrogels due to the dissipative behavior of the PEC through the rupture of electrostatic interactions. Upon cyclic loading-unloading, the hydrogels show recovery of up to 80% of their original dissipative behavior in less than 300 s of rest with limited plasticity. The granular architecture and the tough and self-recoverable properties of the designed hybrid networks make them good candidates for applications, such as shape-memory materials, actuators, biological tissue mimics, and elastic substrates for soft sensors.

Type Label Framework for Bonded Force Fields in LAMMPS

New functionality is added to the LAMMPS molecular simulation package, which increases the versatility with which LAMMPS can interface with supporting software and manipulate information associated with bonded force fields. We introduce the "type label" framework that allows atom types and their higher-order interactions (bonds, angles, dihedrals, and impropers) to be represented in terms of the standard atom type strings of a bonded force field. Type labels increase the human readability of input files, enable bonded force fields to be supported by the OpenKIM repository, simplify the creation of reaction templates for the REACTER protocol, and increase compatibility with external visualization tools, such as VMD and OVITO. An introductory primer on the forms and use of bonded force fields is provided to motivate this new functionality and serve as an entry point for LAMMPS and OpenKIM users unfamiliar with bonded force fields. The type label framework has the potential to streamline modeling workflows that use LAMMPS by increasing the portability of software, files, and scripts for preprocessing, running, and postprocessing a molecular simulation.

Micromechanical Dilution of PLA/PETG-Glass/Iron Nanocomposites: A More Efficient Molecular Dynamics Approach

Polylactic acid (PLA) and poly(ethylene terephthalate glycol) (PETG) are popular thermoplastics used in additive manufacturing applications. The mechanical properties of PLA and PETG can be significantly improved by introducing fillers, such as glass and iron nanoparticles (NPs), into the polymer matrix. Molecular dynamics (MD) simulations with the reactive INTERFACE force field were used to predict the mechanical responses of neat PLA/PETG and PLA-glass/iron and PETG-glass/iron nanocomposites with relatively high loadings of glass/iron NPs. We found that the iron and glass NPs significantly increased the elastic moduli of the PLA matrix, while the PETG matrix exhibited modest increases in elastic moduli. This difference in reinforcement ability may be due to the slightly greater attraction between the glass/iron NP and PLA matrix. The NASA Multiscale Analysis Tool was used to predict the mechanical response across a range of volume percent glass/iron filler by using only the neat and highly loaded MD predictions as input. This provides a faster and more efficient approach than creating multiple MD models per volume percent per polymer/filler combination. To validate the micromechanics predictions, experimental samples incorporating hollow glass microspheres (MS) and carbonyl iron particles (CIP) into PLA/PETG were developed and tested for elastic modulus. The CIP produced a larger reinforcement in elastic modulus than the MS, with similar increases in elastic modulus between PLA/CIP and PETG/CIP at 7.77 vol % CIP. The micromechanics-based mechanical predictions compare excellently with the experimental values, validating the integrated micromechanical/MD simulation-based approach.

Noncovalent Interactions in Mechanical Response of Thermoset Epoxy Resin

Free volume in polymers is known to influence the mechanical response of the polymers. Noncovalent interactions such as hydrogen bonds, Coulombic electrostatic interactions, and van der Waals interactions are present within these free volume regions. The manuscript presents a comprehensive identification, characterization, and evolution of noncovalent interactions as a thermoset epoxy resin (typically used as an interfacial adhesive material) is subjected to uniaxial tension, shear, and shock loading. Even though noncovalent interactions dominate uniaxial tension and shear response (up to strain levels of 50% wherein covalent bond dissociation is not observed), both covalent and noncovalent interactions define response for shock loading. Van der Waals interactions dominate the response as the samples are subjected to strain levels of 50% in tension and shear. In contrast, hydrogen bonds influence shock response.

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.

Bottom-to-top modeling of epoxy resins: From atomic models to mesoscale fracture mechanisms

We outline a coarse-grained model of epoxy resins (bisphenol-F-diglycidyl-ether/3,5-diethyltoluene-2,4-diamine) to describe elastic and plastic deformation, cavitation, and fracture at the μm scale. For this, molecular scale simulation data collected from quantum and molecular mechanics studies are coarsened into an effective interaction potential featuring a single type of beads that mimic 100 nm scale building blocks of the material. Our model allows bridging the time-length scale problem toward experimental tensile testing, thus effectively reproducing the deformation and fracture characteristics observed for strain rates of 10-1 to 10-5 s-1. This paves the way to analyzing viscoelastic deformation, plastic behavior, and yielding characteristics by means of "post-atomistic" simulation models that retain the molecular mechanics of the underlying epoxy resin at length scales of 0.1-10 µm.

An elastomer with ultrahigh strain-induced crystallization

Strain-induced crystallization (SIC) prevalently strengthens, toughens, and enables an elastocaloric effect in elastomers. However, the crystallinity induced by mechanical stretching in common elastomers (e.g., natural rubber) is typically below 20%, and the stretchability plateaus due to trapped entanglements. We report a class of elastomers formed by end-linking and then deswelling star polymers with low defects and no trapped entanglements, which achieve strain-induced crystallinity of up to 50%. The deswollen end-linked star elastomer (DELSE) reaches an ultrahigh stretchability of 12.4 to 33.3, scaling beyond the saturated limit of common elastomers. The DELSE also exhibits a high fracture energy of 4.2 to 4.5 kJ m-2 while maintaining low hysteresis. The heightened SIC and stretchability synergistically promote a high elastocaloric effect with an adiabatic temperature change of 9.3°C.

Multiscale Process Modeling of Semicrystalline PEEK for Tailored Thermomechanical Properties

Polyether ether ketone (PEEK) is a semicrystalline thermoplastic that is used in high-performance composites for a wide range of applications. Because the crystalline phase has a higher mass density than that of the amorphous phase, the evolution of the crystalline phase during high-temperature annealing processing steps results in the formation of residual stresses and laminate deformations, which can adversely affect the composite laminate performance. Multiscale process modeling, utilizing molecular dynamics, micromechanics, and phenomenological PEEK crystal kinetic laws, is used to predict the evolution of volumetric shrinkage, elastic properties, and thermal properties, as a function of crystalline phase evolution, and thus annealing time, in the 306-328 °C temperature range. The results indicate that lower annealing temperatures in this range result in a faster evolution of thermomechanical properties and shrinkage toward the pure crystalline values. Therefore, from the perspective of composite processing, it may be more advantageous to choose the higher annealing rates in this range to slow the volumetric shrinkage and allow PEEK stress relaxation mechanisms more time to relax internal residual stresses in PEEK composite laminates and structures.

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.

Interfaces in reinforced epoxy resins: from molecular scale understanding towards mechanical properties

CONTEXT

We report on atomic level of detail analyses of polymer composite models featuring epoxy resin interfaces to silica, iron oxide, and cellulose layers. Using "reactive" molecular dynamics simulations to explore epoxy network formation, resin hardening is investigated in an unprejudiced manner. This allows the detailed characterization of salt-bridges and hydrogen bonds at the interfaces. Moreover, our sandwich-type composite systems are subjected to tensile testing along the interface normal. To elucidate the role of relaxation processes, we contrast (i) direct dissociation of the epoxy-metal oxide/cellulose contact layer, (ii) constant strain-rate molecular dynamics studies featuring (visco-)elastic deformation and bond rupture of the epoxy resin, and (iii) extrapolated relaxation dynamics mimicking quasi-static conditions. While the fracture mechanism is clearly identified as interface dissociation of the composite constituents, we still find damaging of the nearby polymer phase. The observed plastic deformation and local cavitation are rationalized from the comparably large stress required for the dissociation of salt-bridges, hydrogen bonds, and van der Waals contacts. Indeed, the delamination of the contact layers of epoxy resins with slabs of silica, magnetite, and cellulose call for a maximum stress of 33, 26, and 21 MPa, respectively, as compared to 84 MPa required for bulk epoxy yielding.

METHODS

Molecular dynamics simulations using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code were augmented by a Monte Carlo-type procedure to probe epoxy bond formation (Macromolecules 53(22): 9698-9705). The underlying interaction models are split into conventional Generalized Amber Force Fields (GAFF) for non-reacting moieties and a recently developed reactive molecular mechanics potential enabling epoxy bond formation and cleavage (ACS Polymers Au 1(3): 165-174).

Mesoscale Simulation of Polymer Pyrolysis by Coarse-Grained Molecular Dynamics: A Parametric Study

Full comprehension of the pyrolysis of polymer materials is crucial for the design and application of thermal protection systems; however, it involves complex phenomena at different spatial and temporal scales. To bridge the gap between the abundant atomistic simulations and continuum modeling in the literature, we perform a novel mesoscale study of the pyrolysis process using coarse-grained molecular dynamics (CG MD) simulations. Polyethylene (PE) consisting of united atoms including implicit hydrogen is considered a model polymer, and the configurational change of PE in thermal degradation is modeled by applying the bond-breaking phenomenon based on bond energy or bond length criteria. A cook-off simulation is implemented to optimize the heuristic protocol of bond dissociation by comparing the reaction products with a ReaxFF simulation. The aerobic hyperthermal pyrolysis under oxygen bombardment is simulated at a large scale of hundreds of nanometers to observe the intricate phenomena occurring from the surface to the depth inside the material. The intrinsic thermal durability of the model polymer at extreme conditions with and without oxygen environment can be effectively simulated from the proposed mesoscale simulation to predict important thermal degradation properties required for continuum-scale pyrolysis and ablation simulations. This work serves as an initial investigation of polymer pyrolysis at the mesoscale and helps understand the concept at a larger scale.

Reaction mechanism - explored with the unified reaction valley approach

One of the ultimate goals of chemistry is to understand and manipulate chemical reactions, which implies the ability to monitor the reaction and its underlying mechanism at an atomic scale. In this article, we introduce the Unified Reaction Valley Approach (URVA) as a tool for elucidating reaction mechanisms, complementing existing computational procedures. URVA combines the concept of the potential energy surface with vibrational spectroscopy and describes a chemical reaction via the reaction path and the surrounding reaction valley traced out by the reacting species on the potential energy surface on their way from the entrance to the exit channel, where the products are located. The key feature of URVA is the focus on the curving of the reaction path. Moving along the reaction path, any electronic structure change of the reacting species is registered by a change in the normal vibrational modes spanning the reaction valley and their coupling with the path, which recovers the curvature of the reaction path. This leads to a unique curvature profile for each chemical reaction, with curvature minima reflecting minimal change and curvature maxima indicating the location of important chemical events such as bond breaking/formation, charge polarization and transfer, rehybridization, etc. A decomposition of the path curvature into internal coordinate components or other coordinates of relevance for the reaction under consideration, provides comprehensive insight into the origin of the chemical changes taking place. After giving an overview of current experimental and computational efforts to gain insight into the mechanism of a chemical reaction and presenting the theoretical background of URVA, we illustrate how URVA works for three diverse processes, (i) [1,3] hydrogen transfer reactions; (ii) α-keto-amino inhibitor for SARS-CoV-2 Mpro; (iii) Rh-catalyzed cyanation. We hope that this article will inspire our computational colleagues to add URVA to their repertoire and will serve as an incubator for new reaction mechanisms to be studied in collaboration with our experimental experts in the field.

Coarse-Grained Modeling of Polymer Cleavage within a Porous Catalytic Support

The chemical upcycling of plastic waste to valuable liquid products requires catalytic cleavage architectures that afford control over the resulting product distributions. Recently, a catalyst was synthesized in which polymer chains are cleaved at the bottoms of pores to yield a narrow distribution of alkane products. An attractive feature of this architecture is the ability to modulate the product distribution by tuning physical parameters like the diameter of the pore. Understanding how such parameters affect product distributions is an important requirement of further synthetic improvements. We demonstrate that the pore diameter controls the products of the cleavage reaction via two distinct mechanisms. Our coarse-grained, particle-based simulations yield insight into the interplay of chain cleavage and pore residence times and show that the pore size can bias which bonds along a chain are cleaved.

Modeling of a two-stage polymerization considering glass fibre sizing using molecular dynamics

Fibre reinforced polymers are an important class of materials due to their light weight, high strength, and stiffness. However, there is a lack of knowledge about the interaction of fibre surface, sizing (fibre coating), and resin. Often only idealised academic systems are studied, and only rarely realistic systems that are used in an industrial context. Therefore, methods for studying the behaviour of complex sizing are highly desirable, especially as they play a crucial role in the performance of fibre reinforced polymers. Here, a simplified, yet industrially used resin system is extended using molecular dynamics simulations by adding a fibre surface and sizing layers. Furthermore, a common coupling agent was selected, and several additional assumptions were made about the structure of the sizing. Based on this, a systematic procedure for the development of a final cured system is introduced: a condensation reaction to form oligomers from coupling agent monomers is conducted. Subsequently, a two stage reaction, a polyurethane reaction and a radical polymerisation, is modelled based on an established approach. Using the final cured system, evaluations of averaged quantities during the reactions are carried out. Moreover, the system is evaluated along the normal direction of the fibre surface, which proves a spatial analysis of the fibre-sizing-resin interface.

Evaluation of Machine Learning Interatomic Potentials for the Properties of Gold Nanoparticles

We have investigated Machine Learning Interatomic Potentials in application to the properties of gold nanoparticles through the DeePMD package, using data generated with the ab-initio VASP program. Benchmarking was carried out on Au20 nanoclusters against ab-initio molecular dynamics simulations and show we can achieve similar accuracy with the machine learned potential at far reduced cost using LAMMPS. We have been able to reproduce structures and heat capacities of several isomeric forms. Comparison of our workflow with similar ML-IP studies is discussed and has identified areas for future improvement.

Simulating Polymerization by Boltzmann Inversion Force Field Approach and Dynamical Nonequilibrium Reactive Molecular Dynamics

The radical polymerization process of acrylate compounds is, nowadays, numerically investigated using classical force fields and reactive molecular dynamics, with the aim to probe the gel-point transition as a function of the initial radical concentration. In the present paper, the gel-point transition of the 1,6-hexanediol dimethacrylate (HDDMA) is investigated by a coarser force field which grants a reduction in the computational costs, thereby allowing the simulation of larger system sizes and smaller radical concentrations. Hence, the polymerization is investigated using reactive classical molecular dynamics combined with a dynamical approach of the nonequilibrium molecular dynamics (D-NEMD). The network structures in the polymerization process are probed by cluster analysis tools, and the results are critically compared with the similar all-atom system, showing a good agreement.

Sticker-and-spacer model for amyloid beta condensation and fibrillation

A major pathogenic hallmark of Alzheimer's disease is the presence of neurotoxic plaques composed of amyloid beta (Aβ) peptides in patients' brains. The pathway of plaque formation remains elusive, though some clues appear to lie in the dominant presence of Aβ_{1 − 42} in these plaques despite Aβ₁₋₄₀ making up approximately 90% of the Aβ pool. We hypothesize that this asymmetry is driven by the hydrophobicity of the two extra amino acids that are incorporated in Aβ₁₋₄₂. To investigate this hypothesis at the level of single molecules, we have developed a molecular “sticker-and-spacer lattice model” of unfolded Aβ. The model protein has a single sticker that may reversibly dimerise and elongate into semi-flexible linear chains. The growth is hampered by excluded-volume interactions that are encoded by the hydrophilic spacers but are rendered cooperative by the attractive interactions of hydrophobic spacers. For sufficiently strong hydrophobicity, the chains undergo liquid-liquid phase-separation (LLPS) into condensates that facilitate the nucleation of fibers. We find that a small fraction of Aβ₁₋₄₀ in a mixture of Aβ₁₋₄₀ and Aβ₁₋₄₂ shifts the critical concentration for LLPS to lower values. This study provides theoretical support for the hypothesis that LLPS condensates act as a precursor for aggregation and provides an explanation for the Aβ₁₋₄₂-enrichment of aggregates in terms of hydrophobic interactions.

Accurate predictions of thermoset resin glass transition temperatures from all-atom molecular dynamics simulation

To enable the design and development of the next generation of high-performance composite materials, there is a need to establish improved computational simulation protocols for accurate and efficient prediction of physical, mechanical, and thermal properties of thermoset resins. This is especially true for the prediction of glass transition temperature (T_g), as there are many discrepancies in the literature regarding simulation protocols and the use of cooling rate correction factors for predicting values using molecular dynamics (MD) simulation. The objectives of this study are to demonstrate accurate prediction the T_g with MD without the use of cooling rate correction factors and to establish the influence of simulated conformational state and heating/cooling cycles on physical, mechanical, and thermal properties predicted with MD. The experimentally-validated MD results indicate that accurate predictions of T_g, elastic modulus, strength, and coefficient of thermal expansion are highly reliant upon establishing MD models with mass densities that match experiment within 2%. The results also indicate the cooling rate correction factors, model building within different conformational states, and the choice of heating/cooling simulation runs do not provide statistically significant differences in the accurate prediction of T_g values, given the typical scatter observed in MD predictions of amorphous polymer properties.

Molecular Simulations and Network Analyses of Surface/Interface Effects in Epoxy Resins: How Bonding Adapts to Boundary Conditions

In this study, we unravel the atomic structure of a covalent resin near boundaries such as surfaces and composite constituents. For this, a molecular simulation analysis of epoxy resin hardening under various boundary conditions was performed. On the atomic level of detail, molecular dynamics simulations were employed to study crosslinking reactions and self-organization of the polymer network within nm scale slab models. The resulting structures were then coarsened into a graph theoretical description for connectivity analysis of the nodes and combined with characterization of the node-to-node vector orientation. On this basis, we show that the local bonding of epoxy resins near interfaces tends to avoid under-coordinated linker sites. For both epoxy-vacuum surface models and epoxy-silica/epoxy cellulose interfaces, we find almost fully cured polymer networks. These feature a local increase in network linking lateral to the surface/interface, rather than the dangling of unreacted epoxy groups. Consequently, interface tension is low (as compared to the work of separating bulk epoxy), and the reactivity of the resin surface appears negligible.

Molecular Simulations of Thermomechanical Properties of Epoxy-Amine Resins

All-atom molecular dynamics (MD) simulations were performed with the CHARMM force field to characterize various epoxy resins, such as aliphatic and bisphenol-based resins. A multistep cross-linking algorithm was established, and key properties such as density, glass temperature, and elastic modulus were calculated. A quantitative comparison was made and was proven to be in good agreement with experimental data, with average absolute deviations between experiments and molecular simulation comprised between 2% and 12%. Additional findings on structure-property relationships were highlighted such as the effect of the cross-linking rate and oligomerization of the resin.

Accelerated Diffusion Following Deprotection in Chemically Amplified Resists

Polymeric chemically amplified resists (CARs) are critical materials for high-throughput lithographic processes. A photoactivated acid-anion catalyst changes the polymer's solubility via a deprotection reaction, which enables pattern development through selective dissolution. To capture observed reaction kinetics, reaction-diffusion models employ a catalyst diffusivity that is accelerated by reaction. However, the microscopic origin and factors contributing to this phenomena remain unclear. Herein, we employ detailed atomistic molecular dynamics simulations to examine the impact of protecting group removal and material relaxation on catalyst mobility. We report data on polymer density, catalyst dispersion, excess free volume, and segmental dynamics with increasing time/extent of deprotection. We then propose simple kinetic Monte Carlo algorithms that can describe both molecular dynamics simulations of deprotection reactions and experimental data.

Multi-Scale Modelling of Plastic Deformation, Damage and Relaxation in Epoxy Resins

Epoxy resin plasticity and damage was studied from molecular dynamic simulations and interpreted by the help of constitutive modelling. For the latter, we suggested a physically motivated approach that aims at interpolating two well-defined limiting cases; namely, pulling at the vanishing strain rate and very rapid deformation; here, taken as 50% of the speed of sound of the material. In turn, to consider 0.1-10-m/s-scale deformation rates, we employed a simple relaxation model featuring exponential stress decay with a relaxation time of 1.5 ns. As benchmarks, deformation and strain reversal runs were performed by molecular dynamic simulations using two different strain rates. Our analyses show the importance of molecular rearrangements within the epoxy network loops for rationalizing the strain-rate dependence of plasticity and residual stress upon strain reversal. To this end, our constitutive model reasonably reproduced experimental data of elastic and visco-elastic epoxy deformation, along with the maximum stress experienced before fracturing. Moreover, we show the importance of introducing damage elements for mimicking the mechanical behavior of epoxy resins.

Uncovering the Mechanism of Size Effect on the Thermomechanical Properties of Highly Cross-Linked Epoxy Resins

Epoxy resins are widely used as matrix resins, especially for carbon-fiber-reinforced plastic, due to their outstanding physical and mechanical properties. To date, most research into cross-linking processes using simulation has considered only a distance-based criterion to judge the probability of reaction. In this work, a new algorithm was developed for use with the large-scale atomic/molecular massively parallel simulator (LAMMPS) simulation package to study the cross-linking process; this new approach combines both a distance-based criterion and several kinetic criteria to identify whether the reaction has occurred. Using this simulation framework, we investigated the effect of model size on predicted thermomechanical properties of three different structural systems: diglycidyl ether of bisphenol A (DGEBA)/4,4'-diaminodiphenyl sulfone (4,4'-DDS), DGEBA/diethylenetriamine (DETA), and tetraglycidyl diaminodiphenylmethane (TGDDM)/4,4'-DDS. Derived values of gel point, volume shrinkage, and cross-linked resin density were found to be insensitive to model size in these three systems. Other thermomechanical properties, i.e., glass-transition temperature, Young's modulus, and yield stress, were found to reach stable values for systems larger than ∼40 000 atoms for both DGEBA/4,4'-DDS and DGEBA/DETA. However, these same properties modeled for TGDDM/4,4'-DDS did not stabilize until the system size reached 50 000 atoms. Our results provide general guidelines for simulation system size and procedures to more accurately predict the thermomechanical properties of epoxy resins.

Effect of stoichiometry on crosslinked epoxy resin characteristics: structural heterogeneities, topological defects, properties, free volume and segmental mobility

Experimental studies have shown that changes in stoichiometry (R, ratio of amine groups to epoxy groups) cause considerable variations in the properties of epoxy-amine systems. Rationales based on free volume concepts have been routinely used to address these variations in properties but have hardly been satisfactorily substantiated. Many of these rationales remain as unverified conjectures to date. Substantiating these rationales will certainly bolster our understanding of the structure-stoichiometry-property relationship, but is difficult, due to inherent challenges involved in unambiguously characterizing the structural heterogeneities induced by changes in stoichiometry (structural heterogeneities include compositional distribution in the functionality of monomers, non-uniform dispersion of elastic chains and topological defects). The aim of the present work is to gain molecular-level insights into this relationship and to verify the rationales that rely on free volume concepts used for addressing the variations in properties with stoichiometry, with the help of all-atom molecular dynamics (MD) simulations. Five epoxy-amine systems with varying R ranging from 0.4 to 3, including the stoichiometric system (R = 1), were considered for these purposes. The properties of interest namely density, glass transition temperature (T_g) and thermal expansion coefficient in the rubbery state (α_rl) of these systems were predicted. The local structure, fractional free volume and segmental mobility of these systems were then subsequently characterized as a function of stoichiometry and the results were analysed in detail. The role played by defects in properties and fractional free volume was then investigated. The results revealed significant insights into the compositional distribution of monomers with different functionalities as well as offered insights into the dispersion state and mobility of dangling chains, sols and elastic chains in the systems. Further, strong correlations were found between defect composition, fractional free volume at an elevated temperature (600 K) and thermomechanical properties (T_g and α_rl) and it was established that the key mechanism underlying these correlations was the plasticization caused by defects. Analysis based on the rule of mixture models showed that these correlations were found to be in good agreement with the interpretations based on free volume concepts. The results also revealed a strong negative correlation between fractional free volume at room temperature and defect composition, a phenomenon typically associated with the antiplasticization effect.

Capturing Free-Radical Polymerization by Synergetic Ab Initio Calculations and Topological Reactive Molecular Dynamics

Photocurable polymers are used ubiquitously in 3D printing, coatings, adhesives, and composite fillers. In the present work, the free radical polymerization of photocurable compounds is studied using reactive classical molecular dynamics combined with a dynamical approach of the nonequilibrium molecular dynamics (D-NEMD). Different concentrations of radicals and reaction velocities are considered. The mechanical properties of the polymer resulting from 1,6-hexanediol dimethacrylate systems are characterized in terms of viscosity, diffusion constant, and activation energy, whereas the topological ones through the number of cycles (polymer loops) and cyclomatic complexity. Effects like volume shrinkage and delaying of the gel point for increasing monomer concentration are also predicted, as well as the stress-strain curve and Young's modulus. Combining ab initio, reactive molecular dynamics, and the D-NEMD method might lead to a novel and powerful tool to describe photopolymerization processes and to original routes to optimize additive manufacturing methods relying on photosensitive macromolecular systems.

Solid with infused reactive liquid (SWIRL): A novel liquid-based separation approach for effective CO2 capture

Economical CO₂ capture demands low-energy separation strategies. We use a liquid-infused surface (LIS) approach to immobilize reactive liquids, such as amines, on a textured and thermally conductive solid substrate with high surface-area to volume ratio (A/V) continuum geometry. The infused, micrometer-thick liquid retains that high A/V and directly contacts the gas phase, alleviating mass transport resistance typically encountered in mesoporous solid adsorbents. We name this LIS class "solid with infused reactive liquid" (SWIRL). SWIRL-amine requires no water dilution or costly mixing unlike the current liquid-based commercial approach. SWIRL-tetraethylenepentamine (TEPA) shows stable, high capture capacities at power plant CO₂ concentrations near flue gas temperatures, preventing energy-intensive temperature swings needed for other approaches. Water vapor increases CO₂ capacity of SWIRL-TEPA without compromising stability.

Ligand Interactions and Nanoparticle Shapes Guide the Pathways toward Interfacial Self-Assembly

Non-equilibrium molecular dynamics simulations are used to probe the driving forces behind the formation of highly ordered, epitaxially connected superlattices of polyhedral-shaped nanoparticles (NPs) at fluid-fluid interfaces. By explicitly modeling coarse-grained ligands that cap the NP surface, it is shown that differences in NP shapes and time-dependent facet-specific ligand densities give rise to drastically different transformation mechanisms. Our results indicate that the extent of screening of the inter-particle interactions by the surrounding solvation environment has a significant impact on reversibility and ultimately the coherence of the final two-dimensional superlattice obtained. For the particle shapes examined, a hexagonal pre-assembly and a square superlattice final assembly (upon preferential ligand desorption from {100} facets) were prevalent; however, cuboctahedral NPs formed intermediate epitaxially bonded branched clusters, which eventually grew and rearranged into a square lattice; in contrast, truncated octahedral NPs exhibited an abrupt rhombic-to-square transition driven by the clustering of their numerous {111}-ligands that favored the stacking of linear NP rods. To track the incipient order in the system, we also outline a set of novel order parameters that measure the local orientation alignment between nearest-neighbor pairs. The simulation protocols advanced in this work could pave the way forward for exploration of the vast phase space associated with the interfacial self-assembly of NPs.

Kinetically Corrected Monte Carlo-Molecular Dynamics Simulations of Solid Electrolyte Interphase Growth

We present a kinetic approach to the Monte Carlo-molecular dynamics (MC-MD) method for simulating reactive liquids using nonreactive force fields. A graphical reaction representation allows definition of reactions of arbitrary complexity, including their local solvation environment. Reaction probabilities and molecular dynamics (MD) simulation times are derived from ab initio calculations. Detailed validation is followed by studying the development of the solid electrolyte interphase (SEI) in lithium-ion batteries. We reproduce the experimentally observed two-layered structure on graphite, with an inorganic layer close to the anode and an outer organic layer. This structure develops via a near-shore aggregation mechanism.

The role of interface on the toughening and failure mechanisms of thermoplastic nanocomposites reinforced with nanofibrillated rubber

The interface plays a crucial role in the physical and functional properties of polymer nanocomposites, yet its effects have not been fully recognized in the setting of classical continuum-based modeling. In the present study, we investigate the roles of interface and interfiber interactions on the toughening effects of rubber nanofibers embodied in thermoplastic-based materials. Emphasis is placed on establishing comprehensive theoretical and atomistic descriptions of the nanocomposite systems subjected to pull-out and uniaxial extension in the longitudinal and transverse directions. Using the framework of molecular dynamics, the annealed melt-drawn nanofibers were spontaneously formed via the proposed four-step methodology. The generated nanofibers were then crosslinked using the proposed robust topology-matching algorithm, through which the chemical reactions arising in the crosslinking were closely assimilated. The interfiber interactions were also examined with respect to separation distances and nanofiber radius via a nanofiber-pair atomistic scheme, and the obtained results were subsequently incorporated into the pull-out and uniaxial test simulations. The results indicate that the compatibilizer grafting results in enhanced interfacial shear strength by introducing extra chemical interactions at the interface. In particular, it was found that the compatibilizer restricts the formation and coalescence of nanovoids, resulting in enhanced toughening effects. Together, we have shown that the presence of a small amount of well-dispersed rubber nanofibrillar network whose surfaces are grafted with maleic anhydride compatibilizer can dramatically increase the toughness and alter the failure mechanisms of the nanocomposites without any deterioration in the stiffness, which is also consistent with the recent experimental observations in our lab. The interfacial failure mechanism was also investigated by monitoring the changes in the atomic concentration profiles, mean square displacement and fractional free volume. The results obtained may serve as a promising alternative for the continuum-based modeling and analysis of interfaces.

An Exact Algorithm to Detect the Percolation Transition in Molecular Dynamics Simulations of Cross-Linking Polymer Networks

Periodic molecular dynamics simulations are developing to a routine tool for the investigation of complex, polymeric materials. A typical application is the simulation of the curing reaction of covalently cross-linked polymers, which provides detailed understanding of network formation at the molecular scale, with examples including gelation and glass transitions. In this article, we delineate the connection between percolation theory and gel-point detection in periodic polymeric networks. Specifically, we present an algorithm that can detect the onset of percolation during cross-linking of polymers in periodic molecular dynamic simulations. A sample implementation is provided at https://github.com/puls-group/percolation-analyzer. As an example, we apply the algorithm to simulations of an epoxy resin undergoing curing with an amine hardener. We also compare results with indirect gel point measurements obtained from monitoring the growth of the largest mass and the onset of secondary cycles.

Characterization of Cure Behavior in Epoxy Using Molecular Dynamics Simulation Compared with Dielectric Analysis and DSC

The curing behavior of a thermosetting material that influences the properties of the material is a key issue for predicting the changes in material properties during processing. An empirical equation can describe the reaction kinetics of the curing behavior of an investigated material, which is usually estimated using experimental methods. In this study, the curing process of an epoxy resin, the polymer matrix in an epoxy molding compound, is computed concerning thermal influence using molecular dynamics. Furthermore, the accelerated reaction kinetics, which are influenced by an increased reaction cutoff distance, are investigated. As a result, the simulated crosslink density with various cutoff distances increases to plateau at a crosslink density of approx. 90% for the investigated temperatures during curing time. The reaction kinetics are derived according to the numerical results and compared with the results using experimental methods (dielectric analysis and differential scanning calorimetry), whereby the comparison shows a good agreement between experiment and simulation.