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Human enamel is an incredibly resilient biological material, withstanding repeated daily stresses for decades. The mechanisms behind this resilience remain an open question, with recent studies demonstrating a crack-deflection mechanism contributing to enamel toughness and other studies detailing the roles of the organic matrix and remineralization. Here, we focus on the mineral and hypothesize that self-healing of cracks in enamel nanocrystals may be an additional mechanism acting to prevent catastrophic failure. To test this hypothesis, we used a molecular dynamics (MD) approach to compare the fracture behavior of hydroxyapatite (HAP) and calcite, the main minerals in human enamel and sea urchin teeth, respectively. We find that cracks heal under pressures typical of mastication by fusion of crystals in HAP but not in calcite, which is consistent with the resilience of HAP enamel that calcite teeth lack. Scanning transmission electron microscopy (STEM) images of structurally intact ("sound") human enamel show dashed-line nanocracks that resemble and therefore might be the cracks healed by fusion of crystals produced in silico. The fast, self-healing mechanism shown here is common in soft materials and ceramics but has not been observed in single crystalline materials at room temperature. The crack self-healing in sound enamel nanocrystals, therefore, is unique in the human body and unique in materials science, with potential applications in designing bioinspired materials.

In this study we report a computational approach towards multiscale architected materials analysis and design. A particular challenge in modeling and simulation of materials, and especially the development of hierarchical design approaches, has been to identify ways by which complex multi-level material structures can be effectively modeled. One way to achieve this is to use coarse-graining approaches, where physical relationships can be effectively described with reduced dimensionality. In this paper we report an integrated deep neural network architecture that first learns coarse-grained representations of complex hierarchical microstructure data via a discrete variational autoencoder and then utilizes an attention-based diffusion model solve both forward and inverse problems, including a capacity to solve degenerate design problems. As an application, we demonstrate the method in the analysis and design of hierarchical highly porous metamaterials within the context of nonlinear stress–strain responses to compressive deformation. We validate the mechanical behavior and mechanisms of deformation using embedded-atom molecular dynamics simulations carried out for copper and nickel, showing good agreement with the design objectives. [ABSTRACT FROM AUTHOR]

Architected materials can achieve enhanced properties compared to their plain counterparts. Specific architecting serves as a powerful design lever to achieve targeted behavior without changing the base material. Thus, the connection between architected structure and resultant properties remains an open field of great interest to many fields, from aerospace to civil to automotive applications. Here, we focus on properties related to mechanical compression, and design hierarchical honeycomb structures to meet specific values of stiffness and compressive stress. To do so, we employ a combination of techniques in a singular workflow, starting with molecular dynamics simulation of the forward design problem, augmenting with data-driven artificial intelligence models to address the inverse design problem, and verifying the behavior of de novo structures with experimentation of additively manufactured samples. We thereby demonstrate an approach for architected design that is generalizable to multiple material properties and agnostic to the identity of the base material. [ABSTRACT FROM AUTHOR]

[Display omitted] Attention-based transformer neural networks have had significant impact in recent years. However, their applicability to model the behavior of physical systems has not yet been broadly explored. This is partly due to the high computational burden owing to the nonlinear scaling of very deep models, preventing application to a range of physical systems, in particular complex field data. Here we report the development of a general-purpose attention-based deep neural network model using a multi-headed self-attention approach, FieldPerceiver, that is capable of effectively predicting physical field data – such as stress, energy and displacement fields, as well as predicting overall material properties that characterize the statistics of stress distributions due to applied loading and crack defects, solely based on descriptive input that characterizes the material microstructure based on a set of interacting building blocks, all while capturing extreme short- and long-range relationships. Not using images as input, but rather realizing a neural olog description of materials where the categorization is learned by multi-headed attention, the model has no domain knowledge in its formulation, uses no convolutional layers, scales well to extremely large sizes and has no knowledge about specific properties of the material building blocks. Specifically, as applied to a fracture mechanics problem considered here, the model is capable of capturing size, orientation and geometry effects of crack problems for near- and far-field predictions, offering an alternative way to model materials failure based on language modeling without any convolutional layers commonly used in similar problems. We show that the FieldPerceiver can be used in a general framework, where the model can use insights learned during an initial, general training stage in order to fine-tune predictions for new scenarios, even when using only small additional datasets, revealing its broad generalization capacity. Once trained, the model can make predictions of thousands of scenarios within just a few minutes of compute time. It would take tens of hours, days or months to compute similar output using molecular dynamics simulation, for instance. [ABSTRACT FROM AUTHOR]

Understanding biomass interaction is critical for bottom‐up design of novel biocomposites and existing manufacturing processes. In this study, interactions between bioadhesives (lignin, carbohydrates, or proteins) and fibers (cellulosic fiber or wood fiber) are elucidated via experimental bonding strength tests and molecular dynamics (MD) simulations. Experimental results reveal a good, nearly linear correlation between the composite's density and tensile strength, a finding which has rarely been reported previously. Adhesives are compared to one another: soy protein isolate is found to be the best for pinewood fiber, while apple pectin and soy protein isolate are the best for α‐cellulose fiber. It is further shown that the fiber type plays an important role in defining the composite strength. In agreement with experiments, the MD simulations at nanoscale predict a linear strength to density correlation; this is driven by the hydrogen bond (H‐bond) content in the composite. The H‐bond content is also found to determine the varied performances of different adhesives. [ABSTRACT FROM AUTHOR]

We describe a method to generate 3D architected materials based on mathematically parameterized human readable word input, offering a direct materialization of language. Our method uses a combination of a vector quantized generative adversarial network and contrastive language-image pre-training neural networks to generate images, which are translated into 3D architectures that are then 3D printed using fused deposition modeling into materials with varying rigidity. The novel materials are further analyzed in a metallic realization as an aluminum-based nano-architecture, using molecular dynamics modeling and thereby providing mechanistic insights into the physical behavior of the material under extreme compressive loading. This work offers a novel way to design, understand, and manufacture 3D architected materials designed from mathematically parameterized language input. Our work features, at its core, a generally applicable algorithm that transforms any 2D image data into hierarchical fully tileable, periodic architected materials. This method can have broader applications beyond language-based materials design and can render other avenues for the analysis and manufacturing of architected materials, including microstructure gradients through parametric modeling. As an emerging field, language-based design approaches can have a profound impact on end-to-end design environments and drive a new understanding of physical phenomena that intersect directly with human language and creativity. It may also be used to exploit information mined from diverse and complex databases and data sources. [ABSTRACT FROM AUTHOR]

The gestalt of computational methods including physics-based molecular dynamics simulations, data-driven machine learning (ML) models, and biologically-inspired genetic algorithms affords a powerful toolbox for tackling materials mechanism discovery and design problems. Here, we leverage these methods to investigate the complex multidimensional problem of polycrystalline 2D material fracture. We focus first on graphene and in doing so, demonstrate a practical workflow for exploring the structural dependencies of fracture energy. Despite training our ML model on exclusively single crystal fracture in increments of 10° orientations, we can identify a crack branching mechanism responsible for high bicrystal toughness centered at initial crystal orientation angles of 19° and 41°. These high peaks span only a few degrees in range and are completely overlooked by a search with stride 10°. Furthermore, we can discover qualitative physical phenomena such as collective fracture branch termination and extract quantitative trends relating angular dispersion and mis-orientation angles of crystal grains to fracture energy. None of these complex polycrystalline behaviors were presented in the training data, and the predictive power of the model ultimately allows us to expeditiously generate polycrystalline graphene structures with bespoke fracture paths, a task with great implications in industrial design applications and mechanism discovery. Furthermore, the approach is not limited to graphene specifically, as we demonstrate by retraining the model for another more complex 2D material—MoS2—and achieve polycrystalline fracture predictions of comparable accuracy. [ABSTRACT FROM AUTHOR]

We propose a simple general framework to predict folding, native states, energy barriers, protein unfolding, as well as mutation induced diseases and other protein structural analyses. The model should not be considered as an alternative to classical approaches (Molecular Dynamics or Monte Carlo) because it neglects low scale details and rather focuses on global features of proteins and structural information. We aim at the description of phenomena that are out of the range of classical molecular modeling approaches due to the large computational cost: multimolecular interactions, cyclic behavior under variable external interactions, and similar. To demonstrate the effectiveness of the approach in a real case, we focus on the folding and unfolding behavior of tropoelastin and its mutations. Specifically, we derive a discrete mechanical model whose structure is deduced based on a coarse graining approach that allows us to group the amino acids sequence in a smaller number of 'equivalent' masses. Nearest neighbor energy terms are then introduced to reproduce the interaction of such amino acid groups. Nearest and non-nearest neighbor energy terms, inter and intra functional blocks are phenomenologically added in the form of Morse potentials. As we show, the resulting system reproduces important properties of the folding-unfolding mechanical response, including the monotonic and cyclic force-elongation behavior, representing a physiologically important information for elastin. The comparison with the experimental behavior of mutated tropoelastin confirms the predictivity of the model. Classical approaches to the study of phenomena at the molecular scale such as Molecular Dynamics (MD) represent an incredible tool to unveil mechanical and conformational properties of macromolecules, in particular for biological and medical applications. On the other hand, due to the computational cost, the time and spatial scales are limited. Focusing of the real case of tropoelastin, we propose a new approach based on a careful coarse graining of the system, able to describe the overall properties of the macromolecule and amenable of extension to larger scale effects (protein bundles, protein-protein interactions, cyclic loading). The comparison with tropoelastin behavior, also for mutations, is very promising. [Display omitted] [ABSTRACT FROM AUTHOR]

Understanding the properties and behavior of biomineralized protein-based materials at the organic-inorganic interface is critical to optimize the performance of such materials for biomedical applications. To that end, this work investigates biomineralized protein-based films with applications for bone regeneration. These films were generated using a chimeric protein fusing the consensus repeat derived from the spider Nephila clavipes major ampullate dragline silk with the silica-promoting peptide R5 derived from the Cylindrotheca fusiformis silaffin gene. The effect of pH on the size of silica nanoparticles during their biomineralization on silk films was investigated, as well as the potential impact of nanoparticle size on the differentiation of human mesenchymal stem cells (hMSCs) into osteoblasts. To that end, induction of the integrin αV subunit and the osteogenic markers Runx2 transcription factor and Bone Sialoprotein (BSP) was followed. The results indicated that pH values of 7-8 during biomineralization maximized the coverage of the film surface by silica nanoparticles yielding nanoparticles ranging 200-500 nm and showing enhanced osteoinduction in gene expression analysis. Lower (3-5) or high (10) pH values led to lower biomineralization and poor coverage of the protein surfaces, showing reduced osteoinduction. Molecular dynamics simulations confirmed the activation of the integrin αVβ3 in contact with silica nanoparticles, correlating with the experimental data on the induction of osteogenic markers. This work sheds light on the optimal conditions for the development of fit-for-purpose biomaterial designs for bone regeneration, while the agreement between experimental and computational results shows the potential of computational methods to predict the expression of osteogenic markers for biomaterials. The ability of biomineralized materials to induce hMSCs differentiation for bone tissue regeneration applications was analyzed. Biomaterials were created using a recombinant protein formed by the consensus repeat derived from the spider Nephila clavipes major ampullate dragline silk and the silica-promoting peptide R5 derived from the Cylindrotheca fusiformis silaffin gene. A combination of computational and experimental techniques revealed the optimal conditions for the synthesis of biomineralized silk-silica films with enhanced expression of markers related to bone regeneration. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions within proteins (IDRs) serve an increasingly expansive list of biological functions, including regulation of transcription and translation, protein phosphorylation, cellular signal transduction, as well as mechanical roles. The strong link between protein function and disorder motivates a deeper fundamental characterization of IDPs and IDRs for discovering new functions and relevant mechanisms. We review recent advances in experimental techniques that have improved identification of disordered regions in proteins. Yet, experimentally curated disorder information still does not currently scale to the level of experimentally determined structural information in folded protein databases, and disorder predictors rely on several different binary definitions of disorder. To link secondary structure prediction algorithms developed for folded proteins and protein disorder predictors, we conduct molecular dynamics simulations on representative proteins from the Protein Data Bank, comparing secondary structure and disorder predictions with simulation results. We find that structure predictor performance from neural networks can be leveraged for the identification of highly dynamic regions within molecules, linked to disorder. Low accuracy structure predictions suggest a lack of static structure for regions that disorder predictors fail to identify. While disorder databases continue to expand, secondary structure predictors and molecular simulations can improve disorder predictor performance, which aids discovery of novel functions of IDPs and IDRs. These observations provide a platform for the development of new, integrated structural databases and fusion of prediction tools toward protein disorder characterization in health and disease. [ABSTRACT FROM AUTHOR]

Abstract: Hydrogels are the focus of extensive research due to their potential use in fields including biomedical, pharmaceutical, biosensors, and cosmetics. However, the general weak mechanical properties of hydrogels limit their utility. Here, pristine silk fibroin (SF) hydrogels with excellent mechanical properties are generated via a binary‐solvent‐induced conformation transition (BSICT) strategy. In this method, the conformational transition of SF is regulated by moderate binary solvent diffusion and SF/solvent interactions. β‐sheet formation serves as the physical crosslinks that connect disparate protein chains to form continuous 3D hydrogel networks, avoiding complex chemical and/or physical treatments. The Young's modulus of these new BSICT–SF hydrogels can reach up to 6.5 ± 0.2 MPa, tens to hundreds of times higher than that of conventional hydrogels (0.01–0.1 MPa). These new materials fill the “empty soft materials' space” in the elastic modulus/strain Ashby plot. More remarkably, the BSICT–SF hydrogels can be processed into different constructions through different polymer and/or metal‐based processing techniques, such as molding, laser cutting, and machining. Thus, these new hydrogel systems exhibit potential utility in many biomedical and engineering fields. [ABSTRACT FROM AUTHOR]

Collagen is a ubiquitous protein with remarkable mechanical properties. It is highly elastic, shows large fracture strength and enables substantial energy dissipation during deformation. Most of the connective tissue in humans consists of collagen fibrils composed of a staggered array of tropocollagen molecules, which are connected by intermolecular cross-links. In this study, we report a three-dimensional coarse-grained model of collagen and analyze the influence of enzymatic cross-links on the mechanics of collagen fibrils. Two representatives immature and mature cross-links are implemented in the mesoscale model using a bottom-up approach. By varying the number, type and mechanical properties of cross-links in the fibrils and performing tensile test on the models, we systematically investigate the deformation mechanisms of cross-linked collagen fibrils. We find that cross-linked fibrils exhibit a three phase behavior, which agrees closer with experimental results than what was obtained using previous models. The fibril mechanical response is characterized by: (i) an initial elastic deformation corresponding to the collagen molecule uncoiling, (ii) a linear regime dominated by molecule sliding and (iii) the second stiffer elastic regime related to the stretching of the backbone of the tropocollagen molecules until the fibril ruptures. Our results suggest that both cross-link density and type dictate the stiffness of large deformation regime by increasing the number of interconnected molecules while cross-links mechanical properties determine the failure strain and strength of the fibril. These findings reveal that cross-links play an essential role in creating an interconnected fibrillar material of tunable toughness and strength. [ABSTRACT FROM AUTHOR]

The nucleoskeleton contains mainly nuclear intermediate filaments made of lamin proteins. Lamins provide nuclear structure and also play a role in various nuclear processes including signal transduction, transcription regulation and chromatin organization. The disparate functions of lamins may be related to the intrinsic disorder of the tail domains, which allows for altered and promiscuous binding. Here, we show modulation of lamin tail domain structures in the presence of divalent cations. We utilize changes in fluorescence of tryptophan residues within the Ig-fold flanked by disordered regions to experimentally measure protein thermodynamics. Using spectroscopy experiments and molecular dynamics simulations, we show that the tail domain of lamin B1 shows enhanced association with both Ca2+ and Mg2+ compared to the tail domain of lamin A. Binding curves show a similar KD between protein and ion (250–300 μM) for both proteins with both ions. However, we observe a maximum binding of ions to lamin B1 tail domain which is 2–3 times greater than that for lamin A tail domain by both experiment and simulation. Using simulations, we show that divalent ion association alters the Ig-fold by pinning flanking regions. With cells in culture, we observe altered lamin B1 organization in the presence of excess Mg2+ more so than for lamin A. We suggest that the differential sensitivity to divalent cations contributes to the vastly different functionalities and binding of the 2 proteins. [ABSTRACT FROM AUTHOR]

Wood is a biological material with outstanding mechanical properties resulting from its hierarchical structure across different scales. Although earlier work has shown that the cellular structure of wood is a key factor that renders it excellent mechanical properties at light weight, the mechanical properties of the wood cell wall material itself still needs to be understood comprehensively. The wood cell wall material features a fiber reinforced composite structure, where cellulose fibrils act as stiff fibers, and hemicellulose and lignin molecules act as soft matrix. The angle between the fiber direction and the loading direction has been found to be the key factor controlling the mechanical properties. However, how the interactions between theses constitutive molecules contribute to the overall properties is still unclear, although the shearing between fibers has been proposed as a primary deformation mechanism. Here we report a molecular model of the wood cell wall material with atomistic resolution, used to assess the mechanical behavior under shear loading in order to understand the deformation mechanisms at the molecular level. The model includes an explicit description of cellulose crystals, hemicellulose, as well as lignin molecules arranged in a layered nanocomposite. The results obtained using this model show that the wood cell wall material under shear loading deforms in an elastic and then plastic manner. The plastic regime can be divided into two parts according to the different deformation mechanisms: yielding of the matrix and sliding of matrix along the cellulose surface. Our molecular dynamics study provides insights of the mechanical behavior of wood cell wall material at the molecular level, and paves a way for the multi-scale understanding of the mechanical properties of wood. [ABSTRACT FROM AUTHOR]

The scales of the arapaima (Arapaima gigas), one of the largest freshwater fish in the world, can serve as inspiration for the design of flexible dermal armor. Each scale is composed of two layers: a laminate composite of parallel collagen fibrils and a hard, highly mineralized surface layer. We review the structure of the arapaima scales and examine the functions of the different layers, focusing on the mechanical behavior, including tension and penetration of the scales, with and without the highly mineralized outer layer. We show that the fracture of the mineral and the stretching, rotation and delamination of collagen fibrils dissipate a significant amount of energy prior to catastrophic failure, providing high toughness and resistance to penetration by predator teeth. We show that the arapaima's scale has evolved to minimize damage from penetration by predator teeth through a Bouligand-like arrangement of successive layers, each consisting of parallel collagen fibrils with different orientations. This inhibits crack propagation and restricts damage to an area adjoining the penetration. The flexibility of the lamellae is instrumental to the redistribution of the compressive stresses in the underlying tissue, decreasing the severity of the concentrated load produced by the action of a tooth. The experimental results, combined with small-angle X-ray scattering characterization and molecular dynamics simulations, provide a complete picture of the mechanisms of deformation, delamination and rotation of the lamellae during tensile extension of the scale. [ABSTRACT FROM AUTHOR]

Here we report a series of full atomistic molecular dynamics simulations of six amyloid or amyloid-like protein fibrils in order to systematically understand the effect of different secondary structure motifs on the mechanical tensile and failure response of cross- protein fibrils. We find a similar failure behavior across the six structures; an initial failure event occurs at small strains involving cooperative rupture of a group of hydrogen bonds, followed by a slow one-by-one hydrogen bond rupture process as the remaining -sheets peel off with very low applied stress. We also find that the ultimate tensile strength of the protein fibrils investigated scales directly with the number of hydrogen bonds per unit area which break in the initial rupture event. Our results provide insights into structure–property relationships in protein fibrils important for disease and engineering applications and lay the groundwork for the development of materials selection criteria for the design of de novo amyloid-based functional biomaterials. [ABSTRACT FROM AUTHOR]

Molecular modeling of protein materials is a quickly growing area of research that has produced numerous contributions in fields ranging from structural engineering to medicine and biology. We review here the history and methods commonly employed in molecular modeling of protein materials, emphasizing the advantages for using modeling as a complement to experimental work. We then consider a case study of the protein elastin, a critically important 'mechanical protein' to exemplify the approach in an area where molecular modeling has made a significant impact. We outline the progression of computational modeling studies that have considerably enhanced our understanding of this important protein which endows elasticity and recoil to the tissues it is found in, including the skin, lungs, arteries and the heart. A vast collection of literature has been directed at studying the structure and function of this protein for over half a century, the first molecular dynamics study of elastin being reported in the 1980s. We review the pivotal computational works that have considerably enhanced our fundamental understanding of elastin's atomistic structure and its extraordinary qualities--focusing on two in particular: elastin's superb elasticity and the inverse temperature transition--the remarkable ability of elastin to take on a more structured conformation at higher temperatures, suggesting its effectiveness as a biomolecular switch. Our hope is to showcase these methods as both complementary and enriching to experimental approaches that have thus far dominated the study of most protein-based materials. [ABSTRACT FROM AUTHOR]

Abstract.: The stability of alpha helices is important in protein folding, bioinspired materials design, and controls many biological properties under physiological and disease conditions. Here we show that a naturally favored alpha helix length of 9 to 17 amino acids exists at which the propensity towards the formation of this secondary structure is maximized. We use a combination of thermodynamical analysis, well-tempered metadynamics molecular simulation and statistical analyses of experimental alpha helix length distributions and find that the favored alpha helix length is caused by a competition between alpha helix folding, unfolding into a random coil and formation of higher-order tertiary structures. The theoretical result is suggested to be used to explain the statistical distribution of the length of alpha helices observed in natural protein structures. Our study provides mechanistic insight into fundamental controlling parameters in alpha helix structure formation and potentially other biopolymers or synthetic materials. The result advances our fundamental understanding of size effects in the stability of protein structures and may enable the design of de novo alpha-helical protein materials. Graphical abstract: [ABSTRACT FROM AUTHOR]

The intrinsic interfacial thermal resistance at graphene/organic interfaces, as a result of mismatches in the phonon vibrational spectra of the two materials, diminishes the overall heat transfer performance of graphene/organic nanocomposites. In this paper, we use molecular dynamics (MD) simulations to design alkyl-pyrene molecules that can non-covalently functionalize graphene surfaces in contact with a model organic phase composed of octane. The alkyl-pyrene molecules possess phonon-spectra features of both graphene and octane and, therefore, can serve as phonon-spectra linkers to bridge the vibrational mismatch at the graphene/octane interface. In support of this hypothesis, we find that the best linker candidate can enhance the out-of-plane graphene/organic interfacial thermal conductance by ∼22%, attributed to its capability to compensate the low-frequency phonon mode of graphene. We also find that the length of the alkyl chain indirectly affects the interfacial thermal conductance through different orientations of these chains because they dictate the contribution of the out-of-plane high-frequency carbon-hydrogen bond vibrations to the overall phonon transport. This study advances our understanding of the less destructive non-covalent functionalization method and design principles of suitable linker molecules to enhance the thermal performance of graphene/organic nanocomposites while retaining the intrinsic chemical, thermal, and mechanical properties of pristine graphene. [ABSTRACT FROM AUTHOR]

Organic–inorganic interfaces exist in many natural or synthetic materials, such as mineral–protein interfaces found in bone and epoxy–silica interfaces found in concrete construction. Here, we report a model to predict the intrinsic strength between organic and inorganic materials, based on a molecular dynamics simulation approach combined with the metadynamics method, used to reconstruct the free energy surface between attached and detached states of the bonded system and scaled up to incorporate it into a continuum model. We apply this technique to model an epoxy–silica system that primarily features nonbonded and nondirectional van der Waals and Coulombic chemical interactions. The intrinsic strength between epoxy and silica derived from the molecular level is used to predict the structural behavior of epoxy–silica interface at the macroscopic length scale by invoking a finite element approach using a cohesive zone model which shows a good agreement with existing experimental results. [ABSTRACT FROM PUBLISHER]

There is currently no consensus that the classical perspectiveof electrostatic persistence length (the so-called Odijk–Skolnick–Fixman,or OSF, formulation), derived by equating changes in electrostaticenergy with bending rigidity, is applicable to weak polyelectrolytes.Here, with a focus on polyelectrolyte chains of finite length at asingle scale, we formulate a simple and general theoretical modelfeaturing the electrostatic persistence length, Pe, through the introduction of an electrostatic contourlength, Le, such that the electrostaticenergy balance is applicable to highly flexible charged polyelectrolytes(where the intrinsic stiffness, P0ison the order of Pe). To isolate the effectof ionization, only the salt-free regime is considered. At the upperlimit (relatively rigid molecules), the new formulation convergesto the classical OSF form, while the lower bound (highly flexiblemolecules) approaches proportionality to the Debye screening length,κ–1. In general, the electrostatic persistencecan be described retroactively by the Debye screening, κ–1, and the ratio of electrostatic to intrinsic contourlengths, A/a, complementary to predictivetheoretical formulations. The theory is validated via full atomisticmolecular dynamics simulations of single, isolated model weak polyelectrolytechains in explicit solventspecifically poly(acrylic acid),PAA, and poly(allylamine hydrochloride), PAH, both of which undergosignificant increases in persistence length under ionization. An ensembleof equilibrated polymer states is obtained via temperature assistedsampling, implementing molecular dynamics to drive the polymers intophysically accessible conformations via cyclical temperature fluctuationsand equilibration. [ABSTRACT FROM AUTHOR]

L-3,4-dihydroxyphenylalanine (DOPA) is an amazing biological glue secreted by marine mussels. Through enhanced sampling molecular dynamics, here we demonstrate that proteins with DOPA residues have a strong affinity to a silica surface with an interfacial strength of several hundreds of thousand N/cm2. The mechanism of such strong adhesion is a pair of hydrogen bonds that forms between DOPA and the substrate, enabling enhanced cooperativity as the DOPA residue lays flat on top the surface. Our predicted adhesion force (743 pN) agrees well with experimental measurements (847 ± 157 pN), including the orientation of the DOPA residue on the surface. [ABSTRACT FROM AUTHOR]

Functionalised graphene is an attractive candidate for novel applications in the fabrication of nanodevices or novel composites. Here, we apply molecular dynamics simulations to investigate the assembly of functionalised graphene ribbons and sheets. We illustrate that by designing the location and density of functional groups, the material self-assembles into a defined stable folded structure with lower energy and mechanical properties distinct from the pristine graphene. We show that the hydrogen bonds formed between the functional groups are crucial for this folding process, similar to the driving forces of assembly in many biological protein materials. We propose that such functionalised graphene materials could be employed to realise the bottom-up design of structural materials with tunable mechanical properties as they are expected to achieve multiple mechanical functions under varied conditions. [ABSTRACT FROM AUTHOR]

Abstract: Spider silk is a self-assembling biopolymer that outperforms many known materials in terms of its mechanical performance despite being constructed from simple and inferior building blocks. While experimental studies have shown that the molecular structure of silk has a direct influence on the stiffness, toughness, and failure strength of silk, few molecular-level analyses of the nanostructure of silk assemblies in particular under variations of genetic sequences have been reported. Here we report atomistic-level structures of the MaSp1 protein from the Nephila Clavipes spider dragline silk sequence, obtained using an in silico approach based on replica exchange molecular dynamics (REMD) and explicit water molecular dynamics. We apply this method to study the effects of a systematic variation of the poly-alanine repeat lengths, a parameter controlled by the genetic makeup of silk, on the resulting molecular structure of silk at the nanoscale. Confirming earlier experimental and computational work, a structural analysis reveals that poly-alanine regions in silk predominantly form distinct and orderly -sheet crystal domains while disorderly regions are formed by glycine-rich repeats that consist of -helix type structures and -turns. Our predictions are directly validated against experimental data based on dihedral angle pair calculations presented in Ramachandran plots combined with an analysis of the secondary structure content. The key result of our study is our finding of a strong dependence of the resulting silk nanostructure depending on the poly-alanine length. We observe that the wildtype poly-alanine repeat length of six residues defines a critical minimum length that consistently results in clearly defined -sheet nanocrystals. For poly-alanine lengths below six, the -sheet nanocrystals are not well-defined or not visible at all, while for poly-alanine lengths at and above six, the characteristic nanocomposite structure of silk emerges with no significant improvement of the quality of the -sheet nanocrystal geometry. We present a simple biophysical model that explains these computational observations based on the mechanistic insight gained from the molecular simulations. Our findings set the stage for understanding how variations in the spidroin sequence can be used to engineer the structure and thereby functional properties of this biological superfiber, and present a design strategy for the genetic optimization of spidroins for enhanced mechanical properties. The approach used here may also find application in the design of other self-assembled molecular structures and fibers and in particular biologically inspired or completely synthetic systems. [Copyright &y& Elsevier]

Abstract: Disulfide bonds are important chemical cross-links that control the elasticity of fibrous protein materials such as hair, feather, wool and gluten in breadmaking dough. Here we present a novel computational approach using the first-principles-based ReaxFF reactive force field and demonstrate that this approach can be used to show that the fracture strength of disulfide bonds is decreased under the presence of reducing agents, due to a loss of cross-link stability controlled by the chemical microenvironment. Simulations in explicit solvents and dithiothreitol (DTT) indicate an intermediate step involving weakened elongated bonds, illustrating the tunability of the elasticity, rupture mechanism and strength of proteins. We provide a mechanistic insight into the fracture mechanism of protein disulfide bonds and illustrate the importance of the redox microenvironment, where factors such as accessibility, mechanical strain and local redox potential govern the dominating rupture mechanism and location. The method used here provides a general computational protocol for studying mechanochemical fracture of large-scale protein materials concurrently with experimental efforts. [Copyright &y& Elsevier]

Graphene holds promise as an ultracapacitor due to its high specific surface area and intrinsic capacitance. To exploit both, a maximum surface area must be accessible while the two-dimensional (2D) graphene is detormed to fill volume. Here, we study stable crumpled graphene sheets of different lengths, L, using full atomistic molecular dynamics (MD) and determine a fractal dimension of D ≅ 2.36 ± 0.12, indicating efficient spatial packing. Introduction of defects inducing a transition from membrane-like to amorphous carbon further enhances packing efficiency. Further, variation of self-adhesion energy indicates a predominant role in randomly folded graphene. We determine that approximately 60% of the specific surface area of graphene is solvent accessible once crumpled and can be tuned with applied compression and crumpling. We analyze the solvent accessible surface area (SASA) and approximate the upper bound of free crumpled graphene capacitance to ≈329 F/g. Once crumpled, the achievable capacitance is highly dependent on the confined volume. [ABSTRACT FROM AUTHOR]

Abstract: Carbon nanotubes and graphene have paved the way for the next step in the evolution of carbon materials. Among the novel forms of carbon allotropes is graphyne – a two-dimensional lattice of sp–sp2 -hybridized carbon atoms similar to graphene for which recent progress has been made in synthesizing dehydrobenzoannulene precursors that form subunits of graphyne. Here, we characterize the mechanical properties of single-atomic-layer graphyne sheets by full atomistic first-principles-based ReaxFF molecular dynamics. Atomistic modeling is carried out to determine its mechanical properties for both in-plane and bending deformation including material failure, as well as intersheet adhesion. Unlike graphene, the fracture strain and stress of graphyne depends strongly on the direction of the applied strain and the alignment with carbon triple-bond linkages, ranging from 48.2 to 107.5GPa with ultimate strains of 8.2–13.2%. The intersheet adhesion and out-of-plane bending stiffnesses are comparable to graphene, despite the density of graphyne being only one-half of that of graphene. Unlike graphene, the sparser carbon arrangement in graphyne combined with the directional dependence on the acetylenic groups results in internal stiffening dependent on the direction of applied loading, leading to a nonlinear stress–strain behavior. [Copyright &y& Elsevier]

Abstract: In this paper, the molecular dynamics (MD) simulation technique is described in the context of structural mechanics applications, providing a fundamental understanding of the atomistic approach, and demonstrating its applicability. Atomistic models provide a bottom-up description of material properties and processes, and MD simulation is capable of solving the dynamic evolution of equilibrium and non-equilibrium processes. The applicability of the technique to structural engineering problems is demonstrated through an interface debonding problem in a multi-layered material system usually encountered in composite structures. Interface debonding may lead to a possible premature failure of fiber reinforced polymer (FRP) bonded reinforced concrete (RC) structural elements subjected to moisture. Existing knowledge on meso-scale fracture mechanics may not fully explain the weakening of the interface between concrete and epoxy, when the interface is under moisture; there is a need to study the moisture affected debonding of the interface using a more fundamental approach that incorporates chemistry in the description of materials. The results of the atomistic modeling presented in this paper show that the adhesive strength (in terms of energy) between epoxy and silica is weakened in the presence of water through its interaction with epoxy. This is correlated with the existing meso-scale experimental data. This example demonstrates that MD simulation can be effectively used in studying the durability of the system through an understanding of how materials interact with the environment at the molecular level. In view of the limitation of MD simulation on both length- and time-scales, future research may focus on the development of a bridging technique between MD and finite element modeling (FEM) to be able to correlate the results from the nano- to the macro-scale. [Copyright &y& Elsevier]

Intermediate filaments (IFs) are the key components of cytoskeleton in eukaryotic cells and are critical for cell mechanics. The building block of IFs is a coiled-coil alpha-helical dimer, consisting of several domains that include linkers and other structural discontinuities. One of the discontinuities in the dimer's coiled-coil region is the so-called 'stutter' region. The stutter is a region where a variation of the amino acid sequence pattern from other parts of the alpha-helical domains of the protein is found. It was suggested in earlier works that due to this sequence variation, the perfect coiled-coil arrangement ceases to exist. Here, we show using explicit water molecular dynamics and well-tempered metadynamics that for the coil2 domain of vimentin IFs the stutter is more stable in a non-alpha-helical, unfolded state. This causes a local structural disturbance in the alpha helix, which has a global effect on the nanomechanics of the structure. Our analysis suggests that the stutter features an enhanced tendency to unfolding even under the absence of external forces, implying a much greater structural instability than previously assumed. As a result it features a smaller local bending stiffness than other segments and presents a seed for the initiation of molecular bending and unfolding at large deformation. [ABSTRACT FROM AUTHOR]

Abstract: Collagen is a key constituent in structural materials found in biology, including bone, tendon, skin and blood vessels. Here we report a first molecular level model of an entire overlap region of a C-terminal cross-linked type I collagen assembly and carry out a nanomechanical characterization based on large-scale molecular dynamics simulation in explicit water solvent. Our results show that the deformation mechanism and strength of the structure are greatly affected by the presence of the cross-link, and by the specific loading condition of how the stretching is applied. We find that the presence of a cross-link results in greater strength during deformation as complete intermolecular slip is prevented, and thereby particularly affects larger deformation levels. Conversely, the lack of a cross-link results in the onset of intermolecular sliding during deformation and as a result an overall weaker structure is obtained. Through a detailed analysis of the distribution of deformation by calculating the molecular strain we show that the location of largest strains does not occur around the covalent bonding region, but is found in regions further away from this location. The insight developed from understanding collagenous materials from a fundamental molecular level upwards could play a role in advancing our understanding of physiological and disease states of connective tissues, and also enable the development of new scaffolding material for applications in regenerative medicine and biologically inspired materials. [ABSTRACT FROM AUTHOR]

Intermediate filaments, in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, and play an important role in mechanotransduction as well as in providing mechanical stability to cells at large stretch. The molecular structures, mechanical and dynamical properties of the intermediate filament basic building blocks, the dimer and the tetramer, however, have remained elusive due to persistent experimental challenges owing to the large size and fibrillar geometry of this protein. We have recently reported an atomistic-level model of the human vimentin dimer and tetramer, obtained through a bottom-up approach based on structural optimization via molecular simulation based on an implicit solvent model (Qin et al. in PLoS ONE 2009 4(10):e7294, ). Here we present extensive simulations and structural analyses of the model based on ultra large-scale atomistic-level simulations in an explicit solvent model, with system sizes exceeding 500,000 atoms and simulations carried out at 20 ns time-scales. We report a detailed comparison of the structural and dynamical behavior of this large biomolecular model with implicit and explicit solvent models. Our simulations confirm the stability of the molecular model and provide insight into the dynamical properties of the dimer and tetramer. Specifically, our simulations reveal a heterogeneous distribution of the bending stiffness along the molecular axis with the formation of rather soft and highly flexible hinge-like regions defined by non- alpha-helical linker domains. We report a comparison of Ramachandran maps and the solvent accessible surface area between implicit and explicit solvent models, and compute the persistence length of the dimer and tetramer structure of vimentin intermediate filaments for various subdomains of the protein. Our simulations provide detailed insight into the dynamical properties of the vimentin dimer and tetramer intermediate filament building blocks, which may guide the development of novel coarse-grained models of intermediate filaments, and could also help in understanding assembly mechanisms. [ABSTRACT FROM AUTHOR]

Intermediate filaments (IFs) assembled in vitro from recombinantly expressed proteins have a diameter of 8-12 nm and can reach several micrometers in length. IFs assemble from a soluble pool of subunits, tetramers in the case of vimentin. Upon salt addition, the subunits form first unit length filaments (ULFs) within seconds and then assembly proceeds further by endto- end fusion of ULFs and short filaments. So far, IF subunits have mainly been observed by electron microscopy of glycerol sprayed and rotary metal shadowed specimens. Due to the shear forces during spraying the IF subunits appear generally as straight thin rods. In this study, we used atomic force microscopy (AFM), cryo-electron microscopy (cryo-EM) combined with molecular modeling to investigate the conformation of the subunits of vimentin, desmin and keratin K5/K14 IFs in various conditions. Due to their anisotropic shape the subunits are difficult to image at high resolution by cryo-EM. In order to enhance contrast we used a cryo-negative staining approach. The subunits were clearly identified as thin, slightly curved rods. However the staining agent also forced the subunits to aggregate into two-dimensional networks of dot-like structures. To test this conformational change further, we imaged dried unfixed subunits on mica by AFM revealing a mixture of extended and dot-like conformations. The use of divalent ions such as calcium and magnesium, as well as glutaraldehyde exposure favored compact conformations over elongated ones. These experimental results as well as coarse-grained molecular dynamics simulations of a vimentin tetramer highlight the plasticity of IF subunits. [ABSTRACT FROM AUTHOR]

Abstract: The ability of nature to integrate disparate properties in materials is astounding. Diatoms, unicellular algae that originated approximately 200 million years ago, contain frustules, or silicified cell walls with nanoscale size pores, which are surprisingly tough when compared to bulk silica, which is one of the most brittle materials known. For example, the frustule morphology of the Coscinodiscus sp. diatom consists of a hierarchy of three overlapping porous silica layers that lie on a hexagonal grid, much like a honeycomb within a honeycomb. Here we utilize the porous structure found in diatoms to develop a bioinspired nanoporous material implemented in silicon. By varying the size of the trusses in the constituting silicon nanostructure, we examine associated mechanical properties, as well as fracture and toughening mechanisms by carrying out a series of molecular dynamics simulations with the first principles based reactive force field ReaxFF. We find that by controlling the wall width of the silicon nanostructure, it is possible to significantly enhance the mechanical response of the material, creating a highly deformable (up to 80% strain) and extremely tough material. Our findings provide fundamental insight into transforming a brittle material (s.a. silicon or silica) into a ductile material, through alterations of its structural arrangement at the nanoscale. [Copyright &y& Elsevier]

Alpha-helix based protein networks as they appear in intermediate filaments in the cell's cytoskeleton and the nuclear membrane robustly withstand large deformation of up to several hundred percent strain, despite the presence of structural imperfections or flaws. This performance is not achieved by most synthetic materials, which typically fail at much smaller deformation and show a great sensitivity to the existence of structural flaws. Here we report a series of molecular dynamics simulations with a simple coarse-grained multi-scale model of alpha-helical protein domains, explaining the structural and mechanistic basis for this observed behavior. We find that the characteristic properties of alpha-helix based protein networks are due to the particular nanomechanical properties of their protein constituents, enabling the formation of large dissipative yield regions around structural flaws, effectively protecting the protein network against catastrophic failure. We show that the key for these self protecting properties is a geometric transformation of the crack shape that significantly reduces the stress concentration at corners. Specifically, our analysis demonstrates that the failure strain of alpha-helix based protein networks is insensitive to the presence of structural flaws in the protein network, only marginally affecting their overall strength. Our findings may help to explain the ability of cells to undergo large deformation without catastrophic failure while providing significant mechanical resistance. [ABSTRACT FROM AUTHOR]

Abstract: We report molecular dynamics (MD) simulation and atomistically informed continuum modeling of the nanomechanics of the β-helix protein motif, a key building block of amyloids associated with Alzheimer’s, Huntington’s and prion diseases, forming a nanotube-like protein structure. We find that the β-helix structure is extremely extensible and can sustain tensile deformation up to 800% engineering strain without rupture of the covalently bonded protein backbone. Our atomistic simulation results reveal that the instantaneous strength of the tube is proportional to the rate of H-bond rupture, providing a link between the dynamics of hydrogen bond rupture and the mechanical signature of the protein structure. This finding proves that concurrent as opposed to sequential breaking of bonds leads to higher mechanical resistance, corroborating earlier results found in studies of β-sheet protein domains. Inspired by the beta-helical domain of the needle-like cell puncture device of bacteriophage T4, we carry out compressive loading simulations of the β-helix, and show that this protein motif can withstand extremely large compressive loads, far exceeding the tensile strength. Different mechanical deformation modes under compressive loading are summarized in a deformation map. Our findings illustrate the potential of the β-helix protein motif as an inspiration for nano-scale materials applications, ranging from stiff nanotubes to self-assembling peptide based fibers inspired by amyloids. [Copyright &y& Elsevier]

Vimentin coiled-coil alpha-helical dimers are elementary protein building blocks of intermediate filaments, an important component of the cell’s cytoskeleton that has been shown to control the large-deformation behavior of eukaryotic cells. Here we use a combination of atomistic simulation and continuum theory to model tensile and bending deformation of single alpha-helices as well as coiled-coil double helices of the 2B segment of the vimentin dimer. We find that vimentin dimers can be extended to tensile strains up to 100% at forces below 50 pN, until strain hardening sets in with rapidly rising forces, approaching 8 nN at 200% strain. We systematically explore the differences between single alpha-helical structures and coiled-coil superhelical structures. Based on atomistic simulation, we discover a transition in deformation mechanism under varying pulling rates, resulting in different strength criteria for the unfolding force. Based on an extension of Bell’s theory that describes the dependence of the mechanical unfolding force on the pulling rate, we develop a fully atomistically informed continuum model of the mechanical properties of vimentin coiled-coils that is capable of predicting its nanomechanical behavior over a wide range of deformation rates that include experimental conditions. This model enables us to describe the mechanics of cyclic stretching experiments, suggesting a hysteresis in the force–strain response, leading to energy dissipation as the protein undergoes repeated tensile loading. We find that the dissipated energy increases continuously with increasing pulling rate. Our atomistic and continuum results help to interpret experimental studies that have provided evidence for the significnificance of vimentin intermediate filaments for the large-deformation regime of eukaryotic cells. We conclude that vimentin dimers are superelastic, highly dissipative protein assemblies. [ABSTRACT FROM AUTHOR]

Mineralized collagen fibrils are highly conserved nanostructural building blocks of bone. By a combination of molecular dynamics simulation and theoretical analysis it is shown that the characteristic nanostructure of mineralized collagen fibrils is vital for its high strength and its ability to sustain large deformation, as is relevant to the physiological role of bone, creating a strong and tough material. An analysis of the molecular mechanisms of protein and mineral phases under large deformation of mineralized collagen fibrils reveals a fibrillar toughening mechanism that leads to a manifold increase of energy dissipation compared to fibrils without mineral phase. This fibrillar toughening mechanism increases the resistance to fracture by forming large local yield regions around crack-like defects, a mechanism that protects the integrity of the entire structure by allowing for localized failure. As a consequence, mineralized collagen fibrils are able to tolerate microcracks of the order of several hundred micrometres in size without causing any macroscopic failure of the tissue, which may be essential to enable bone remodelling. The analysis proves that adding nanoscopic small platelets to collagen fibrils increases their Young's modulus and yield strength as well as their fracture strength. We find that mineralized collagen fibrils have a Young's modulus of 6.23 GPa (versus 4.59 GPa for the collagen fibril), yield at a tensile strain of 6.7% (versus 5% for the collagen fibril) and feature a fracture stress of 0.6 GPa (versus 0.3 GPa for the collagen fibril). [ABSTRACT FROM AUTHOR]

Collagen is the most abundant structural protein in humans, with dozens of sequence variants accounting for over 30% of the protein in an animal body. The fibrillar and hierarchical arrangements of collagen are critical in providing mechanical properties with high strength and toughness. Due to this ubiquitous role in human tissues, collagen-based biomaterials are commonly used for tissue repairs and regeneration, requiring chemical and thermal stability over a range of temperatures during materials preparation ex vivo and subsequent utility in vivo. Collagen unfolds from a triple helix to a random coil structure during a temperature interval in which the midpoint or T m is used as a measure to evaluate the thermal stability of the molecules. However, finding a robust framework to facilitate the design of a specific collagen sequence to yield a specific T m remains a challenge, including using conventional molecular dynamics modeling. Here we propose a de novo framework to provide a model that outputs the T m values of input collagen sequences by incorporating deep learning trained on a large data set of collagen sequences and corresponding T m values. By using this framework, we are able to quickly evaluate how mutations and order in the primary sequence affect the stability of collagen triple helices. Specifically, we confirm that mutations to glycines, mutations in the middle of a sequence, and short sequence lengths cause the greatest drop in T m values. [ABSTRACT FROM AUTHOR]

Spider silk is an ultrastrong and extensible self-assembling biopolymer that outperforms the mechanical characteristics of many synthetic materials including steel. Here we report atomic-level structures that represent aggregates of MaSp1 proteins from the N. Clavipes silk sequence based on a bottom-up computational approach using replica exchange molecular dynamics. We discover that poly-alanine regions predominantly form distinct and orderly beta-sheet crystal domains while disorderly structures are formed by poly-glycine repeats, resembling 31-helices. These could be the molecular source of the large semicrystalline fraction observed in silks, and also form the basis of the so-called “prestretched” molecular configuration. Our structures are validated against experimental data based on dihedral angle pair calculations presented in Ramachandran plots, alpha-carbon atomic distances, as well as secondary structure content. [ABSTRACT FROM AUTHOR]

Enamel is the hardest and most resilient tissue in the human body. Enamel includes morphologically aligned, parallel, ∼50 nm wide, microns-long nanocrystals, bundled either into 5-μm-wide rods or their space-filling interrod. The orientation of enamel crystals, however, is poorly understood. Here we show that the crystalline c-axes are homogenously oriented in interrod crystals across most of the enamel layer thickness. Within each rod crystals are not co-oriented with one another or with the long axis of the rod, as previously assumed: the c-axes of adjacent nanocrystals are most frequently mis-oriented by 1°–30°, and this orientation within each rod gradually changes, with an overall angle spread that is never zero, but varies between 30°–90° within one rod. Molecular dynamics simulations demonstrate that the observed mis-orientations of adjacent crystals induce crack deflection. This toughening mechanism contributes to the unique resilience of enamel, which lasts a lifetime under extreme physical and chemical challenges. Enamel is the hardest tissue in the body and has been widely studied, yet aspects of its structure remain unclear. Here, the authors report on a study of the orientation and alignment of enamel crystals and challenge previous assumptions. [ABSTRACT FROM AUTHOR]

Many fibers in biomaterials such as tendon, elastin, or silk feature a nonlinear stiffening behavior of the stress-strain relationship, where the rigidity of the material increases severely as the material is being stretched. Here we show that such nonlinear stiffening is beneficial for a fiber's ability to withstand cracks, leading to a flaw tolerant state in which stress concentrations around cracks are diminished. Our findings, established by molecular mechanics and the derivation of a theoretical scaling law, explain experimentally observed fiber sizes in a range of biomaterials and point to the importance of nonlinear stiffening to enhance their fracture properties. Our study suggests that nonlinear stiffening provides a mechanism by which nanoscale mechanical properties can be scaled up, providing a means towards bioinspired fibrous material and structural design. [ABSTRACT FROM AUTHOR]

Abstract: In addition to being associated with severe degenerative diseases, amyloids show exceptional mechanical properties including great strength, sturdiness and elasticity. However, thus far physical models that explain these properties remain elusive, and our understanding of molecular deformation and failure mechanisms of individual amyloid fibrils is limited. Here we report a series of molecular dynamics simulations, carried out to analyze the mechanical response of two-fold symmetric Aβ(1–40) amyloid fibrils, twisted protein nanofilaments consisting of a H-bonded layered structure. We find a correlation of the mechanical behavior with chemical and nanostructural rearrangements of the fibril during compressive and tensile deformation, showing that the density of H-bonds varies linearly with the measured strain. Further, we find that both compressive and tensile deformation is coupled with torsional deformation, which is manifested in a strong variation of the interlayer twist angle that is found to be proportional to both the applied stress and measured strain. In both compression and tension we observe an increase of the Young''s modulus from 2.34GPa (for less than 0.1% strain in compression and 0.2% strain in tension), to 12.43GPa for compression and 18.05GPa for tension. The moduli at larger deformation are in good agreement with experimental data, where values in the range of 10–20GPa have been reported. Our studies confirm that amyloids feature a very high stiffness, and elucidate the importance of the chemical and structural rearrangements of the fibrils during deformation. [Copyright &y& Elsevier]

Amorphous polymers are one of the primary materials used in pressure sensitive adhesives (PSAs). Their design can be aided by a better understanding of the mechanisms governing the molecular and mesoscopic scale behavior. This work presents a molecular dynamics study of the toughness and failure modes of a coarse-grained polydisperse PSA model in probe peel tests, achieved by varying the crosslinking density and locations. Generally, the toughness of polydisperse PSAs increases at a crosslinking density of 0.5%, compared to the non-crosslinked structure, and declines at higher crosslinking densities, which also changes the failure mode from cohesive to adhesive. The performance is affected by the length of the polymer chains that form crosslinks, although high crosslinking densities make the system less sensitive to effects related to its polydispersity. The results herewith presented display an optimal performance when 35–45% of the particles in the system belong to the giant component of the PSA network. This is achieved at crosslinking densities of 0.5–1.0%, depending on the length of the chains that are allowed to crosslink. [ABSTRACT FROM AUTHOR]

Abstract The inter-chain sliding is the dominant mechanism of energy dissipation within pressure sensitive adhesives (PSAs), and it is significantly affected by the density and location of crosslinks on the polymer chains. The work presents molecular dynamics simulations of the debonding process of PSAs using a coarse-grained model. Introducing crosslinks enhances the connectivity of the polymer network, so that more chains participate in the inter-chain sliding. However, too many crosslinks have a deleterious effect on the adhesive performance, reducing the extent to which the polymer chains can be stretched. This limitation is alleviated by placing the crosslinking sites on the far ends of the polymer chains, so that the whole length of the polymer chains can slide. Our model enables a predictive theoretical framework for better understanding the performance of PSAs at the molecular scale and helps to propose strategies for the de novo bottom-up design of high-performance PSAs. Graphical abstract Image 1 Highlights • There exists an optimized crosslinking density for maximized adhesive performance. • Crosslinking polymer chains at the ends enhance the adhesive performance. • Middle or single-end crosslinking on polymer chains leads to limited improvement. [ABSTRACT FROM AUTHOR]

Graphene has attracted intense attentionto the use in extremeapplications. However, its small thickness facilitates wrinkle formation,and it is not clear how such structural change affects its area-specificcapacitance. Herein, we combine molecular dynamics and continuum mechanics-basedsimulations to study the changes in surface area induced by wrinkles.We find that the high specific surface area of graphene can only beaffected up to 2% regardless of loading conditions, geometry, anddefects. [ABSTRACT FROM AUTHOR]