Mesoscale Material Research Articles

The mechanics of air entry of drying-cracking soils: Physical models

Because of common exposure to high temperatures and forced ventilation of geomaterials in energy production and storage, failure mode of these materials often involves intense drying and constrained shrinkage associated cracking. Previous experiments show that drying-cracking occurs when the materials are completely saturated, practically simultaneously with the onset of air entry and start of desaturation. Computer assisted experiments are presented focusing on the phenomenon of air entry into drying granular meso-scale material models. A critical value of capillary adhesion force is assessed associated with the first (and subsequent) unstable air entries (Haines jumps) into drying capillary water of granular materials, as well as the corresponding saturation. The entries are recognized as precursors of drying cracks. The evaporating models with different separations of grains are photographed every 10 s and the images of menisci are computer-processed to follow the evolving water body geometry and cluster saturation. Energy released during subsequent instabilities is also assessed.

Cross-diffusion waves resulting from multiscale, multi-physics instabilities: theory

Abstract. We propose a multiscale approach for coupling multi-physics processes across the scales. The physics is based on discrete phenomena, triggered by local thermo-hydro-mechano-chemical (THMC) instabilities, that cause cross-diffusion (quasi-soliton) acceleration waves. These waves nucleate when the overall stress field is incompatible with accelerations from local feedbacks of generalized THMC thermodynamic forces that trigger generalized thermodynamic fluxes of another kind. Cross-diffusion terms in the 4×4 THMC diffusion matrix are shown to lead to multiple diffusional P and S wave equations as coupled THMC solutions. Uncertainties in the location of meso-scale material instabilities are captured by a wave-scale correlation of probability amplitudes. Cross-diffusional waves have unusual dispersion patterns and, although they assume a solitary state, do not behave like solitons but show complex interactions when they collide. Their characteristic wavenumber and constant speed define mesoscopic internal material time–space relations entirely defined by the coefficients of the coupled THMC reaction–cross-diffusion equations. A companion paper proposes an application of the theory to earthquakes showing that excitation waves triggered by local reactions can, through an extreme effect of a cross-diffusional wave operator, lead to an energy cascade connecting large and small scales and cause solid-state turbulence.

The Xenopus spindle is as dense as the surrounding cytoplasm.

The mitotic spindle is a self-organizing molecular machine, where hundreds of different molecules continuously interact to maintain a dynamic steady state. While our understanding of key molecular players in spindle assembly is significant, it is still largely unknown how the spindle's material properties emerge from molecular interactions. Here, we use correlative fluorescence imaging and label-free three-dimensional optical diffraction tomography (ODT) to measure the Xenopus spindle's mass density distribution. While the spindle has been commonly referred to as a denser phase of the cytoplasm, we find that it has the same density as its surrounding, which makes it neutrally buoyant. Molecular perturbations suggest that spindle mass density can be modulated by tuning microtubule nucleation and dynamics. Together, ODT provides direct, unbiased, and quantitative information of the spindle's emergent physical properties-essential to advance predictive frameworks of spindle assembly and function.

Ballistic Penetration Analysis of Soft Laminated Composites Using Sublaminate Mesoscale Modeling

Ballistic impact mitigation requires the development of protective armor applications from composite material systems with good energy absorption and penetration resistance against threats, e.g., metallic projectiles. In this aim, high-strength and high-stiffness soft fibrous composite materials (such as ultra-high molecular weight polyethylene—UHMWPE) are often used. The high specific strength feature is one of the main reasons for using these soft composite systems in ballistic impact applications. In the present investigation, experimental and computational finite element (FE) studies were carried out to investigate the ballistic behaviors of these soft layered composite targets. To this end, a new FE multi-scale analysis framework for ballistic simulations is offered. The proposed analysis presents a new meso-scale sublaminate material model, which is applied to Dyneema® cross-ply laminate in order to predict its behavior under ballistic impact. The sublaminate model is implemented within an explicit dynamic FE code to simulate the continuum response in each element. The sublaminate model assumes a through-thickness periodic stacking of repeated cross-ply configuration. In addition, a cohesive layer is introduced in the sublaminate model in order to simulate the delamination effect leading to the subsequent degradation and deletion of the elements. This new approach eliminates the widely used costly computational approach of using explicit cohesive elements installed at pre-specified potential delamination paths between the layers. Furthermore, in-plane damage modes (such as fiber tensile, and out-of-plane shearing) are also accounted for by employing failure criteria and strain-softening. The obtained quantitative results of ballistic impact simulations show good correlation when compared to a relatively wide range of experiments. Moreover, the simulations include evidence of capturing the main energy absorption mechanisms under high-velocity impact. The proposed modeling approach can be used as a useful armor design tool.

Numerical prediction of the ballistic performance of hygrothermally aged CFRP laminates using a multi-scale modelling approach

A multi-scale modelling strategy is proposed to investigate the potential effects of hygrothermal ageing on the ballistic performance of CFRP laminates. At the micro-scale, damage evolution due to cyclic hygrothermal loads is simulated on a representative microstructure using an adapted fatigue damage law. Then, the results of the micro-mechanical analysis are used to measure the predicted transverse crack density and calibrate a meso-scale material model with the effects of micro-scale damage. Finally, a meso-scale impact model is generated with seeded transverse cracks at the predicted crack density and the calibrated material properties from the homogenisation step, which allows for the performance of the laminate to be compared at different stages of hygrothermal ageing damage.

Meso–macro-scale computational analysis of boron nitride nanotube-reinforced aluminium and epoxy nanocomposites: A case study on crack propagation

In this paper, an outline of mean-field homogenization and fracture toughness of boron nitride nanotube-reinforced aluminium and epoxy composites have been presented. The meso-scale material modelling has been achieved using Mori-Tanaka and double inclusion homogenization schemes. To examine the effectiveness of Mori-Tanaka and double inclusion schemes, a comparison has been drawn with the rule of mixture. Meso-scale numerical results of boron nitride nanotube-reinforced aluminium and epoxy composites are presented for various design parameters such as aspect ratio and volume fraction of boron nitride nanotubes. The validation studies of the developed transversely isotropic composites model have been documented with the experiments performed and existing literature. Finally, macro-scale fracture toughness simulations incorporating the transversely isotropic properties have been performed using the domain integral method. It is observed that aluminium and epoxy with elastoplastic and viscoelastic nature, respectively, have shown a significant effect on the fracture properties of the composites.

From the editors

This issue of the Magazine presents articles related to cable diagnostics and technology. Two of them, written by authors from Canada and Australia, summarize experiences and research activities on the use of dielectric response spectroscopy for diagnoses of insulation condition in medium voltage cables. The third article presents work performed in the USA on development of superconducting gas insulated cable system for power transmission at voltage level above 10 kV. Finally, the fourth article, from Norway, raises the importance of mesoscale material effect on the performance of cable joints.

Bayesian identification and model comparison for random property fields derived from material microstructure

This paper provides a Bayesian framework for determining the spatial variability of the apparent material properties of two-phase composites. Bayesian analysis is applied to learn the parameters of the random fields that characterize the mesoscale material properties using computer-simulated images of the material microstructure. The information from such images is used to define the likelihood function of the random field parameters given the homogenized microscale data. The uncertainty in the parameter estimates is quantified through determining their full posterior distribution instead of a point estimate by application of an adaptive sampling algorithm. In addition, the Bayesian approach allows for assessing the plausibility of different correlation models belonging to the Matérn class through computing their respective marginal likelihoods for various choices of the smoothness parameter. The framework is applied to a composite material with large inclusion/matrix stiffness ratio and useful conclusions are derived with regard to the most appropriate correlation model and its parameters.

Meso-scale cracking behavior of Cement Treated Base material

Although much attention had been paid to the study of macroscopic performance of Cement Treated Base (CTB), the meso-scale study of this heterogeneous and quasi-brittle material is rather limited. In this paper, a two-dimensional (2D) meso-scale crack propagation model of CTB assumed as a three-phase material composed of aggregate, cement mortar and interface transitional zones (ITZ) was developed through Finite Element method (FEM) with cohesive elements. Digital image processing (DIP) methods and vectorization processing were utilized to create a 2D heterogeneous numerical fracture model using the digital image obtained through scanning. The zero-thickness cohesive elements with traction-separation laws were inserted into both the cement mortar and the aggregate–cement interfaces to simulate the potential micro-crack in the cohesive zone model (CZM). Nano-indentation tests and inverse analysis were employed to determine the material parameters of model. Different cohesive parameters were obtained for the crack propagation of FE models to study the meso-scale material properties. Analysis results showed that the load-displacement curves, crack geometry, and tensile strength based on the numerical simulation agreed with those obtained from laboratory tests.

Mesoscale modeling of hypervelocity impacts using the CTH shock physics code

Material fragmentation after a hypervelocity impact is important to predictive electro-optical and infrared (EO/IR) modeling. Successful comparisons with data require that hot, submicron fragments are generated in such impacts; however, experimental data has so far been unable to produce fragments of this scale. The purpose of this work was to investigate how modeling assumptions of macro-scale, bulk materials might influence the generation of debris in hypervelocity impacts and ultimately the predicted EO/IR signatures of these debris clouds. Sphere-on-plate impact simulations simplified the comparison of different modeling approaches. In one set of simulations, materials were modeled with the traditional, bulk approach. Those results were compared to simulations run with the mesoscale material grain structure explicitly modeled. This study focused on the comparison of two parameters that are tied directly to the EO/IR signature: strain rate at failure (a proxy for debris fragment size) and material temperature. Interfaces between grains, here due to void insertion, resulted in the most notable change in both the strain rate at failure and material temperature. Shock reflections from grain-void interfaces induced higher strain rates and material temperatures, and it is expected that similar effects may be produced from inclusions or dislocations in real materials. Thus, interfaces within a material may play an important role in producing smaller hot debris fragments that support the EO/IR predictive models of hypervelocity impacts.

A constitutive model for fiber kinking: Formulation, finite element implementation, and verification

A new mesoscale material model is proposed to analyze structures that fail by the fiber kinking damage mode. The model is formulated following the fiber kinking theory such that the interaction of shear nonlinearity and fiber rotation are tracked throughout the loading history. The model is implemented as a user-defined material in a commercial finite element code. A decomposition algorithm is introduced in the finite element implementation to decouple the mesh size and kink band width. To evaluate the assumptions of the mesoscale model, the results were compared with those of a high-fidelity micromechanical model. A direct comparison between the two models shows remarkable correlation, providing evidence that the key features of the fiber kinking phenomenon are appropriately accounted for in the mesoscale model. The model is demonstrated for a simple unnotched compression configuration. The results show that the model is successful at representing the kinematics of fiber kinking.

Liquid-Liquid Phase Separation Is Driven by Large-Scale Conformational Unwinding and Fluctuations of Intrinsically Disordered Protein Molecules.

Liquid-liquid phase separation occurs via a multitude of transient, noncovalent, and intermolecular interactions resulting in phase transition of intrinsically disordered proteins/regions (IDPs/IDRs) and other biopolymers into mesoscopic, dynamic, nonstoichiometric, and supramolecular condensates. Here we present a unique case to demonstrate that unusual conformational expansion events coupled with solvation and fluctuations drive phase separation of tau, an IDP associated with Alzheimer's disease. Using intramolecular excimer emission as a powerful proximity readout, we show the unraveling of polypeptide chains within the protein-rich interior environment that can promote critical interchain contacts. Using highly sensitive picosecond time-resolved fluorescence depolarization measurements, we directly capture rapid large-amplitude torsional fluctuations in the extended chains that can control the relay of making-and-breaking of noncovalent intermolecular contacts maintaining the internal fluidity. The interplay of these key molecular parameters can be of prime importance in modulating the mesoscale material property of liquid-like condensates and their maturation into pathological gel-like and solid-like aggregates.

Effect of Volume Element Geometry on Convergence to a Representative Volume

To accurately simulate fracture, it is necessary to account for small-scale randomness in the properties of a material. Apparent properties of statistical volume element (SVE) can be characterized below the scale of a representative volume element (RVE). Apparent properties cannot be defined uniquely for an SVE, in the manner that unique effective properties can be defined for an RVE. Both constitutive behavior and material strength properties in SVE must be statistically characterized. The geometrical partitioning method can be critically important in affecting the probability distributions of mesoscale material property parameters. Here, a Voronoi tessellation-based partitioning scheme is applied to generate SVE. Resulting material property distributions are compared with those from SVE generated by square partitioning. The proportional limit stress of the SVE is used to approximate SVE strength. Superposition of elastic results is used to obtain failure strength distributions from boundary conditions at variable angles of loading.

Dynamic DNA material with emergent locomotion behavior powered by artificial metabolism.

Metabolism is a key process that makes life alive-the combination of anabolism and catabolism sustains life by a continuous flux of matter and energy. In other words, the materials comprising life are synthesized, assembled, dissipated, and decomposed autonomously in a controlled, hierarchical manner using biological processes. Although some biological approaches for creating dynamic materials have been reported, the construction of such materials by mimicking metabolism from scratch based on bioengineering has not yet been achieved. Various chemical approaches, especially dissipative assemblies, allow the construction of dynamic materials in a synthetic fashion, analogous to part of metabolism. Inspired by these approaches, here, we report a bottom-up construction of dynamic biomaterials powered by artificial metabolism, representing a combination of irreversible biosynthesis and dissipative assembly processes. An emergent locomotion behavior resembling a slime mold was programmed with this material by using an abstract design model similar to mechanical systems. Dynamic properties, such as autonomous pattern generation and continuous polarized regeneration, enabled locomotion along the designated tracks against a constant flow. Furthermore, an emergent racing behavior of two locomotive bodies was achieved by expanding the program. Other applications, including pathogen detection and hybrid nanomaterials, illustrated further potential use of this material. Dynamic biomaterials powered by artificial metabolism could provide a previously unexplored route to realize "artificial" biological systems with regenerating and self-sustaining characteristics.

Exploring the 3D architectures of deep material network in data-driven multiscale mechanics

This paper extends the deep material network (DMN) proposed by Liu et al. (2019) to tackle general 3-dimensional (3D) problems with arbitrary material and geometric nonlinearities. It discovers a new way of describing multiscale heterogeneous materials by a multi-layer network structure and mechanistic building blocks. The data-driven framework of DMN is discussed in detail about the offline training and online extrapolation stages. Analytical solutions of the 3D building block with a two-layer structure in both small- and finite-strain formulations are derived based on interfacial equilibrium conditions and kinematic constraints. With linear elastic data generated by direct numerical simulations on a representative volume element (RVE), the network can be effectively trained in the offline stage using stochastic gradient descent and advanced model compression algorithms. Efficiency and accuracy of DMN on addressing the long-standing 3D RVE challenges with complex morphologies and material laws are validated through numerical experiments, including 1) hyperelastic particle-reinforced rubber composite with Mullins effect; 2) polycrystalline materials with rate-dependent crystal plasticity; 3) carbon fiber reinforced polymer (CFRP) composites with fiber anisotropic elasticity and matrix plasticity. In particular, we demonstrate a three-scale homogenization procedure of CFRP system by concatenating the microscale and mesoscale material networks. The complete learning and extrapolation procedures of DMN establish a reliable data-driven framework for multiscale material modeling and design.

Nonequilibrium Monte Carlo simulations of entangled polymer melts under steady shear flow.

We present a nonequilibrium Monte Carlo (MC) methodology based on expanded nonequilibrium thermodynamic formalism to simulate entangled polymeric materials undergoing steady shear flow. Motivated by the standard kinetic theory for entangled polymers, a second-rank symmetric conformation tensor based on the entanglement segment vector was adopted in the expanded statistical-ensemble based MC method as the nonequilibrium structural variable that properly represents the deformed structure of the system by the flow. The corresponding (second-rank symmetric) conjugate thermodynamic force variable was introduced to simulate an external flow field. As a test case, we applied the GENERIC MC to C400H802 entangled linear polyethylene melts in a wide range of shear rates. Detailed analysis of the GENERIC MC results for various structural and rheological properties (such as chain size, chain orientation, mesoscale chain configuration, topological properties, and material functions) was carried out via direct comparison with the corresponding NEMD results. Overall, the GENERIC MC is shown to predict the general trends of the nonequilibrium properties of polymer systems reasonably for a wide range of flow strengths (i.e., 0.5 ≤ De ≤ 540). In conjunction with NEMD, the present MC method can thus be used to extract fundamental thermodynamic information (nonequilibrium entropy and free energy functions) of entangled polymeric systems under various flow types. Despite the general consistency between the GENERIC MC and NEMD results, some quantitative discrepancies appear in the intermediate-to-strong flow regime. This behavior stems from the inherent mean-field nature of the MC force field which is applied to the individual entanglement segments independently and uniformly along the chain, without accounting for any flow-induced structural or dynamical correlations between segments.

Enhancement of a meso-scale material model for nonlinear elastic finite element computations of plain-woven fabric membrane structures

Due to their structure of crossed yarns embedded in coating, woven fabric membranes are characterised by a highly nonlinear stress-strain behaviour. In order to determine an accurate structural response of membrane structures, a suitable description of the material behaviour is required. Typical phenomenological material models like linear-elastic orthotropic models only allow a limited determination of the real material behaviour. A more accurate approach becomes evident by focusing on the meso-scale, which reveals an inhomogeneous however periodic structure of woven fabrics. The present work focuses on an established meso-scale model. The novelty of this work is an enhancement of this model with regard to the coating stiffness. By performing an inverse process of parameter identification using a state-of-the-art Levenberg-Marquardt algorithm, a close fit w.r.t. measured data from a common biaxial test is shown and compared to results applying established models. Subsequently, the enhanced meso-scale model is processed into a multi-scale model and is implemented as a material law into a finite element program. Within finite element analyses of an exemplary full scale membrane structure by using the implemented material model as well as by using established material models, the results are compared and discussed.

Aerosol jet printed silver nanowire transparent electrode for flexible electronic application

Aerosol jet printing technology enables fine feature deposition of electronic materials onto low-temperature, non-planar substrates without masks. In this work, silver nanowires (AgNWs) are proposed to be printed into transparent flexible electrodes using a Maskless Mesoscale Material Deposition Aerosol Jet® printing system on a glass substrate. The influence of the most significant process parameters, including printing cycles, printing speed, and nozzle size, on the performance of AgNW electrodes was systematically studied. The morphologies of printed patterns were characterized by scanning electron microscopy, and the transmittance was evaluated using an ultraviolet-visible spectrophotometer. Under optimum conditions, high transparent AgNW electrodes with a sheet resistance of 57.68 Ω/sq and a linewidth of 50.9 μm were obtained, which is an important step towards a higher performance goal for flexible electronic applications.

Voronoi tessellation based statistical volume element characterization for use in fracture modeling

Accurate characterization of random heterogeneity in a material microstructure is essential to the accurate characterization of complex fracture patterns that result from random crack nucleation and propagation. It is also important to characterize microstructural behavior at intermediate scales, between the length scale of material heterogeneity and the scale of a Representative Volume Element (RVE). The availability of material property data at multiple scales will ultimately allow adjustment of computational cost and level of accuracy with respect to resolution of complex fracture patterns. Statistical Volume Elements (SVE) may be generated at the mesoscale by partitioning an RVE. SVE provide a probabilistic characterization of material heterogeneity, while also presenting a continuum representation of apparent properties. Appropriate definition of an SVE requires modeling choices, such as partitioning methods and size. An essential modeling assumption is the choice of loading condition used to approximate SVE apparent behavior, since the constitutive properties of an SVE are not necessarily invariant with respect to the boundary condition applied. This work develops a Voronoi tessellation based partitioning scheme applied at various length scales, for heterogeneous materials with various contrast ratios. Results show the variability of failure strength for a given SVE as a function of loading direction. Results of the mesoscale material property analysis are implemented in an asynchronous spacetime discontinuous Galerkin (aSDG) finite element based fracture model.

Time-resolved diffraction of shock-released SiO2 and diaplectic glass formation

Understanding how rock-forming minerals transform under shock loading is critical for modeling collisions between planetary bodies, interpreting the significance of shock features in minerals and for using them as diagnostic indicators of impact conditions, such as shock pressure. To date, our understanding of the formation processes experienced by shocked materials is based exclusively on ex situ analyses of recovered samples. Formation mechanisms and origins of commonly observed mesoscale material features, such as diaplectic (i.e., shocked) glass, remain therefore controversial and unresolvable. Here we show in situ pump-probe X-ray diffraction measurements on fused silica crystallizing to stishovite on shock compression and then converting to an amorphous phase on shock release in only 2.4 ns from 33.6 GPa. Recovered glass fragments suggest permanent densification. These observations of real-time diaplectic glass formation attest that it is a back-transformation product of stishovite with implications for revising traditional shock metamorphism stages.