Macroscopic Length Scales Research Articles

Adsorption and self-assembly properties of the plant based biosurfactant, Glycyrrhizic acid

There is an increased interest in the use of natural surfactant as replacements for synthetic surfactants due to their biosustainable and biocompatible properties. A category of natural surfactants which are attracting much current interest is the triterpenoid saponins; surface active components found extensively in a wide range of plant species. A wide range of different saponin structures exist, depending upon the plant species they are extracted from; but regardless of the variation in structural details they are all highly surface active glycosides. Greater exploitation and application requires a characterisation and understanding of their basic adsorption and self-assembly properties. HypothesisGlycyrrhizic acid, extracted from Licorice root, is a monodesmosidic triterpenoid saponin. It is widely used in cosmetic and pharmaceutical applications due to its anti-inflammatory properties, and is an ingredient in foods as a sweetener additive. It has an additional attraction due to its gel forming properties at relatively low concentrations. Although it has attracted much recent attention, many of its basic surface active characteristics, adsorption and self-assembly, remain relatively unexplored. How the structure of the Glycyrrhizic acid saponin affects its surface active properties and the impact of gelation on these properties are important considerations, and to investigate these are the focus of the study. ExperimentsIn this paper the adsorption properties at the air–water interface and the self-assembly in solution have been investigated using by neutron reflectivity and small angle neutron scattering; in non-gelling and gelling conditions. FindingsThe adsorption isotherm is determined in water and in the presence of gelling additives, and compared with the adsorption behaviour of other saponins. Gelation has minimal impact on the adsorption; apart from producing a rougher surface with a surface texture on a macroscopic length scale. Globular micelles are formed in aqueous solution with modest anisotropy, and are compared with the structure of other saponin micelles. The addition of gelling agents results in only minimal micelle growth, and the solutions remain isotropic under applied shear flow.

Macroscopic materials assembled from nanoparticle superlattices.

Nanoparticle assembly has been proposed as an ideal means to program the hierarchical organization of a material by using a selection of nanoscale components to build the entire material from the bottom up. Multiscale structural control is highly desirable because chemical composition, nanoscale ordering, microstructure and macroscopic form all affect physical properties1,2. However, the chemical interactions that typically dictate nanoparticle ordering3-5 do not inherently provide any means to manipulate structure at larger length scales6-9. Nanoparticle-based materials development therefore requires processing strategies to tailor micro- and macrostructure without sacrificing their self-assembled nanoscale arrangements. Here we demonstrate methods to rapidly assemble gram-scale quantities of faceted nanoparticle superlattice crystallites that can be further shaped into macroscopic objects in a manner analogous to the sintering of bulk solids. The key advance of this method is that the chemical interactions that govern nanoparticle assembly remain active during the subsequent processing steps, which enables the local nanoscale ordering of the particles to be preserved as the macroscopic materials are formed. The nano- and microstructure of the bulk solids can be tuned as a function of the size, chemical makeup and crystallographic symmetry of the superlattice crystallites, and the micro- and macrostructures can be controlled via subsequent processing steps. This work therefore provides a versatile method to simultaneously control structural organization across the molecular to macroscopic length scales.

The effect of crystallographic orientation and interfaces on thermo-mechanical softening of a martensitic steel

Thermo-mechanical softening forms the basis for hot working of metallic materials. In materials with hierarchical microstructures such as martensite, softening processes can be mediated or restricted by interfaces. In the present study, the operation of three distinct softening mechanisms in P91 martensitic steel during thermo-mechanical processing (TMP) has been investigated. The softening in the present case is found to arise from the interplay between microstructural strain, texture, and phase transformation. Further, softening characteristics vary with the TMP parameters. The manifestation of softening has been explored at the macroscopic, mesoscopic, and microscopic length scales. It has been found that each softening mechanism is differently mediated by the interfaces and is governed by local crystallographic orientation. Thermo-mechanical softening of martensite proceeds through orientation-dependent dynamic recrystallization. The role of specific interfaces in impeding this mechanism has been highlighted. In contrast, TMP of austenite proceeds through interface-mediated softening, combining the phenomena of recrystallization and phase transformation.

Particles to partial differential equations parsimoniously.

Equations governing physico-chemical processes are usually known at microscopic spatial scales, yet one suspects that there exist equations, e.g., in the form of partial differential equations (PDEs), that can explain the system evolution at much coarser, meso-, or macroscopic length scales. Discovering those coarse-grained effective PDEs can lead to considerable savings in computation-intensive tasks like prediction or control. We propose a framework combining artificial neural networks with multiscale computation, in the form of equation-free numerics, for the efficient discovery of such macro-scale PDEs directly from microscopic simulations. Gathering sufficient microscopic data for training neural networks can be computationally prohibitive; equation-free numerics enable a more parsimonious collection of training data by only operating in a sparse subset of the space-time domain. We also propose using a data-driven approach, based on manifold learning (including one using the notion of unnormalized optimal transport of distributions and one based on moment-based description of the distributions), to identify macro-scale dependent variable(s) suitable for the data-driven discovery of said PDEs. This approach can corroborate physically motivated candidate variables or introduce new data-driven variables, in terms of which the coarse-grained effective PDE can be formulated. We illustrate our approach by extracting coarse-grained evolution equations from particle-based simulations with a priori unknown macro-scale variable(s) while significantly reducing the requisite data collection computational effort.

Hyperelastic material properties of axonal fibers in brain white matter

Accurate characterization of the mechanical properties of the human brain at both microscopic and macroscopic length scales is a critical requirement for modeling of traumatic brain injury and brain folding. To date, most experimental studies that employ classical tension/compression/shear tests report the mechanical properties of the brain averaged over both the gray and white matter within the macroscopic regions of interest. As a result, there is a missing correlation between the independent mechanical properties of the microscopic constituent elements and the composite bulk macroscopic mechanical properties of the tissue. This microstructural computational study aims to inversely predict the hyperelastic mechanical properties of the axonal fibers and their surrounding extracellular matrix (ECM) from the bulk tissue's mechanical properties. We develop a representative volume element (RVE) model of the bulk tissue consisting of axonal fibers and ECM with the embedded element technique. A multiobjective optimization technique is implemented to calibrate the model and establish the independent mechanical properties of axonal fibers and ECM based on seven previously reported experimental mechanical tests for bulk white matter tissue from the corpus callosum. The result of the study shows that the discrepancy between the reported values for the elastic behavior of white matter in literature stems from the anisotropy of the tissue at the microscale. The shear modulus of the axonal fiber is seven times larger than the ECM, with axonal fibers that also show greater nonlinearity, contrary to the common assumption that both components exhibit identical nonlinear characteristics. Statement of significanceThe reported mechanical properties of white matter microstructure used in traumatic brain injury or brain mechanics studies vary widely, in some cases by up to two orders of magnitude. Currently, the material parameters of the white matter microstructure are identified by a single loading mode or ultimately two modes of the bulk tissue. The presented material models only define the response of the bulk and homogenized white matter at a macroscopic scale and cannot explicitly capture the connection between the material properties of microstructure and bulk structure. To fill this knowledge gap, our study characterizes the hyperelastic material properties of axonal fibers and ECM using microscale computational modeling and multiobjective optimization. The hyperelastic material properties for axonal fibers and ECM presented in this study are more accurate than previously proposed because they have been optimized using seven or six loading modes of the bulk tissue, which were previously limited to only two of the seven possible loading modes. As such, the predicted values with high accuracy could be used in various computational modeling studies. The systematic characterization of the material properties of the human brain tissue at both macro- and microscales will lead to more accurate computational predictions, which will enable a better understanding of injury criteria, and has a positive impact on the improved development of smart protection systems, and more accurate prediction of brain development and disease progression.

Large and Local Magnetoresistance in a State-of-the-Art Perpendicular Magnetic Medium.

PurposeMagnetotransport properties of granular oxide-segregated CoPtCr films were studied on both macroscopic and microscopic length scales by performing bulk and point-contact magnetoresistance measurements, respectively. Such a perpendicular magnetic medium is used in state-of-the-art hard disc drives and, when combined with magnetotransport phenomena for read/write operations, may lead to a novel concept for magnetic recording with high areal density.Materials and MethodsThe CoPtCr films were deposited by an epitaxy-like sputtering and contained several perpendicularly magnetized granular-media layers with different coercivities; they are very much like the state-of-the-art perpendicular magnetic medium, which can be found in today’s hard disc drives. Magnetoresistive properties of bulk films were assessed by measuring the film resistance in the standard Van der Pauw geometry, while the local transport was probed by the point-contact technique.ResultsThe bulk measurements showed only a negligible magnetoresistance of less than 0.02%. In contrast, the local point-contact measurements revealed giant-magnetoresistance-like changes ΔR in local resistance of the contact R with more than 10,000% ratio ΔR/R.ConclusionThe observed large and local magnetoresistive effect could be tentatively attributed to a tunnel magnetoresistance between oxide-segregated CoPtCr grains with different coercivities. The tunneling picture of electronic transport in our granular medium was confirmed by the observation of tunneling-like current–voltage characteristics of the contacts and bias dependence of the contact magnetoresistance – both the local point-contact resistance and magnetoresistance were found to decrease with the applied dc bias.

Xolography for linear volumetric 3D printing.

The range of applications for additive manufacturing is expanding quickly, including mass production of athletic footwear parts1, dental ceramics2 and aerospace components3 as well as fabrication of microfluidics4, medical devices5, and artificial organs6. The light-induced additive manufacturing techniques7 used are particularly successful owing to their high spatial and temporal control, but such techniques still share the common motifs of pointwise or layered generation, as do stereolithography8, laser powder bed fusion9, and continuous liquid interface production10 and its successors11,12. Volumetric 3D printing13-20 is the next step onward from sequential additive manufacturing methods. Here we introduce xolography, a dual colour technique using photoswitchable photoinitiators to induce local polymerization inside a confined monomer volume upon linear excitation by intersecting light beams of different wavelengths. We demonstrate this concept with a volumetric printer designed to generate three-dimensional objects with complex structural features as well as mechanical and optical functions. Compared to state-of-the-art volumetric printing methods, our technique has a resolution about ten times higher than computed axial lithography without feedback optimization, and a volume generation rate four to five orders of magnitude higher than two-photon photopolymerization. We expect this technology to transform rapid volumetric production for objects at the nanoscopic to macroscopic length scales.

Phase field modelling of microscopic failure in composite laminates

The previous study of the authors on a phase field method for modelling progressive failure in multi-phase materials is further extended in this study to capture microscopic failure processes in composite laminates. The auxiliary phase field model for the regularization of material interface is re-formulated. In the computational model, a small part of the model is built from microscopic length scale to explicitly consider the microstructure of the material while the other area is built from macroscopic length scale to improve the efficiency. Cohesive elements are employed to link the two mesh parts with different length scales and also to capture the intralaminar failure. The existing ABAQUS subroutine “UEL” has been rewritten for the present study due to the introduction of cohesive elements and a BFGS solver is used to improve the iteration stability. The thickness effect of a thin ply made laminate is considered and the crack suppression effect is investigated.

Taking a closer look: A molecular-dynamics investigation of microscopic and apparent dynamic contact angles

HypothesisMolecular dynamics (MD) may be used to investigate the velocity dependence of both the microscopic and apparent dynamic contact angles (θm and θapp). MethodsWe use large-scale MD to explore the steady displacement of a water-like liquid bridge between two molecularly-smooth solid plates under the influence of an external force F0. A coarse-grained model of water reduces the computational demand and the solid-liquid affinity is varied to adjust the equilibrium contact angle θ0. Protocols are devised to measure θm and θapp as a function of contact-line velocity Ucl. FindingsFor all θ0, θm is velocity-dependent and consistent with the molecular-kinetic theory of dynamic wetting (MKT). However, θapp diverges from θm as F0 is increased, especially at the receding meniscus. The behavior of θapp follows that predicted by Voinov: (θapp)3 = (θm)3 + 9Ca·ln(L/Lm), where Ca is the capillary number and L and Lm are suitably-chosen macroscopic and microscopic length scales. For each θ0, there is a critical velocity Ucrit and contact angle θcrit at which θapp→0 and the receding meniscus deposits a liquid film. Setting θapp=0, θm=θcrit and Ucl=Ucrit in the Voinov equation yields the value of L/Lm. The predicted values of θapp then agree well with those measured from the simulations. Since θm obeys the MKT, we have, therefore, demonstrated the utility of the combined model of dynamic wetting proposed by Petrov and Petrov.

Machine Learning in Computational Surface Science and Catalysis: Case Studies on Water and Metal-Oxide Interfaces.

The goal of many computational physicists and chemists is the ability to bridge the gap between atomistic length scales of about a few multiples of an Ångström (Å), i. e., 10−10 m, and meso- or macroscopic length scales by virtue of simulations. The same applies to timescales. Machine learning techniques appear to bring this goal into reach. This work applies the recently published on-the-fly machine-learned force field techniques using a variant of the Gaussian approximation potentials combined with Bayesian regression and molecular dynamics as efficiently implemented in the Vienna ab initio simulation package, VASP. The generation of these force fields follows active-learning schemes. We apply these force fields to simple oxides such as MgO and more complex reducible oxides such as iron oxide, examine their generalizability, and further increase complexity by studying water adsorption on these metal oxide surfaces. We successfully examined surface properties of pristine and reconstructed MgO and Fe3O4 surfaces. However, the accurate description of water–oxide interfaces by machine-learned force fields, especially for iron oxides, remains a field offering plenty of research opportunities.

Topological Interlocking and Geometric Stiffening as Complementary Strategies for Strong Plant Shells.

Many organisms encapsulate their embryos in hard, protective shells. While birds and reptiles largely rely on mineralized shells, plants often develop highly robust lignocellulosic shells. Despite the abundance of hard plant shells, particularly nutshells, it remains unclear which fundamental properties drive their mechanical stability. This multiscale analysis of six prominent (nut)shells (pine, pistachio, walnut, pecan, hazelnut, and macadamia) reveals geometric and structural strengthening mechanisms on the cellular and macroscopic length scales. The strongest tissues, found in walnut and pistachio, exploit the topological interlocking of 3D-puzzle cells and thereby outperform the fiber-reinforced structure of macadamia under tensile and compressive loading. On the macroscopic scale, strengthening occurs via an increased shell thickness, spherical shape, small size, and a lack of extended sutures. These functional interrelations suggest that simple geometric modifications are a powerful and resource-efficient strategy for plants to enhance the fracture resistance of entire shells and their tissues. Understanding the interplay between structure, geometry, and mechanics in hard plant shells provides new perspectives on the evolutionary diversification of hard seed coats, as well as insights for nutshell-based material applications.

1200% enhancement of solar energy conversion by engineering three dimensional arrays of flexible biophotoelectrochemical cells in a fixed footprint encompassed by Johnson solid shaped optical well

Photosynthetic proteins carry out photochemical charge separation with a near-unity quantum efficiency and provide interesting materials for sustainable solar energy conversion in man-made photoelectrochemical devices. The three-dimensional architectures of natural photosynthesisers on both macroscopic and microscopic length scales contrast strikingly with the essentially two-dimensional architectures of commercial photovoltaic devices. In this work we fabricated flexible and semi-transparent bio-photoelectrochemical cells (BPEC) that showed excellent flexibility and durability in response to repeated mechanical deformation. A three-dimensional stack of five such BPECs connected in parallel produced a peak photocurrent of 2900 nA under simulated sunlight in the laboratory and 2400 nA when tested outdoors. Placement of the BPEC stack within either a regular solid reflective well or a Johnson solid reflective well further boosted these photocurrents, computational analysis indicating that the strongest boost that more than doubled output was the consequence of multiple reflections within the Johnson solid that increased the light intensity incident on the BPEC stack. These design features, inspired by natural structures for absorbing and reflecting sunlight, improved the relative performance of the BPECs under non-peak insolation, such that the photocurrent output under natural sunlight was relatively uniform between 10 a.m. and 5 p.m. We discuss how the flexibility, durability and partial transparency of the individual BPECs enable the fabrication of cell arrays with a range of three-dimensional architectures.

Nanostructure and Fracture Behavior of Carbon Nanofiber-Reinforced Cement Using Nanoscale Depth-Sensing Methods.

In recent years, carbon nanofibers have been investigated as a suitable reinforcement for cementitious composites to yield novel multifunctional materials with improved mechanical, electrical, magnetic, and self-sensing behavior. Despite several studies, the interactions between carbon nanofibers and Portland cement hydration products are not fully understood, with significant implications for the mechanical response and the durability at the macroscopic lengthscale. Thus, the research objective is to investigate the influence of carbon nanofibers on the nanostructure and on the distribution of hydration products within Portland cement paste. Portland cement w/c = 0.44 specimens reinforced with 0.0 wt%, 0.1 wt%, and 0.5 wt% CNF by mass fraction of cement are cast using a novel synthesis procedure. A uniform dispersion of carbon nanofibers (CNF) via a multi-step approach: after pre-dispersing carbon nanofibers using ultrasonic energy, the carbon nanofibers are further dispersed using un-hydrated cement particles in high shear mixing and mechanical stirring steps. High-resolution scanning electron microscopy analysis shows that carbon nanofibers fill nanopores and connect calcium–silicate hydrates (C–S–H) grains. Grid nano-indentation testing shows that Carbon nanofibers influence the probability distribution function of the local packing density by inducing a shift towards higher values, = 0.76–0.93. Statistical deconvolution analysis shows that carbon nanofibers result in an increase in the fraction of high-density C–S–H by 6.7% from plain cement to cement + 0.1 wt% CNF and by 10.7% from plain cement to cement + 0.5 wt% CNF. Moreover, CNF lead to an increase in the C–S–H gel porosity and a decrease in both the capillary porosity and the total porosity. Based on scratch testing, adding 0.1 wt% CNF yields a 4.5% increase in fracture toughness and adding 0.5 wt% CNF yields a 7.6% increase in fracture toughness. Finally, micromechanical modelling predicts an increase of respectively 5.97% and 21.78% in the average Young’s modulus following CNF modification at 0.1 wt% CNF and 0.5 wt% CNF levels.

Sponge-derived natural bioactive glass microspheres with self-assembled surface channel arrays opening into a hollow core for bone tissue and controlled drug release applications

Porous, bioactive microspheres have always been a dream material to biomedical scientists for bone regeneration and drug delivery applications due to their interconnectivity, unique pore geometry, encapsulation ability and porosity spanning macroscopic, microscopic and nanoscopic length scales. Extensive efforts have been made to produce such materials synthetically at a great cost of money, time and labor. Herein, naturally-assembled multifunctional, open-channeled and hollow bioactive micro silica spheres (diameter 209.4 ± 38.5 µm) were discovered in a marine sponge (Geodia macandrewii), by peeling the outer surface of the sterrasters using hydrogen fluoride. The obtained micro silica spheres exhibited valuable characteristics such as homogeneously distributed pores, a cavity in the center of the sphere, and channels (approx. 3000) opening from each pore into the central cavity. Simulated body fluid analysis demonstrated the bioactivity of the micro silica spheres; whereas, no bioactivity was recorded for the original untreated sterrasters. The non-cytotoxicity and osteogenic ability of the isolated microspheres were confirmed through osteoblast cell culture. Finally, these silica based porous microspheres were tested for controlled drug release capacity. The spheres showed excellent loading and release abilities for an anti-cancer drug, carboplatin, in simulated solutions and in human cancer cell culture, HeLa, through a real time cell analyzer system. The drug loading capacity of the porous beads was determined as 10.59%. Considering the unique biological and physicochemical properties, these novel bioactive silica spheres, which we name as giant macroporous silica (GMS), are promising materials for a range of applications including bone tissue engineering and drug delivery.

Constructional and functional anatomy of Ediacaran rangeomorphs

AbstractEdiacaran rangeomorphs were the first substantially macroscopic organisms to appear in the fossil record, but their underlying biology remains problematic. Although demonstrably heterotrophic, their current interpretation as osmotrophic consumers of dissolved organic carbon (DOC) is incompatible with the inertial (high Re) and advective (high Pe) fluid dynamics accompanying macroscopic length scales. The key to resolving rangeomorph feeding and physiology lies in their underlying construction. Taphonomic analysis of three-dimensionally preserved Charnia from the White Sea identifies the presence of large, originally water-filled compartments that served both as a hydrostatic exoskeleton and semi-isolated digestion chambers capable of processing recalcitrant substrates, most likely in conjunction with a resident microbiome. At the same time, the hydrodynamically exposed outer surface of macroscopic rangeomorphs would have dramatically enhanced both gas exchange and food delivery. A bag-like epithelium filled with transiently circulated seawater offers an exceptionally efficient means of constructing a simple, DOC-consuming, multicellular heterotroph. Such a body plan is broadly comparable to that of anthozoan cnidarians, minus such derived features as muscle, tentacles and a centralized mouth. Along with other early bag-like fossils, rangeomorphs can be reliably identified as total-group eumetazoans, potentially colonial stem-group cnidarians.

Proton Transport in [BMIM+][BF4-]/Water Mixtures Near the Percolation Threshold.

The incorporation of ionic liquids into existing proton exchange membrane (PEM) materials has been shown to enhance thermal stability and improve conductivity at reduced water content. Because proton transport is dictated by an interplay between vehicular diffusion and the Grotthuss mechanism, it is expected that the nanoscale structure of the resulting ionic liquid/water networks will sensitively influence transport properties. In this work, we study proton transport in [BMIM+][BF4-]/water mixtures of systematically varying water volume fraction, focusing on concentrations near the percolation threshold in which water networks are connected over macroscopic length scales. We utilize reactive molecular dynamics within the multistate empirical valence bond (MS-EVB) framework to explicitly model Grotthuss hopping processes. Excellent agreement with experimental conductivity data is obtained within the Nernst-Einstein approximation, indicating that proton transport proceeds in a largely uncorrelated manner even at pH <0. We additionally study the changing topology of the hydrogen-bonded water network in these mixtures using percolation and graph theory analysis. We find that the proton diffusion coefficient and forward hop rate increase linearly with water content at concentrations ranging from dilute through the percolation threshold; surprisingly, we find no deviation in this trend at the percolation transition. The high concentration of BF4- anions inherently alters the fraction of Eigen and Zundel proton states, producing a net detrimental effect on proton transport rates relative to bulk water. This mechanistic insight is useful for selecting ideal ionic liquid candidates and determining the optimal ionic liquid concentration to incorporate into PEM materials.

On the dynamics of Richtmyer–Meshkov bubbles in unstable three-dimensional interfacial coherent structures with time-dependent acceleration

Richtmyer–Meshkov instability (RMI) plays an important role in many areas of science and engineering, from supernovae and fusion to scramjets and nano-fabrication. Classical RMI is induced by a steady shock and impulsive acceleration, whereas in realistic environments, the acceleration is usually variable. We focus on RMI induced by acceleration with power-law time-dependence and apply group theory to study the dynamics of regular bubbles. For early time linear dynamics, we find the dependence of the growth rate on the initial conditions and show that it is independent of the acceleration parameters. For late-time nonlinear dynamics, we consider regular asymptotic solutions, find a continuous family of such solutions, including their curvature, velocity, Fourier amplitudes, and interfacial shear, and study their stability. For each solution, the interface dynamics is directly linked to the interfacial shear. The non-equilibrium velocity field has intense fluid motion near the interface and effectively no motion in the bulk. The quasi-invariance of the fastest stable solution suggests that the dynamics of nonlinear RM bubbles is characterized by two macroscopic length scales: the wavelength and the amplitude, in agreement with observations. The properties of a number of special solutions are outlined. These are the flat Atwood bubble, the curved Taylor bubble, the minimum shear bubble, the convergence limit bubble, and the critical bubble. We elaborate new theory benchmarks for future experiments and simulations.

Chiral Instabilities and the Onset of Chiral Turbulence in QED Plasmas.

We present a first principles study of chiral plasma instabilities and the onset of chiral turbulence in QED plasmas with strong gauge matter interaction (e^{2}N_{f}=64), far from equilibrium. By performing classical-statistical lattice simulations of the microscopic theory, we show that the generation of strong helical magnetic fields from a helicity imbalance in the fermion sector proceeds via three distinct phases. During the initial linear instability regime the helicity imbalance of the fermion sector causes an exponential growth (damping) of magnetic field modes with right- (left-) handed polarization, for which we extract the characteristic growth (damping) rates. Secondary growth of unstable modes accelerates the helicity transfer from fermions to gauge fields and ultimately leads to the emergence of a self-similar scaling regime characteristic of a decaying turbulence, where magnetic helicity is efficiently transferred to macroscopic length scales. Within this turbulent regime, the evolution of magnetic helicity spectrum can be described by an infrared power spectrum with spectral exponent κ=10.2±0.5 and dynamical scaling exponents α=1.14±0.50 and β=0.37±0.13.

Emergent quantum materials

Abstract

DEM modelling of mini-triaxial test based on one-to-one mapping of sand particles

This paper presents a discrete-element method simulation of mini-triaxial tests on a sand with realistically shaped grains. It compares the results with physical experiments at multiple length scales, including the macroscopic sample length scale and the particle scale. A series of image-processing techniques were utilised to binarise, segment and label the raw data in images obtained from the mini-triaxial test. The images were obtained using an X-ray synchrotron radiation scanner. A spherical harmonic analysis was used to filter the image data and to reconstruct the natural particle morphology. Two parameters, these being the radius ratio of the smallest to largest sphere [Formula: see text] and a characteristic distance [Formula: see text] within the multisphere clump method, were chosen to represent the realistic particle morphology, balancing accuracy against computational cost. A one-to-one discrete-element model, where every particle in the physical experiment has its own numerical twin, was constructed. The discrete-element model was contained by a numerically generated flexible membrane allowing free deformation of the specimen under a prescribed confining stress, as in a physical triaxial test. Finally, attention was given to particle scale properties and their influences on the mechanical response of the discrete-element model. For a given strain rate it was found that shear modulus and friction coefficient affect the initial stiffness, the peak load and the dilation significantly. This study, and the simulation results within it, demonstrate that the proposed modelling approach is capable of reproducing macroscopic (e.g. stiffness, deviatoric stress response and volumetric response) and particle-level (e.g. displacement, rotation and branch vector orientation) behaviours that are very similar to what occurs within physical experiments, validating the effectiveness of the proposed one-to-one mapping technique.