Mesoscopic Structures Research Articles

Kernel machine tests of association using extrinsic and intrinsic cluster evaluation metrics

Modeling the network topology of the human brain within the mesoscale has become an increasing focus within the neuroscientific community due to its variation across diverse cognitive processes, in the presence of neuropsychiatric disease or injury, and over the lifespan. Much research has been done on the creation of algorithms to detect these mesoscopic structures, called communities or modules, but less has been done to conduct inference on these structures. The literature on analysis of these community detection algorithms has focused on comparing them within the same subject. These approaches, however, either do not accomodate a more general association between community structure and an outcome or cannot accommodate additional covariates that may confound the association of interest. We propose a semiparametric kernel machine regression model for either a continuous or binary outcome, where covariate effects are modeled parametrically and brain connectivity measures are measured nonparametrically. By incorporating notions of similarity between network community structures into a kernel distance function, the high-dimensional feature space of brain networks, defined on input pairs, can be generalized to non-linear spaces, allowing for a wider class of distance-based algorithms. We evaluate our proposed methodology on both simulated and real datasets.

Numerical dissipation induced by the low-pass filtering in nonlinear gyrokinetic simulations

De-aliasing is an essential procedure for eliminating the aliasing error in nonlinear simulations, such as nonlinear gyrokinetic turbulence simulations. An ideal approach to de-aliasing in the periodic dimension is the Fourier truncation. Finite difference low-pass filtering applied in the non-periodic direction strongly dampens aliasing modes. At the same time, it induces numerical dissipation in the region of the physically realistic solution. It is shown analytically that the long-wave dissipation coefficient is proportional to the (Np−3) power of the wavenumber under desirable constraints satisfying the highest order of accuracy, where Np is the number of filter points. Numerical results after applying the optimized low-pass filtering to the nonlinear gyrokinetic turbulence simulation suggest that the nine-point format preserves intact mesoscopic zonal structures in tokamak plasma, and is therefore suitable for long-time nonlinear turbulence simulations.

Synergistic effects of aggregate-void distribution on low-temperature fracture performance and crack propagation of asphalt concrete under mode I and mode II fracturing

Mesoscopic structures of asphalt concrete play an important role in low-temperature cracking behavior. Existing studies mainly focus on a single feature of the mesoscopic structure, neglecting the spatial distribution and synergistic effects of aggregates and voids, especially in Mode II fracturing. The results show that: in the case of −5 °C and Mode I fracturing, the fracture trend is less affected by the spatial distribution of mesoscopic structure, and tending to spread through aggregate and asphalt mastic along the shortest path. In the case of −5 °C and Mode II fracturing, the crack is easily affected by the distribution of large particle size aggregates in the initial zone, but not by the uneven distribution of voids. In the case of 10 °C and Mode I fracturing, the dominant large aggregate particle size influence on the path is weakened, and the effect of void distribution on the cracking path is perceptibly increased. In the case of 10 °C and Mode II fracturing, the location of large-particle aggregate determines the main streak of fractures, and the uneven distribution of void space determines the occurrence of fracture bending.

Bound states in the continuum and long-lived electronic resonances in mesoscopic structures

Bound states in the continuum and long-lived electronic resonances in mesoscopic structures

Uncertainty relations in thermodynamics of irreversible processes on a mesoscopic scale

Studies of mesoscopic structures have become a leading and rapidly evolving research field ranging from physics, chemistry, and mineralogy to life sciences. The increasing miniaturization of devices with length scales of a few nanometers is leading to radical changes in the realization of new materials and in shedding light on our understanding of the fundamental laws of nature that govern the dynamics of systems at the mesoscopic scale. We investigate thermodynamic processes in small systems in Onsager’s region based on recent experimental results and previous theoretical research. We show that fundamental quantities such as the total entropy production, the thermodynamic variables conjugate to the thermodynamic forces, and the Glansdorff–Prigogine’s dissipative variable may be discretized at the mesoscopic scale. We establish the canonical com- mutation rules (CCRs) valid at the mesoscopic scale. The numerical value of the discretization constant is estimated experimentally. The ultraviolet divergence problem is solved by applying the correspondence principle with Einstein–Prigogine’s fluctuations theory in the limit of macroscopic systems. Examples of quantization of thermodynamic systems out of the Onsager region are currently being finalized.

Structure and dynamics of amphiphilic patchy cubes in a nanoslit under shear.

Patchy nanocubes are intriguing materials with simple shapes and space-filling and multidirectional bonding properties. Previous studies have revealed various mesoscopic structures such as colloidal crystals in the solid regime and rod-like or fractal-like aggregates in the liquid regime of the phase diagram. Recent studies have also shown that mesoscopic structural properties, such as an average cluster size M and orientational order, in amphiphilic nanocube suspensions are associated with macroscopic viscosity changes, mainly owing to differences in cluster shape among patch arrangements. Although many studies have been conducted on the self-assembled structures of nanocubes in bulk, little is known about their self-assembly in nanoscale spaces or structural changes under shear. In this study, we investigated mixtures of one- and two-patch amphiphilic nanocubes confined in two flat parallel plates at rest and under shear using molecular dynamics simulations coupled with multiparticle collision dynamics. We considered two different patch arrangements for the two-patch particles and two different slit widths H to determine the degree of confinement in constant volume fractions in the liquid regime of the phase diagram. We revealed two unique cluster morphologies that have not been previously observed under bulk conditions. At rest, the size of the rod-like aggregates increased with decreasing H, whereas that of the fractal-like aggregates remained constant. Under weak shear with strong confinement, the rod-like aggregates maintained a larger M than the fractal-like aggregates, which were more rigid and maintained a larger M than the rod-like aggregates under bulk conditions.

Higher-order correlations reveal complex memory in temporal hypergraphs

Many real-world complex systems are characterized by interactions in groups that change in time. Current temporal network approaches, however, are unable to describe group dynamics, as they are based on pairwise interactions only. Here, we use time-varying hypergraphs to describe such systems, and we introduce a framework based on higher-order correlations to characterize their temporal organization. The analysis of human interaction data reveals the existence of coherent and interdependent mesoscopic structures, thus capturing aggregation, fragmentation and nucleation processes in social systems. We introduce a model of temporal hypergraphs with non-Markovian group interactions, which reveals complex memory as a fundamental mechanism underlying the emerging pattern in the data.

Three-dimensional hard X-ray ptychographic reflectometry imaging on extended mesoscopic surface structures

Many nanodevices and quantum devices, with their sizes often spanning from millimeters down to sub-nanometer, have intricate low-dimensional, non-uniform, or hierarchical structures on surfaces and interfaces. Since their functionalities are dependent on these structures, high-resolution surface-sensitive characterization becomes imperative to gain a comprehensive understanding of the function–structure relationship. We thus developed hard x-ray ptychographic reflectometry imaging, a new technique that merges the high-resolution two-dimensional imaging capabilities of hard x-ray ptychography for extended objects, with the high-resolution depth profiling capabilities of x-ray reflectivity for layered structures. The synergy of these two methods fully leverages both amplitude and phase information from ptychography reconstruction to not only reveal surface topography and localized structures, such as shapes and electron densities, but also yields statistical details, such as interfacial roughness that is not readily accessible through coherent imaging solely. The hard x-ray ptychographic reflectometry imaging is well-suited for three-dimensional imaging of mesoscopic samples, particularly those comprising planar or layered nanostructures on opaque supports, and could also offer a high-resolution surface metrology and defect analysis on semiconductor devices, such as integrated nanocircuits and lithographic photomasks for microchip fabrications.

Mesoscopic transport in KSTAR plasmas: avalanches and the E × B staircase

Abstract The self-organization is one of the most interesting phenomena in the non-equilibrium complex system, generating ordered structures of different sizes and durations. In tokamak plasmas, various self-organized phenomena have been reported, and two of them, coexisting in the near-marginal (interaction dominant) regime, are avalanches and the E × B staircase. Avalanches mean the ballistic flux propagation event through successive interactions as it propagates, and the E × B staircase means a globally ordered pattern of self-organized zonal flow layers. Various models have been suggested to understand their characteristics and relation, but experimental researches have been mostly limited to the demonstration of their existence. Here we report detailed analyses of their dynamics and statistics and explain their relation. Avalanches influence the formation and the width distribution of the E × B staircase, while the E × B staircase confines avalanches within its mesoscopic width until dissipated or penetrated. Our perspective to consider them the self-organization phenomena enhances our fundamental understanding of them as well as links our findings with the self-organization of mesoscopic structures in various complex systems.

Torsional progressive damage mechanisms in 3-D braided carbon fiber/epoxy resin composite tubes

3-D braided composites are a promising material for manufacturing tubular structures. However, a thorough understanding of their damage mechanisms under torsion is required to maximize their potential applications. The present work constructed a multiscale equivalent model, integrating mesoscopic and homogeneous structures to reveal torsional behavior of 3-D braided carbon fiber/epoxy resin composite tubes. The cumulative failure process, spatial stress distribution and interface damage were calculated to illustrate stress transfer and damage initiation and propagation. It is found that stress varies on the surface and internally within the representative unit cell (RUC). The yarns experience both axial tension parallel to the direction of torsion and axial compression perpendicular to the direction of torsion. The stress difference between them leads to damage initiation and propagation. Interfacial cracking as main damage mode hinders the stress transfer between resin and fiber bundles. The results show that the braided yarn path, axial stress dispersion in two directions and localization of damage effectively impede the torsional damage propagation.

Structures and interactions forming stable shellac-casein nanocomplexes with a pH-cycle

Casein forms diverse structures with functionalities tunable by complexation with surfactants, and shellac is an emerging surfactant. In the present work, molecular and mesoscopic structures of shellac and micellar casein and the underlying interactions after treatment with a pH-cycle were investigated. Dispersions with 0.5 % w/v shellac and various shellac:casein mass ratios were prepared at pH 12.0 to dissolve shellac and dissociate casein micelles, followed by neutralization to pH 7.0 to form complexes. Both covalent and non-covalent (hydrogen bonding, electrostatic, and hydrophobic) interactions contributed to the complex formation. The formed complexes had an average diameter of ~80 nm. The complexation of shellac and casein prevented the precipitation of protonated shellac during neutralization, and dispersions with casein:shellac mass ratios of 2:1 and above were absent of precipitates at pH 7.0. The formed nanocomplexes may have applications for preparing novel colloidal systems and loading lipophilic bioactive compounds.

STZ-Clay: A shear-transformation-zone theory based constitutive model for clay

The shear-transformation-zone (STZ) theory is a mesoscale-based approach that attributes material macroscopic plastic deformation to the flipping, creation, and annihilation of mesoscopic structures known as STZs. In this study, the potential of the STZ theory in soil constitutive modeling is demonstrated through the development of a model coined STZ-Clay, by extending the conventional STZ theory to incorporate two essential characteristics of clay, i.e., plastic volumetric strain and pressure dependence. The STZ-Clay model assumes that the plastic volumetric strain arises from the creation and annihilation of STZs, while the pressure-dependency is accounted for by the dissipation rate function and evolution law of two internal variables, namely STZ density and orientational bias. Remarkably, the STZ-Clay model achieves a unique critical state under different loading paths and reasonably reproduces the influence of consolidation history on the hardening and dilatancy of clay. Overall, the STZ-Clay model offers a fresh perspective for understanding the yielding mechanism and critical state of clay through the lens of mesostructural evolution.

Swelling evolution mechanism for argillaceous slate in a hydrochemical environment

In radioactive waste repositories and tunnel engineering, the near-field groundwater environment is extremely complex, and changes in multiple chemical components are bound to disrupt the long-term stability of soft rock and soil, thus inducing a series of environmental and engineering geological problems. In this study argillaceous slate was selected as the research object and different types of aqueous chemical solutions were prepared. Lateral constraint expansion tests, X-ray diffraction tests, nuclear magnetic resonance tests and scanning electron microscopy tests were then carried out. The expansion characteristics and evolution mechanism of argillaceous slate in a hydrochemical environment are then revealed at the multiscale level, and the internal relationship between the macroscopic expansion of argillaceous slate and the microscopic and mesoscopic structures explored. Finally, based on experimental data and the grey theory, a non-equal step GM(1, N ) grey prediction model was constructed. The results indicated that: (1) the water‒rock physicochemical reactions mainly affect the microstructure evolution of the argillaceous slate expansion process through pore changes, mineral dissolution and ion exchange; (2) there is a certain correlation between the microstructure parameters and the expansion rate, and it was found that pore volume and clay mineral content are the main factors affecting the expansion of soft rocks; and (3) the model verification results show that the non-equal step GM(1, N ) grey prediction model established in this study can effectively predict the expansion trend of soft rocks in different hydrochemical environments. The research findings can provide a reference for the study of the expansion mechanism of soft rocks in complex hydrochemical environments and the disposal of expansion problems. Supplementary material: the Supplementary Figures and Tables are available at https://doi.org/10.6084/m9.figshare.c.7095856

Peptide Self-Assembly into Amyloid Fibrils: Unbiased All-Atom Simulations.

Protein self-assembly plays an important role in biological systems, accounting for the formation of mesoscopic structures that can be highly symmetric as in the capsid of viruses or disordered as in molecular condensates or exhibit a one-dimensional fibrillar morphology as in amyloid fibrils. Deposits of the latter in tissues of individuals with degenerative diseases like Alzheimer's and Parkinson's has motivated extensive efforts to understand the sequence of molecular events accounting for their formation. These studies aim to identify on-pathway intermediates that may be the targets for therapeutic intervention. This detailed knowledge of fibril formation remains obscure, in part due to challenges with experimental analyses of these processes. However, important progress is being achieved for short amyloid peptides due to advances in our ability to perform completely unbiased all-atom simulations of the self-assembly process. This perspective discusses recent developments, their implications, and the hurdles that still need to be overcome to further advance the field.

Moiré effect enables versatile design of topological defects in nematic liquid crystals

Recent advances in surface-patterning techniques of liquid crystals have enabled the precise creation of topological defects, which promise a variety of emergent applications. However, the manipulation and application of these defects remain limited. Here, we harness the moiré effect to engineer topological defects in patterned nematic liquid crystal cells. Specifically, we combine simulation and experiment to examine a nematic cell confined between two substrates of periodic surface anchoring patterns; by rotating one surface against the other, we observe a rich variety of highly tunable, novel topological defects. These defects are shown to guide the three-dimensional self-assembly of colloids, which can conversely impact defects by preventing the self-annihilation of loop-defects through jamming. Finally, we demonstrate that certain nematic moiré cells can engender arbitrary shapes represented by defect regions. As such, the proposed simple twist method enables the design and tuning of mesoscopic structures in liquid crystals, facilitating applications including defect-directed self-assembly, material transport, micro-reactors, photonic devices, and anti-counterfeiting materials.

Capillary Wicking on Heliamphora minor-Mimicking Mesoscopic Trichomes Array.

Liquid spontaneously spreads on rough lyophilic surfaces, and this is driven by capillarity and defined as capillary wicking. Extensive studies on microtextured surfaces have been applied to microfluidics and their corresponding manufacturing. However, the imbibition at mesoscale roughness has seldom been studied due to lacking fabrication techniques. Inspired by the South American pitcher plant Heliamphora minor, which wicks water on its pubescent inside wall for lubrication and drainage, we implemented 3D printing to fabricate a mimetic mesoscopic trichomes array and investigated the high-flux capillary wicking process. Unlike a uniformly thick climbing film on a microtextured surface, the interval filling of millimeter-long and submillimeter-pitched trichomes creates a film of non-uniform thickness. Different from the viscous dissipation that dominated the spreading on microtextured surfaces, we unveiled an inertia-dominated transition regime with mesoscopic wicking dynamics and constructed a scaling law such that the height grows to 2/3 the power of time for various conditions. Finally, we examined the mass transportation inside the non-uniformly thick film, mimicking a plant nutrition supply method, and realized an open system siphon in the film, with the flux saturation condition experimentally determined. This work explores capillary wicking in mesoscopic structures and has potential applications in the design of low-cost high-flux open fluidics.

Hydration properties and mesoscopic structures of different depolymerized konjac glucomannan: Experiments and molecular dynamics simulations

The degradation of Konjac glucomannan (KGM) can greatly change its characterization and impact its applications in the food industry. KGM with varying hydration properties can be diversely utilized in the food sector. To investigate the variability between the structure and properties of KGM with different depolymerized degree (DP), the different depolymerized konjac glucomannan (DKGMx) was prepared by enzymatic digestion. Hydration properties were assessed using solubility index (WSI), water absorption index (WAI), apparent viscosity, hydrophilic angle, hygroscopicity, and rheological properties; thermal stability was evaluated through thermo-physical analysis (TG); changes in structure were analyzed using gel permeation chromatography (GPC), Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction analysis (XRD), scanning electron microscopy imaging (SEM), and molecular dynamics simulation. These findings indicated that that as DP decreased, DKGMx exhibited lower molecular weight, decreased the swelling capacity and apparent viscosity, decreased the hydrophilic angle, increased moisture absorption capacity, and water solubility, altered the crystallized region, decreased thermal stability, and changed the rheological properties. Molecular dynamics simulations revealed that the alteration in degree of polymerization (DP) induced changes in chain flexibility, hydrogen bond count. Molecular simulation and macroscopic experiments elucidated how DP led to changes in the hydration properties of KGM at a mesoscopic scale by altering its chain structure and interaction forces.

Surfactant‐Templated Synthesis of High‐Performance Noble Metal Electrocatalysts: A Case of Dioctadecyldimethylammonium Chloride

Mesoscopic structures of noble metal (NM) nanomaterials are important parameters that remarkably affect physicochemical properties and electrocatalytic performances. To date, various synthesis strategies have been proposed to prepare NM nanomaterials with well‐defined mesoscopic structures. Specifically, amphiphilic surfactants that chemically composed of hydrophobic tail(s) and hydrophilic head(s) have been utilized as functional templates to precisely engineer mesoscopic structures of NM nanomaterials and further optimize their electrochemical performance. Compared with traditional surfactants, dioctadecyldimethylammonium chloride (DODAC) is a functional amphiphilic surfactant that can assemble into vesical and cylinder micelles and thus template precise synthesis of NM nanomaterials with various advanced structures. In this review, recent developments in DODAC‐templated synthesis of high‐performance NM electrocatalysts with a specific focus on the findings in the group are presented. Three kinds of advanced NM mesoscopic structures, including one‐dimensional (1D) nanowires, three‐dimensional (3D) mesoporous nanospheres (MSs), and sophisticated hollow/asymmetric MSs, are described in detail. Meanwhile, the applications in various electrocatalytic reactions are presented to highlight high activity, selectivity, and stability of NM electrocatalysts. This review provides some insights into both synthesis and application exploration of high‐performance NM electrocatalysts by templated synthesis of amphiphilic surfactants.

Isotropic gap formation, localization, and waveguiding in mesoscale Yukawa-potential amorphous structures

Amorphous photonic structures are mesoscopic optical structures described by electrical permittivity distributions with underlying spatial randomness. They offer a unique platform for studying a broad set of electromagnetic phenomena, including transverse Anderson localization, enhanced wave transport, and suppressed diffusion in random media. Despite this, at a more practical level, there is insufficient work on both understanding the nature of optical transport and the conditions conducive to vector-wave localization in these planar structures, as well as their potential applications to photonic nanodevices. In this study, we fill this gap by investigating experimentally and theoretically the characteristics of optical transport in a class of amorphous photonic structures and by demonstrating their use to some basic waveguiding nanostructures. We demonstrate that these 2-D structures have unique isotropic and asymmetric band gaps for in-plane propagation, controlled from first principles by varying the scattering strength and whose properties are elucidated by establishing an analogy between photon and carrier transport in amorphous semiconductors. We further observe Urbach band tails in these random structures and uncover their relation to frequency- and disorder-dependent Anderson-like localized modes through the modified Ioffe-Regel criterion and their mean free path - localization length character. Finally, we illustrate that our amorphous structures can serve as a versatile platform in which photonic devices such as disorder-localized waveguides can be readily implemented.

Nanosphere Chain Model of Magnetic Fluid and Its Dynamic Performance.

The magnetorheological effect is a critically important mechanical property of magnetic fluids. Accurately capturing the macroscopic properties of magnetorheological fluids with elongated particle forms, such as nanosphere chains, remains a challenging task, particularly due to the complexities arising from particle asymmetry. Traditional particle dynamics primarily utilize spherical particles as computational units, but this approach can lead to significant inaccuracies, especially when analyzing nonspherical magnetorheological fluids, due to the neglect of particle asymmetry. In this work, an advanced particle dynamics model has been developed by integrating the rotation and collision of these asymmetric particles, specifically tailored for the configuration of nanosphere chains. This model exhibits a significant reduction in error by a factor of 3.883, compared to conventional particle models. The results demonstrate that alterations in the geometric characteristics of magnetic nanosphere chains can cause changes in mesoscopic structures and magnetic potential energy, thereby influencing the mechanical properties at the macroscopic level. This work has developed an accurate mesoscopic simulation method for calculating chain-type magnetorheological fluids, establishing a connection between mesoscopic structures and macroscopic properties, and unveiling the tremendous potential for accelerating the design of next-generation magnetic fluids using this approach.