Mesoscopic Research Articles

Study on the mechanism of carbide precipitation by surface quenching treatment on GCr15 bearing rings based on the phase-field method

In this paper, the thermodynamics database describing Gibbs free energy of FCC phase and M23C6 phase based on Fe-Cr-C ternary alloy was coupled into phase field simulation, and the phase field model was developed on the mesoscopic scale which simulates precipitation, growth and coarsening of M23C6 carbides in FCC austenitic matrix by considering the elastic energy. As the boundary condition of imported phase field calculation, the heat treatment COSMAP software was applied to obtain the macro numerical simulation results of quenching. The phase composition, element distribution, and the evolution including the nucleation, growth and coarsening was simulated by phase field method for the M23C6 carbides in quenching process of GCr15 bearing ring. By means of comparison between the calculation results of phase field simulation and the morphology, quantity and distribution of carbides observed by SEM experiment, this paper present the mechanism on precipitation of micro M23C6 carbides influenced by quenching process parameters, and the experiment verifies the feasibility and accuracy of phase field simulation.

Large-Scale Algorithmic Search Identifies Stiff and Sloppy Dimensions in Synaptic Architectures Consistent With Murine Neocortical Wiring.

Complex systems can be defined by "sloppy" dimensions, meaning that their behavior is unmodified by large changes to specific parameter combinations, and "stiff" dimensions, whose change results in considerable behavioral modification. In the neocortex, sloppiness in synaptic architectures would be crucial to allow for the maintenance of asynchronous irregular spiking dynamics with low firing rates despite a diversity of inputs, states, and short- and long-term plasticity. Using simulations on neural networks with first-order spiking statistics matched to firing in murine visual cortex while varying connectivity parameters, we determined the stiff and sloppy parameters of synaptic architectures across three classes of input (brief, continuous, and cyclical). Algorithmically generated connectivity parameter values drawn from a large portion of the parameter space reveal that specific combinations of excitatory and inhibitory connectivity are stiff and that all other architectural details are sloppy. Stiff dimensions are consistent across input classes with self-sustaining synaptic architectures following brief input occupying a smaller subspace as compared to the other input classes. Experimentally estimated connectivity probabilities from mouse visual cortex are consistent with the connectivity correlations found and fall in the same region of the parameter space as architectures identified algorithmically. This suggests that simple statistical descriptions of spiking dynamics are a sufficient and parsimonious description of neocortical activity when examining structure-function relationships at the mesoscopic scale. Additionally, coarse graining cell types does not prevent the generation of accurate, informative, and interpretable models underlying simple spiking activity. This unbiased investigation provides further evidence of the importance of the interrelationship of excitatory and inhibitory connectivity to establish and maintain stable spiking dynamical regimes in the neocortex.

Advances in Photovoltaic Technologies from Atomic to Device Scale

The question of how energy resources can be efficiently used is likewise of fundamental and technological interest. In this opinion, we give a brief overview on developments of harvesting solar energy across different length scales and address some strategies to tackle economic and ecological challenges, in particular with a view to sustainability and toward a circular economy. On the mesoscopic scale, the emergence of thermodynamic laws in open quantum systems is of central importance and how they can be employed for efficient quantum thermal machines and batteries. The broad tunability of band gaps in quantum dot systems makes them attractive for hybrid photovoltaic devices. Complementary, machine learning-aided band gap engineering and the high-throughput screening of novel materials assist with improving absorption characteristics. On the device scale, hybrid concepts of optical control via metasurfaces enable a multitude of functionalities such as a directed re-emission of embedded photoluminescent materials or field enhancement effects from nanostructures. Advanced techniques in computational nanophotonics concern a topology optimization of nanostructured layers together with multiobjective optimization toward specific light management tasks. On the industrial level, modern manufacturers explore 3D printing and flexible solar cell platforms obtained from roll-to-roll technologies. The remote control of solar parks through applications via the Internet of Things opens up new strategies to expand to difficult terrain where human interaction is only required to a limited extent.

A membrane catalyst synthesized from manganese slag with a high H2O and SO2 tolerance during SCR

Shaped catalysts are actually much more practical than powdered catalysts, and are of great technological importance. However, only few investigations showed the feasibility of fabricating efficient shaped catalysts. For the first time, this work synthesized a membrane catalyst from manganese slag and Teflon filter. The obtained catalyst converted 92.6% of nitrogen oxide (1000 ppm, 1.44 m min−1) at 200 °C in selective catalytic reduction. The activation energy was as low as 13.80 kJ mol−1. Moreover, the membrane catalyst showed a good ability to tolerate 10% H2O + 200 ppm SO2. After detailed characterizations, interstitial Teflon in the membrane catalyst created a wrinkle layer on catalyst surface, increased the hydrophobicity from both mesoscopic and microscopic scales, thus resulting in good tolerance ability for H2O and SO2. Above result puts forward an applicable shaped catalyst to alleviate inevitable physical deactivation derived from sulphate deposition.

Improvement of wetting and necking of nickel-based superalloys fabricated by sequential dual-laser powder bed fusion via particle-scale computational fluid dynamics

The stability of additively manufactured products is mainly affected by their pore defects and surface quality and critical in their applications in various engineering fields. Based on this understanding, a three-dimensional high-fidelity particle-scale computational fluid dynamics (CFD) model for a sequential dual-laser powder bed fusion (SDL_PBF) process was developed in this paper. Using the model, the mechanism of improving the product quality of nickel-based superalloy GH4169 by dual laser sequential scanning strategies was particularly discussed. The effects of laser powers and offsets of sequential dual lasers on the molten pool wetting, pores, and necking were also specially studied, in which the process parameter window was determined through orthogonal experiments. The CFD simulations showed that, when the offsets of the sequential dual lasers are about 3.7 times of the laser radius, the wetting of the molten pool is the best in our test, because the molten pool flows around, resulting in a larger overlapping area. The SDL_PBF with a suitable rear laser source can eliminate the pores and the entrained air formed by the collapse of the recoil depression, which in turn is caused by the front laser. This is because the recoil depression generated by the rear laser can break down the pores caused by the incomplete melting of the front laser, so that the gas in the pores communicates with the air outside, and the liquid in the molten pool is replenished, thereby eliminating the pores and reducing the porosity of the product, which is consistent with the experimental results. In addition, the simulation results showed that the molten pool can flow stably and quickly due to the combined action of strong Marangoni force and steam recoil force as well as weak surface tension in the case of the SDL_PBF with appropriate process parameters, resulting in greatly improved surface quality. Therefore, this work can provide a way for improving multi-laser additive manufacturing of high-performance products. • A particle scale CFD model of SDL_PBF was developed for the first time. • The optimized process window was obtained through orthogonal experiment. • The mechanism of improving product quality was explored at mesoscopic scale.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo.

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

A level-set formulation to simulate diffusive solid/solid phase transformation in polycrystalline metallic materials - Application to austenite decomposition in steels

Numerous full-field numerical methods exist concerning the digital description of polycrystalline materials and the modeling of their evolution during thermomechanical treatments. However, these strategies are globally dedicated to the modeling of recrystallization and grain growth for single-phase materials, or to the modeling of phase transformations without considering recrystallization and related phenomena. A generalized numerical framework capable of making predictions in a multi-phase polycrystalline context while respecting the concomitance of the different microstructural mechanisms is thus of prime interest. A novel finite element level-set based full-field numerical formulation is proposed to principally simulate diffusive solid–solid phase transformation at the mesoscopic scale in the context of two-phase metallic alloys. A global kinetic framework, capable of accounting for other concomitant mechanisms such as recrystallization and grain growth is considered in this numerical model. The proposed numerical framework is shown to be promising through a couple of illustrative 1D and 2D test cases in the context of austenite decomposition in steels and compared with ThermoCalc estimations.

Computational Approaches to Alkaline Anion-Exchange Membranes for Fuel Cell Applications.

Anion-exchange membranes (AEMs) are key components in relatively novel technologies such as alkaline exchange-based membrane fuel cells and AEM-based water electrolyzers. The application of AEMs in these processes is made possible in an alkaline environment, where hydroxide ions (OH-) play the role of charge carriers in the presence of an electrocatalyst and an AEM acts as an electrical insulator blocking the transport of electrons, thereby preventing circuit break. Thus, a good AEM would allow the selective transport of OH- while preventing fuel (e.g., hydrogen, alcohol) crossover. These issues are the subjects of in-depth studies of AEMs-both experimental and theoretical studies-with particular emphasis on the ionic conductivity, ion exchange capacity, fuel crossover, durability, stability, and cell performance properties of AEMs. In this review article, the computational approaches used to investigate the properties of AEMs are discussed. The different modeling length scales are microscopic, mesoscopic, and macroscopic. The microscopic scale entails the ab initio and quantum mechanical modeling of alkaline AEMs. The mesoscopic scale entails using molecular dynamics simulations and other techniques to assess the alkaline electrolyte diffusion in AEMs, OH- transport and chemical degradation in AEMs, ion exchange capacity of an AEM, as well as morphological microstructures. This review shows that computational approaches can be used to investigate different properties of AEMs and sheds light on how the different computational domains can be deployed to investigate AEM properties.

Insight into the anisotropic deformation of landslide sliding zone soil containing directional cracks based on in situ triaxial creep test and numerical simulation

The mechanical behavior of in situ sliding zone soil is unique and is significant for the state identification and prediction of landslides. This study focuses on interpreting the anisotropic deformation observed on the sliding zone soil of the Huangtupo landslide during an in situ triaxial creep test; specifically, the deformation of the A-Surface (towards 35° dip direction) of the soil cube, which points approximately to the landslide sliding orientation, is significantly large. Such anisotropy could be attributed to damaged structure, assumed as pre-existing directional cracks, of the in situ soil. Therefore, a Discrete Element Method (DEM) model containing prefabricated cracks is established to investigate the deforming behavior of compressed soil during in situ creep test on the mesoscopic scale. Results indicated that the specimen's anisotropic deformation is intimately related to the presence of prefabricated cracks. Subjected to the prefabricated cracks, microcracks generated during the loading process of the specimen initiated and developed in a directional way, subsequently forming directed cracks. Then the directed cracks tend to form a complete slip zone. However, due to the insufficient vertical load, the directed cracks were unable to coalesce, and the soil mass did not fail during the in situ creep test. Thereafter, additional load was applied in the simulation model. The directed cracks then merged and a full slip zone formed, and the soil was completely destroyed. As a consequence, the anisotropic characteristics of compressed in situ sliding zone soil can be well explained in view of the cracks development. This study may help perceive the landslide deformation characteristics and facilitate the evaluation and prediction methods of landslide stability.

Synthetic five-wave mixing in an integrated microcavity for visible-telecom entanglement generation

Nonlinear optics processes lie at the heart of photonics and quantum optics for their indispensable role in light sources and information processing. During the past decades, the three- and four-wave mixing (χ(2) and χ(3)) effects have been extensively studied, especially in the micro-/nano-structures by which the photon-photon interaction strength is greatly enhanced. So far, the high-order nonlinearity beyond the χ(3) has rarely been studied in dielectric materials due to their weak intrinsic nonlinear susceptibility, even in high-quality microcavities. Here, an effective five-wave mixing process (χ(4)) is synthesized by incorporating χ(2) and χ(3) processes in a single microcavity. The coherence of the synthetic χ(4) is verified by generating time-energy entangled visible-telecom photon pairs, which requires only one drive laser at the telecom waveband. The photon-pair generation rate from the synthetic process shows an estimated enhancement factor over 500 times upon intrinsic five-wave mixing. Our work demonstrates a universal approach of nonlinear synthesis via photonic structure engineering at the mesoscopic scale rather than material engineering, and thus opens a new avenue for realizing high-order optical nonlinearities and exploring functional photonic devices.

Mesoscopic-scale complexity in macroscopically-uniform plastic flow of an Al0.3CoCrFeNi high-entropy alloy

The concept of a smooth and homogeneous plastic flow of solids is nowadays constantly challenged by various observations of the self-organization of crystal defects on mesoscopic scales pertaining, e.g., to acoustic emission or the evolution of the local strain field. Such investigations would be of particular interest for High-Entropy Alloys (HEAs) characterized by extremely complex microstructures. However, the complexity of their deformation has been only studied in relation to the jerky flow. The present work explores a mesoscale complexity of the macroscopically-smooth plastic flow of an Al0.3CoCrFeNi alloy. An inclusive approach involving various experimental methods and complementary nonlinear analyses allowed to reveal transitions between distinct dynamical regimes, which may be assimilated with noises of different colors, in particular the blue noise that is rarely observed in complex systems, and various kinds of reddened behavior. Such findings provide significant new insights into the micro/macro transition in the deformation behavior of HEAs.

Unveiling the anisotropic fractal magnetic domain structure in bulk crystals of antiskyrmion host (Fe,Ni,Pd)3P by small-angle neutron scattering

Intermetallic Pd-doped (Fe,Ni)3P, which crystallizes in a non-centrosymmetric tetragonal structure with S 4 symmetry, has recently been discovered to host magnetic antiskyrmions, antivortex-like topological spin textures. In this material, uniaxial magnetic anisotropy and dipolar interactions play a significant role, giving rise to finely branched magnetic domain patterns near the surface of bulk crystals, as revealed by a previous magnetic force microscopy (MFM) measurement. However, small-angle neutron scattering (SANS) is a more suitable method for characterizing bulk properties and fractal structures on the mesoscopic length scale. In this study, using SANS and MFM, the magnetic domain structure in bulk single crystals of (Fe0.63Ni0.30Pd0.07)3P is quantitatively investigated. The SANS results demonstrate that the magnetic domain structure exhibits anisotropic fractal character on length scales down to the width of the magnetic domain walls. The fractal features are gradually lost in magnetic fields, and different field dependencies are observed at 300 and 2 K due to a temperature-dependent anisotropy. This study quantifies the fractality of the highly anisotropic magnetic domain structures in an antiskyrmion material, and highlights the versatility of SANS for the study of fractal structures in magnetic systems.

Self-organized bistability on scale-free networks

A dynamical system approaching the first-order transition can exhibit a specific type of critical behavior known as self-organized bistability (SOB). It lies in the fact that the system can permanently switch between the coexisting states under the self-tuning of a control parameter. Many of these systems have a network organization that should be taken into account to understand the underlying processes in detail. In the present paper, we theoretically explore an extension of the SOB concept on the scale-free network under coupling constraints. As provided by the numerical simulations and mean-field approximation in the thermodynamic limit, SOB on scale-free networks originates from facilitated criticality reflected on both macro- and mesoscopic network scales. We establish that the appearance of switches is rooted in spatial self-organization and temporal self-similarity of the network's critical dynamics and replicates extreme properties of epileptic seizure recurrences. Our results, thus, indicate that the proposed conceptual model is suitable to deepen the understanding of emergent collective behavior behind neurological diseases.

Crowd Dynamics: Modeling and Control of Multiagent Systems

This review aims to present recent developments in modeling and control of multiagent systems. A particular focus is set on crowd dynamics characterized by complex interactions among agents, also called social interactions, and large-scale systems. Specifically, in a crowd each individual agent interacts with a field generated by the other agents and the environment. These systems can be modeled at the microscopic scale by ordinary differential equations, while an alternative description at the mesoscopic scale is given by a partial differential equation for the propagation of the probability density of the agents. Control actions can be applied at the individual level as well as at the level of the corresponding fields. This article presents and compares different control types, and the specific application to multilane, multiclass traffic is developed in some detail, showing the main tools at work in a hybrid setting with relevant impacts on autonomous driving.

A 3D mesoscopic frictional cohesive zone model for the steel-concrete interface

It is essential to model the behavior of the interfaces between steel reinforcement and concrete in order to understand the stress transfer between these two components in reinforced concrete structures, which strongly affects the initiation and propagation of cracks. The macroscopic interface models commonly used in structure simulations are functions of various parameters whose physical significance is sometimes not very clear and identification is difficult. That is why the mesoscopic scale is investigated here to improve the understanding of the behavior of the interface when considering both ribbed and smooth bars. A 3D interface model is proposed and implemented to this aim. It takes into account friction and damage by combining a modified cohesive zone model (CZM) based on Tvergaard's approach, and a frictional model in the damaged part of the interface. In this contribution, three dimensional numerical reinforced concrete samples, representing pullout tests, are generated with a detailed geometry of the steel bar. Then, pull-out numerical simulations are performed on the generated samples using an isotropic damage approach with regularization in tension and in compression in order to describe cracking in concrete. The interface model is described and its functionality is verified on a pullout test with smooth bar. The overall response is studied in terms of damage and distribution of the principle stresses near the steel bar, and the applied force versus free end displacements curves which are compared to available experimental data. Finally, a good agreement between simulations and experimental results when using smooth and ribbed bars is obtained.

High-fidelity, high-spatial-resolution diffusion magnetic resonance imaging of ex vivo whole human brain at ultra-high gradient strength with structured low-rank echo-planar imaging ghost correction.

Diffusion magnetic resonance imaging (dMRI) of whole ex vivo human brain specimens enables three-dimensional (3D) mapping of structural connectivity at the mesoscopic scale, providing detailed evaluation of fiber architecture and tissue microstructure at a spatial resolution that is difficult to access in vivo. To account for the short T2 and low diffusivity of fixed tissue, ex vivo dMRI is often acquired using strong diffusion-sensitizing gradients and multishot/segmented 3D echo-planar imaging (EPI) sequences to achieve high spatial resolution. However, the combination of strong diffusion-sensitizing gradients and multishot/segmented EPI readout can result in pronounced ghosting artifacts incurred by nonlinear spatiotemporal variations in the magnetic field produced by eddy currents. Such ghosting artifacts cannot be corrected with conventional correction solutions and pose a significant roadblock to leveraging human MRI scanners with ultrahigh gradients for ex vivo whole-brain dMRI. Here, we show that ghosting-correction approaches that correct for either polarity-related ghosting or shot-to-shot variations in a separate manner are suboptimal for 3D multishot diffusion-weighted EPI experiments in fixed human brain specimens using strong diffusion-sensitizing gradients on the 3-T Connectom MRI scanner, resulting in orientationally biased dMRI estimates. We apply a recently developed advanced k-space reconstruction method based on structured low-rank matrix (SLM) modeling that handles both polarity-related ghosting and shot-to-shot variation simultaneously, to mitigate artifacts in high-angular resolution multishot dMRI data acquired in several fixed human brain specimens at 0.7-0.8-mm isotropic spatial resolution using b-values up to 10,000 s/mm2 and gradient strengths up to 280 mT/m. We demonstrate the improved mapping of diffusion tensor imaging and fiber orientation distribution functions in key neuroanatomical areas distributed across the whole brain using SLM-based EPI ghost correction compared with alternative techniques.

From Hidden Shear‐Elasticity to Opto‐ and Thermo‐Elastic Properties in Confined Polymer Melts and Viscous Liquids

AbstractThe newly identified low frequency elasticity of mesoscopic liquids opens the route to the identification of novel dynamic liquid properties. Two experimental examples illustrating the impact of the liquid elasticity in optics and thermodynamics are presented. It is revealed that at mesoscopic scale, liquids are able to convert the mechanical energy in optical and thermal effects. The fluids are submitted to a low frequency (∼Hz) mechanical shear strain (external stress), thus excluding a coupling with molecular time scales. The dynamic response is probed using two in situ methods accessing in real time optical response of the isotropic phase of liquid crystals and probing the thermal response upon shear deformation. In both cases, a dynamic response is identified: the isotropic phase of liquid crystals exhibits a low frequency dynamic birefringence while ordinary liquids exhibit cold and hot thermal waves synchronous to the low frequency excitation.

Development and benchmarking of numerical model in OpenFOAM® for the prediction of channel segregation during columnar alloy solidification

• Benchmark sn-5 wt%Pb alloy solidification problem is simulated using OpenFOAM solver. • Mesh sensitivity analysis is performed to resolve the flow in channels segregates. • Effect of microsegregation and mushy zone models on channels formation is studied. • Scheil's model predicts more negative and positive segregation than Lever rule. • Inertial drag in mushy zone significantly affects the channel segregates formation. In the past, most of the numerical studies on the prediction of macrosegregation and mesosegregation (e.g. channel type segregation) were performed using in-house codes and commercial software, both of which have limitations such as huge license costs, non-availability for general public research etc. In this study, a dedicated CFD solver is developed in an open-source platform – OpenFOAM® for the prediction and characterization of channel segregates in castings. The solver accounts for the fluid flow, heat transfer, species transport, multiscale segregation, solidification and mushy zone drag phenomena that occur during alloy solidification. The developed solver is extensively validated with the reported benchmarked experimental and numerical results for the sn-Pb alloy solidification. Direct numerical simulations (DNS) are performed to resolve the flow field in and around the channels (which are of mesoscopic length scale) for the first time. It is observed that mesh size ≤ 2 d 2 (secondary dendritic arm spacing) is required to resolve the flow in channels and accurately predict their morphology and locations. Further, the effect of different microsegregation and mushy zone drag models on the segregation and morphology of channel segregates is thoroughly investigated. The predicted extent of negative and positive segregation is found to be more (negative segregation ∼ 7.7 wt%Pb and positive segregation ∼ 18.7 wt%Pb) in Scheil’s microsegregation model compared to Lever rule. Furthermore, the inertial drag in the mushy zone significantly affects the convective transport of solute and thereby the morphology and the number of channel segregates.

Cross-scale identification for friction and wear boundaries of tooth flank of high-feed milling cutter

In the milling process, under the high-efficiency and intermittent cutting loads, the instantaneous posture of the milling cutter and the instantaneous cutter-workpiece engagement are in an unstable state. It is difficult to accurately identify the friction and wear boundary of the cutter tooth flank. It has become an urgent problem to be solved in the life evaluation of milling cutters. The characteristics of the instantaneous posture variation of the milling cutter and the distribution of the thermal-stress mechanical coupling field of the flank of cutter tooth under the vibration were studied. Using the cross-scale load transfer method, the cross-scale relationship between the macro and micro friction loads on the cutter tooth flank was realized. The number of broken valence bonds, the sudden change of potential energy and the attenuation of elastic modulus of the super-cell on the flank of cutter tooth were studied. The mesoscopic scale identification method of the friction and wear boundary feature points of the tooth flank was proposed. The instantaneous and cumulative boundary distribution of friction and wear on the flank of cutter tooth were obtained, and verified by experiments.

Multi-scale modeling of the concrete SHPB test based on DEM-FDM coupling method

The split Hopkinson pressure bar (SHPB) test is the most commonly used method for testing the dynamic mechanical behavior of materials at high strain rates. In this paper, for the SHPB test of concrete, an efficient multi-scale mechanical calculation method based on coupling of discrete element method (DEM) and finite difference method (FDM) is proposed, and SHPB test system for analysis of the macroscopic and microscopic dynamic mechanical properties and damage evolution of concrete under impact loading is established by this coupling method. A three-phase mesoscopic scale model of concrete is constructed by DEM, and the crushability, real geometry-shape, and particle size distribution of aggregates are considered by combining 3D scanning technology and the “ball-clump-cluster” method. Meanwhile, FDM is adopted to simulate the SHPB model, and the “coupling wall” mechanism is applied to realize the signal transmission between the models. On this basis, the stress waves obtained by the direct monitoring method through numerical simulation are basically consistent with those obtained by the theoretical calculation method, which verifies the dynamic characteristics of the SHPB model. Finally, the different types of microcrack propagation are analyzed in the premise of examining the static and dynamic mechanical response of the concrete model. It was found that the distribution of mortar and aggregate microcracks on the outside of the concrete was significantly more than that on the inside due to transverse inertia force, and the superiority of the method in simulating the damage evolution behavior of concrete meso-structural is demonstrated.