Packing Configuration Research Articles

Predicting the elasto-plastic response of short fiber reinforced composites using a computationally efficient multi-scale framework based on physical matrix properties

Predicting the nonlinear mechanical response of short fiber reinforced composites (SFRCs) is a crucial and challenging task. In this paper, a computationally efficient multi-scale strategy is proposed to predict the anisotropic elasto-plastic behavior of SFRCs using the intrinsic mechanical behavior of the pure polymer and fibers without the requirements for reverse engineering. In doing so, different simple unit cells are first examined to find the one that can adequately describe the nonlinear mechanical response of SFRCs' representative volume elements (RVE) with aligned fibers. Considering the effects of packing configuration, fiber aspect ratio, volume fraction and material properties, the performance of different unit cells is investigated. Then, the homogenized mechanical responses of unit cells are linked to Hill's anisotropic plasticity model to correlate the mechanical response of the suggested unit cell to the continuum domain. Using the pseudo-grain approach and a numerical orientation averaging framework, the effects of fiber misalignment are taken into account. A multi-step homogenization strategy is also employed to consider the variation of fiber orientation tensor and volume fraction through the thickness. Finally, the validity and robustness of the proposed multi-scale strategy are extensively investigated based on the RVE-generated results and the available experimental observations.

Integrated CO2 capture and methanation from the intermediate-temperature flue gas on dual functional hybrids of AMS/CaMgO||NixCoy

The integrated CO2 capture and conversion (iCCC) technology has caused more and more interests for the Carbon Neutrality as it can make full use of the heat of high-temperature or intermediate-temperature flue gas to achieve efficient CO2 chemical utilization, avoiding additional costs for CO2 transportation and producing value-added chemicals. Herein, we developed the dual functional adsorbent||catalyst hybrids of alkali metal salts (AMS)/CaMgO||NixCoy for the integrated CO2 capture and methanation (iCCC-methanation) at the intermediate temperature of 350 °C. By loading alkali metal salts into porous CaMgO composites, the AMS/CaMgO shows a stable CO2 adsorption performance with an excellent saturated capacity of 12.8 mmol g−1 at 350 °C. Meanwhile, CO2 and H2 can be simultaneously activated on the catalytic active sites of Co and Ni on the bimetal NixCoy alloy catalysts for the efficient methanation. After the temperature matching between CO2 capture and conversion, an excellent iCCC-methanation performance with the CO2 conversion efficiency near 93.4 % and CH4 selectivity of 88 % are achieved in one dual-bed column at 350 °C. More importantly, the products selectivity between CH4 and CO can be modulated by altering the packing configurations of sorbent/catalyst in the fixed-bed column, such as the dual-bed mode, multilayer mode, and physical mixing mode. Based on the elementary consecutive dynamic law, we revealed that the distance between the adsorption site and catalytic site plays a critical role for the CO2 hydrogenation. The superior performance of this iCCC-methanation demonstrates the importance of the synergistic promotions between the CO2 capture and in-situ conversion, as well as its promising application in CO2 emission control.

On the effect of flow regime and pore structure on the flow signatures in porous media

In this study, lattice Boltzmann method (LBM) is utilized for three-dimensional simulation of fluid flow through two porous structures, consisting of grains with the same diameter: (i) a homogeneous porous domain, in which the grains are placed with a simple cubic packing configuration, and (ii) a randomly packed porous domain. An ultra-fine mesh size is considered to perform the simulations in three orders of magnitude of Reynolds number (Re), covering laminar to turbulent flow regimes, and capture different flow signatures. Pore velocity fields are derived, and their sample probability density functions (PDF) are analyzed vs time to investigate the dynamics of the flow. The analysis of the PDFs clearly shows that stagnant zones play a significant role in the formation of the pore flow fields, manifested by multimodal PDFs, and the distribution of the velocities in porous media at various Re cannot be characterized by a single PDF model regardless of the pore structure. While the velocities at the stagnant regions and in the vicinity of the solid boundaries are primarily affected by the viscous forces and exhibit a power-law PDF at different Re, the velocities in the main (preferential) flow pathways away from the boundaries are shown to be influenced by the inertial forces, hence having an exponential PDF when Re is low. At high Re, however, depending on the tortuosity of the porous structure, the velocities may exhibit an exponential or even Laplace PDF.

A quasi-physical method for random packing of spherical particles

In this work, a quasi-physical method for the random packing of spherical particles based on the equivalent spring structure and the principle of force equilibrium is proposed. The model is inspired by a meshing method “Distmesh”. For the purpose of generating a feasible packing, the proposed model calculates the displacements of each particle based on physical principles and disregards forces that may not help with convergence, thus offering a natural and possibly fast route towards the final packing configuration. The packing densities predicted by the proposed method are in good agreement with those predicted by other methods and the experimental results. Finally, the topological properties of the packing of particles with log-normal size distributions, binary mixtures and ternary mixtures are evaluated by radical tessellation. The results show that the particle size differences and the proportions of each kind of particles have significant effect on the packing properties of the mixture. • Proposing a new quasi-physical model for the random packing of particles. • The model is inspired by a meshing method, which can more easily form force grids. • The model offers a natural and possibly fast route towards the final packing. • The particle size and volume ratio have significant effect on the packing properties.

Mechanical neural networks: Architected materials that learn behaviors.

Aside from some living tissues, few materials can autonomously learn to exhibit desired behaviors as a consequence of prolonged exposure to unanticipated ambient loading scenarios. Still fewer materials can continue to exhibit previously learned behaviors in the midst of changing conditions (e.g., rising levels of internal damage, varying fixturing scenarios, and fluctuating external loads) while also acquiring new behaviors best suited for the situation at hand. Here, we describe a class of architected materials, called mechanical neural networks (MNNs), that achieve such learning capabilities by tuning the stiffness of their constituent beams similar to how artificial neural networks (ANNs) tune their weights. An example lattice was fabricated to demonstrate its ability to learn multiple mechanical behaviors simultaneously, and a study was conducted to determine the effect of lattice size, packing configuration, algorithm type, behavior number, and linear-versus-nonlinear stiffness tunability on MNN learning as proposed. Thus, this work lays the foundation for artificial-intelligent (AI) materials that can learn behaviors and properties.

Two-Dimensional Conjugated Mass Transfer of Carbon Dioxide Absorption in a Hollow-Fiber Gas-Liquid Membrane Contactor.

The absorption efficiencies of CO2 in hollow-fiber membrane contactors using an ethanolamine (MEA) solvent under both concurrent- and countercurrent-flow operations were investigated theoretically and experimentally. Two-dimensional mathematical modeling was developed by Happel’s free surface model, and the resultant partial differential equations were solved analytically using the separated variables method with the use of an orthogonal expansion technique. A simplified expression of Sherwood number variations was reported by employing the relevant operations conditions and expressed in terms of the computed eigenvalues for predicting concentration distribution and absorption efficiency. It is emphasized that, in comparing various fiber packing configurations, both theoretical predictions and experimental results should be compared to find the absorption flux increment accomplished by the CO2/N2 stream passing through the fiber cells under the same mass flow rate. The value of the present mathematical treatment is evident to propose a simplified expression of the averaged Sherwood number variations, and provides the predictions of the absorption flux, absorption efficiency, average Sherwood number with the absorbent Graetz number, inlet CO2 concentration, and absorbent flow rates as parameters. The availability of such concise expressions, as developed directly from the analytical formulations, is the value of the present study. The experiments of the CO2 absorption using MEA with alumina (Al2O3) hollow fiber membranes are also set up to confirm the accuracy of the theoretical predictions. The accuracy derivations between the experimental results and theoretical predictions for concurrent- and countercurrent-flow operations are and , respectively. The operations of the hollow-fiber membrane contactor implementing N = 7 fiber cells and N = 19 fiber cells offer an inexpensive method of improving absorption efficiency by increasing fiber numbers with consideration of device performance.

Mathematical Modelling and Simulation of Second Life Battery Pack with Heterogeneous State of Health

The service life of Lithium-ion batteries disposed from electric vehicles, with an approximate remaining capacity of 75–80%, can be prolonged with their adoption in less demanding second life applications such as buildings. A photovoltaic energy generation system integrated with a second life battery energy storage device is modelled mathematically to assess the design’s technical characteristics. The reviewed studies in the literature assume, during the modelling process, that the second life battery packs are homogeneous in terms of their initial state of health and do not consider the module-to-module variations associated with the state of health differences. This study, therefore, conducts mathematical modelling of second life battery packs with homogenous and heterogeneous state of health in module level using second-order equivalent circuit model (ECM). The developed second-order ECM is validated against experimental data performed in the lab on 3Ah NCM batteries. The degradation parameters are also investigated using the battery cell’s first life degradation data and exponential triple smoothing (ETS) algorithm. The second-order ECM is integrated with the energy generation system to evaluate and compare the performance of the homogenous and heterogeneous battery packs during the year. Results of this study revealed that in heterogeneous packs, a lower electrical current and higher SOC is observed in modules with lower state of health due to their higher ohmic resistance and lower capacity, compared to the other modules for the specific battery pack configuration used in this study. The methodology presented in this study can be used for mathematical modelling of second life battery packs with heterogenous state of health of cells and modules, the simulation results of which can be employed for obtaining the optimum energy management strategy in battery management systems.

A New Multiphysics Modeling Framework to Simulate Large Battery Packs

Li-ion batteries are used in a wide variety of applications, ranging from consumer electronics to electric vehicles (EVs) and large-scale energy storage. There are also ongoing efforts to electrify air transportation. The system level issues such as safety, thermal effects, and cell balancing need to be addressed as use of batteries become widespread in the transportation sector. These issues can be studied experimentally, however, extensive experimental testing at system level involving large battery packs is impractical. Additionally, experimental testing alone cannot provide insights into these issues. This makes experimental characterization studies necessary as well, which are not feasible beyond the lab scale. Appropriate use of modeling and simulation can provide an attractive alternative to gain insights into the system level issues. Presently, simplified equivalent circuit and empirical models are typically used at pack level. Since these models do not capture various physical phenomena and electrochemical processes, they cannot provide necessary insights into these issues. There are many simulation studies on thermal management of battery packs, but these studies are limited to studying heat transfer and fluid flow without capturing their effect on the life and performance of batteries. At the scale of a single li-ion cell, there are physics-based models incorporating various processes, including transport processes, reaction kinetics, thermal effect, and degradation mechanisms. However, these models are typically not used to study battery packs. One such attempt reported in literature involved the use of thermal single-particle battery model at the pack level, but this study considered simplified thermal boundary conditions representing natural convection type heat transfer, a rather simplistic treatment for the heat leaving the batteries1. There have been other similar studies as well2-4. Since thermal management systems presently used in EVs and new designs developed by researchers involve far more complex heat transfer processes, a model capturing heat transfer processes in these thermal management systems in an accurate manner is necessary. Using an accurate physics-based electrochemical-thermal model at the battery pack level and combing it with a heat transfer model for battery thermal management system can enable studying battery performance, aging, and safety characteristics at the pack level. However, this type of simulation would be computationally prohibitively expensive, especially for large battery packs, like the ones used in EVs.In the present work, we first develop volume averaged heat transfer models for two different battery pack designs, one involving prismatic/pouch cells, and other involving cylindrical cells, like the Tesla EV battery pack. These volume averaged models are informed by full-order steady-state computational fluid dynamics (CFD) simulations, and later validated against full-order transient CFD simulations for a wide variety of operating conditions. The simulations conducted using volume averaged heat transfer models are at least two orders of magnitude faster than conventional simulations while maintaining the same level of accuracy. Next, the volume averaged heat transfer model for one of these battery pack designs and the recently reported volume averaged thermal tank-in-series battery model are used to develop a modeling framework for multiple cells connected in series to form a module, and multiple such modules connected in parallel forming a battery pack. This modeling framework enables fast simulation of large battery packs while considering complex battery physics in each individual battery and heat transfer in the thermal management system. This proposed approach can be used for any battery pack design and configuration. Using this modeling framework, we perform detailed analysis on the battery pack, including studying electrochemical and thermal behavior of individual batteries in the pack as well as pack level characteristics under different operating conditions. Finally, we also study effect of cell-cell to variations due to possible manufacturing variations and variations in the state of charge (SOC) of batteries across the battery pack.

Real-space determination of the isolated magnetic skyrmion deformation under electric current flow

The manipulation and control of electron spins, the fundamental building blocks of magnetic domains and spin textures, are at the core of spintronics. Of particular interest is the effect of the electric current on topological magnetic skyrmions, such as the current-induced deformation of isolated skyrmions. The deformation has consequences ranging from perturbed dynamics to modified packing configurations. In this study, we measured the current-driven real-space deformation of isolated, pinned skyrmions within Co10Zn10 at room temperature. We observed that the skyrmions are surprisingly soft, readily deforming during electric current application into an elliptical shape with a well-defined deformation axis (semimajor axis). We found that this axis rotates unidirectionally toward the current direction irrespective of electric current polarity and that the elliptical deformation reverses back upon current termination. We quantified the average distortion δ, which increased by ∼90% during the largest applied current density |j| = 8.46 ×109 A/m2 when compared with the skyrmion's intrinsic shape ([Formula: see text]). Additionally, we demonstrated an approximately 120% average skyrmion core size expansion during current application, highlighting the skyrmions' inherent topological protection. This evaluation of in situ electric current-induced skyrmion deformation paints a clearer picture of spin-polarized electron-skyrmion interactions and may prove essential in designing spintronic devices.

CFD-DEM Investigation on Pressure Drops of Heterogeneous Alternative-Layer Particle Beds for Low-Carbon Operating Blast Furnaces

Low-carbon operation technologies of the blast furnace (BF) are crucial for reducing carbon dioxide emissions from the steelmaking industry. The variation characteristic of permeability and structure in a BF lumpy zone has a critical impact on achieving low-carbon operations. Still, their influences have not been fully understood, and related studies are very limited. To solve the problem of the deteriorating permeability of blast furnaces after lowering the coke ratio, this study aims to provide insights into the pressure drop of the lumpy zone in an ironmaking BF based on computational fluid dynamics coupled with the discrete element method (CFD-DEM) model. The study systematically investigates the influence of different packing configurations on permeability using a heterogeneous alternating-layer (HAL) packed bed. After the model was validated by comparing the simulation’s results with ones calculated by the Ergun equation, it was used to investigate the effects of the number of layers, coke-mixing ratio, nut coke replacement ratio, and particle-size ratio on the structure, void fraction variation, and pressure drop of the HAL packed bed. The results reveal the effect of these factors on the permeability of the lumpy zone, providing fundamental guidance towards low-carbon operations of BFs.

Modal characteristics of a sustainable sandwich structure with cork stopper cores

• An eco-friendly and low-cost sustainable sandwich structure with cork stopper cores is proposed. • Natural frequencies of the sustainable sandwich panel are theoretically predicted. • Effect of the cork stopper geometric parameters on modal performance is comprehensively addressed. • Influence of packing configuration of cork stoppers on dynamic behaviors is determined. Cork is a natural sustainable material, which is widely used for wine bottle stopper. This paper proposes an environment-friendly and low-cost sandwich concept consisting of cork stoppers and aluminum covering skins for a novel building material solution. A set of prototypes with natural and agglomerated cork stopper cores are fabricated respectively. Modal tests are carried out to address the effect of arrangement orientations in the cores on natural frequencies. Besides, theoretical and finite element analysis are conducted to determine vibration behaviors of the sustainable sandwich structures. The results show that the natural frequencies of the sustainable sandwich panels are highly affected by the parent materials and packing configurations. Furthermore, the effects of cork stopper core dimensions on the vibration performance are determined by a parametric study, providing comprehensive information for sustainable building structure development and waste management.

Optimization study of air-cooled stagger-arranged battery pack with reverse-layered airflow

For low cost and environmental adaptability, the air-cooling system has been widely used as the thermal management system and is being discussed in more and more studies. In this paper, a three-dimensional model of a stagger-arranged IFR-38120 battery pack was firstly established to investigate the effects of different cell-to-cell interval (d), two-roll interval (r), and cell-to-wall interval (s) on battery cooling performance. Then, the reverse-layered stagger-arranged battery pack configuration was optimized by the Design of Experiment method. The simulation results demonstrated that compared to the original configuration, the maximum temperature (Tmax) and maximum temperature difference (ΔTmax) of the optimized reverse-layered stagger-arranged configuration dropped to 310.46 K and 6.60 K, respectively. The corresponding pressure resistance (Δp) and the space utilization factor (α) were 195.66 Pa and 0.484, respectively. Additionally, a 5 × 5 spoiler was added to the optimized model to improve temperature distribution further. Temperature uniformity was further improved with the spoilers on each side, and the ΔTmax of the battery pack decreased by 1.85 K compared with the one without a spoiler.

Cyclo[18]carbon‐A new class of electron acceptor for organic solar cells applications

The all-carboatomic ring, cyclo[18]carbon (C18), has the potential to act as an electron acceptor due to promising electronic and optical properties. In this study, we first illustrated the geometrical, electronic, and excited-state properties of C18 using various hybrid and long-range corrected density functional theory (DFT) methods. Further, we studied the nature of intermolecular interactions between dimers of C18 to gain insights into packing configurations of cyclo[18] in dimer and trimer configurations. Also, using the state-of-the-art DFT methods, we have reported the thorough characterization of the lowest excited-state (i.e. charge-transfer state) in various donor-acceptor model complexes based on pentacene and C18. We established an interplay between the molecular packing of C18 and pentacene molecules on the energy of charge transfer state. All these results could help in the designing of more efficient organic solar cells.

The role of crystal packing on the optical response of trialkyltetrelethynyl acenes.

The electronic and optical responses of an organic semiconductor (OSC) are dictated by the chemistries of the molecular or polymer building blocks and how these chromophores pack in the solid state. Understanding the physicochemical nature of these responses is not only critical for determining the OSC performance for a particular application, but the UV/visible optical response may also be of potential use to determine aspects of the molecular-scale solid-state packing for crystal polymorphs or thin-film morphologies that are difficult to determine otherwise. To probe these relationships, we report the quantum-chemical investigation of a series of trialkyltetrelethynyl acenes (tetrel = silicon or germanium) that adopt the brickwork, slip-stack, or herringbone (HB) packing configurations; the π-conjugated backbones considered here are pentacene and anthradithiophene. For comparison, HB-packed (unsubstituted) pentacene is also included. Density functional theory and G0W0 (single-shot Green's function G and/or screened Coulomb function W) electronic band structures, G0W0-Bethe-Salpeter equation-derived optical spectra, polarized ϵ2 spectra, and distributions of both singlet and triplet exciton wave functions are reported. Configurational disorder is also considered. Furthermore, we evaluate the probability of singlet fission in these materials through energy conservation relationships.

Two-step annealing induced structural rejuvenation: A cause for memory effect in metallic glasses

The structural origin of the memory effect is still elusive in glassy materials. In this letter, the memory effect in a series of metallic glasses (MGs) is observed by two step annealing using differential scanning calorimetry (DSC) and molecular dynamics simulations. It demonstrates that the Kovacs peak can be reflected from not only the system potential energy but also the atomic dynamics, showing the memory effect could originate from the formation of more loose packing configurations around mobile atoms by structural rejuvenation in the second step of high temperature annealing. In contrast, the high-low temperature annealing protocol can only induce the monotonic relaxation. Therefore, our results pave a pathway to better understand the origin of memory effect in MGs and other glassy materials from their dynamics and local atomic structure.

Statistical relationships between numerous retired lithium-ion cells and packs with random sampling for echelon utilization

Retired batteries are widely repurposed in energy storage packs as an economical and eco-friendly method to achieve echelon utilization. However, pack performance is strongly affected by variations in retired cells and pack configuration. Quantifying this effect in various pack configurations considering cell-to-cell variations is crucial for predicting the performance of numerous packs. Therefore, under a random sampling scenario, we developed statistical models of relationships between retired cells and packs in terms of capacity and resistance based on probability and statistics, thereby providing a solid theoretical foundation for designing and optimizing the pack structure. It is proven that parallel configuration improves the utilization efficiency and variation of pack-level capacities. Meanwhile, both parallel and series configurations reduce the pack-level resistance variation. Moreover, the statistical capacity performance of packs with parallel connections in series is superior to that of packs with series connections in parallel, although their statistical resistance characteristics are the same. Furthermore, based on the developed models, a capacity screening criterion is proposed that retired cells with a capacity greater than μC-2σC should be accepted in screening process to randomly compose energy storage packs, thereby reducing the capacity variation of packs while making full use of retired cells.

Molecular mechanism of CD44 homodimerization modulated by palmitoylation and membrane environments

The homodimerization of CD44 plays a key role in an intercellular-to-extracellular signal transduction and tumor progression. Acylated modification and specific membrane environments have been reported to mediate translocation and oligomerization of CD44; however, the underlying molecular mechanism remains elusive. In this study, extensive molecular dynamics simulations are performed to characterize the dimerization of palmitoylated CD44 variants in different bilayer environments. CD44 forms homodimer depending on the cysteines on the juxta-membrane domains, and the dimerization efficiency and packing configurations are defected by their palmitoylated modifications. In the phase-segregated (raft included) membrane, homodimerization of the palmitoylated CD44 is hardly observed, whereas PIP2 addition compensates to realize dimerization. However, the structure of CD44 homodimer formed in the phase-segregated bilayer turns susceptive and PIP2 addition allows for an extensive conformation of the cytoplasmic domain, a proposal prerequisite to access the cytoskeleton linker proteins. The results unravel a delicate competitive relationship between PIP2, lipid raft, and palmitoylation in mediating protein homodimerization, which helps to clarify the dynamic dimer conformations and involved cellular signaling of the CD44 likewise proteins.

Tin(IV) halide complexes with 5,7-dimethyl-8-quinolinol: structures, optical and thermal properties

Three new tin(IV) halide complexes with 5,7-dimethyl-8-quinolinol (dmqo), Sn(dmqo)2F2 (1), Sn(dmqo)2Cl2 (2a and 2 b), and Sn(dmqo)2I2 (3), have been synthesized and characterized by single-crystal X-ray diffraction, UV-Vis spectroscopy, fluorescence, and thermal analysis. The three crystals are of the monoclinic system with space group P2 1 /c. A second polymorph of 2 was observed in the space group C2/c. The Sn(IV) center is six coordinate with two bidentate ligands with N and O donor atoms and two halides in a slightly distorted octahedral geometry. The tin(IV) complexes exhibit parallel displaced packing configuration between 5,7-dimethyl-8-quinolinol ligands. Increasing the size of the halide coordinated with the Sn(IV) center increases molecular packing distortion, resulting in weakening π-π interactions between pyridyl rings. Photoluminescence and thermal properties are affected by halide coordination with tin. The relative quantum yields of Sn(dmqo)2F2 and Sn(dmqo)2Cl2 are higher than that of Sn(dmqo)2I2. Complexes 1 and 2 show interesting blue-shifted emissions in the solid state compared to solution. Thermal stability decreases in the order of increasing the size of halide coordinated to Sn(IV).

3D Organisation of Cells in Pseudostratified Epithelia

Pseudostratified epithelia have smooth apical and basal surfaces, yet along the apical-basal axis, cells assume highly irregular shapes, which we introduce as punakoids. They interact dynamically with many more cells than visible at the surface. Here, we review a recently developed new perspective on epithelial cell organisation. Seemingly random at first sight, the cell packing configurations along the entire apical-basal axis follow fundamental geometrical relationships, which minimise the lateral cell-cell contact energy for a given cross-sectional cell area variability. The complex 3D cell neighbour relationships in pseudostratified epithelia thus emerge from a simple physical principle. This paves the way for the development of data-driven 3D simulation frameworks that will be invaluable in the simulation of epithelial dynamics in development and disease.

Descriptor-free unsupervised learning method for local structure identification in particle packings.

Local structure identification is of great importance in many scientific and engineering fields. However, mathematical and supervised learning methods mostly rely on specific descriptors of local structures and can only be applied to particular packing configurations. In this work, we propose an improved unsupervised learning method, which is descriptor-free, for local structure identification in particle packing. The point cloud is used as the input of the improved method, which directly comes from spatial positions of particles and does not rely on specific descriptors. The improved method constructs an autoencoder based on the point cloud network combined with Gaussian mixture models for dimension reduction and clustering. Numerical examples show that the improved method performs well in local structure identification of quasicrystal disk and sphere packings, achieving comparable accuracy with previous methods. For disordered packings, which have been considered having nearly no local structures, the improved method identifies a nontrivial seven-neighbor motif in the maximally dense random packing of disks and finds acentric structural motifs in the random close packing of spheres, which demonstrate the ability on identification of new and unknown local structures. The improved unsupervised learning method would help obtain information from massive simulation and experimental results as well as devising new order parameters for particle packings.