Homogenization Scheme Research Articles

Rapid detection of Tulipalin A with SESI-Orbitrap MS: an exploration across spring flowers

BackgroundAllergic contact dermatitis and chronic actinic dermatitis are frequently observed among florists and gardeners due to exposure to potentially allergenic plants and plant products. Tulipalin A, an alpha-methylene-gamma-butyrolactone, is a common allergen synthesized by Tulipa genera, but its natural occurrence across Plantae remains unexplored.ResultsHere, we demonstrated the secondary electrospray ionization coupled Orbitrap mass spectrometry (SESI-Orbitrap MS) methodology for quantifying tulipalin A release from plants upon injury. By outlining temperature treatment, homogenization strategies and plant organ distribution, we show that processing flower samples stored at room temperature using a garlic press yielded the highest tulipalin A release upon injury. Via real-time monitoring, tulipalin A release was demonstrated to occur immediately upon homogenization. Next, the biosynthesis of tulipalin A across spring flowers was landscaped. Highlighting Rosa, Gerbera, Neapolitanum, Ranunculus, Othocalis, Muscari, Galanthus, Tulipa and Alstroemeria to release detectable amounts of tulipalin A upon injury. Tulipalin A was predominantly released from the Tulipa and Alstroemeria species, both belonging to the Liliales order, as stated in previous clinical and research studies.ConclusionsIn conclusion, a rapid method using the SESI-Orbitrap MS is reported to detect and track tulipalin A synthesis across plant organs and outline its cross-species distribution. Our methodology can be easily adapted for mapping other volatile plant defense metabolites and identify potentially allergenic plants. By addressing these aspects, we can ensure a safer work environment for florists and gardeners.

Nonlinear Transient Heat Transfer and Optimisation of Multidirectional (1D/2D/3D) Functionally Graded Porous Composites

In this paper, the steady and transient heat transfer behaviours of multidirectional (1D/2D/3D) functionally graded composite plates are investigated. Also, two different porosity types, i.e., even and uneven distributions, are considered along with material gradation. Here, the spatial/temperature-dependent effective material properties of these highly heterogeneous composites with porosity are evaluated using the extended Voigt’s homogenisation scheme via multi-variable power-law functions and further verified with the representative volume element (RVE) scheme. In continuation, generalised mathematical models are developed by including material nonlinearity using the cubic-polynomial-based temperature-dependent constitutive model. The Poisson’s and Laplace’s equations are utilised for steady and transient heat transfer problems, respectively, and the weak form is derived using the Galerkin method. Further, coupled finite element method (FEM)–finite difference method (FDM) is adopted via Picard’s successive iteration and Crank–Nicolson technique to compute the nonlinear transient temperature. The proposed model is verified by comparing it with the previously reported results. In addition, the effects of heterogeneity, porosity, power-law indices and boundary conditions on the steady/transient heat transfer responses of multidirectional functionally graded plates are examined and discussed in detail. At last, the optimum material distributions are obtained using the response surface methodology (RSM) by minimising the heat transfer responses.

Football Net: Leveraging the Structure of Truncated Icosahedron in Convolutional Neural Network Design

Deep neural networks often suffer from the degradation of fine-grained features during feature transmission. To mitigate this issue, we propose an innovative CNN architecture, Football Net, which is designed to enhance feature propagation. By introducing Asymmetric Skip Connections, Football Net effectively captures and preserves fine-grained details. Another significant challenge in deep neural networks is achieving robustness. Football Net addresses this challenge by incorporating a novel misaligned feature merging mechanism and a new homogeneous ensemble learning strategy. The experimental results indicate that this improved ensemble strategy significantly reduces both bias and variance, thereby enhancing overall classification performance. We conducted extensive experiments on the CIFAR-10, ImageNet-100, and ImageNet-1k datasets. The results demonstrate the competitiveness of Football Net in image classification tasks, achieving accuracy comparable to state-of-the-art models such as ResNet, U-Net, and U-Net++ while also improving robustness.

CRISPR-Based Homogeneous Electrochemical Strategy for Near-Zero Background Detection of Breast Cancer Extracellular Vesicles via Fluidity-Enhanced Magnetic Capture Nanoprobe.

Precise identification and analysis of multiple protein biomarkers on the surface of breast cancer cell-derived extracellular vesicles (BC-EVs) are of great significance for noninvasive diagnosis of the breast cancer subtypes, but it remains a major challenge owing to their high heterogeneity and low abundance. Herein, we established a CRISPR-based homogeneous electrochemical strategy for near-zero background and ultrasensitive detection of BC-EVs. To realize the high-performance capture and isolation of BC-EVs, fluidity-enhanced magnetic nanoprobes were facilely prepared. After capturing BC-EVs, the AND logic gate-based catalytic hairpin assembly (CHA) and the trans-cleavage activity of CRISPR-Cas12a against the magnetic signal nanoprobes were triggered successively, generating a significant electrochemical signal. Notably, the as-developed metal-mediated magnetic signal nanoprobes could efficiently decrease the background signal by magnetic separation, endowing the method with a high signal-to-noise ratio. Consequently, by ingeniously integrating DNA logic gate-based CRISPR-CHA signal amplification with dual magnetic nanoprobes in a homogeneous electrochemical strategy, precise identification and ultrasensitive detection of BC-EVs was successfully achieved through simultaneous and specific recognition of dual protein markers on the BC-EVs surface. More importantly, this approach could effectively discriminate specific subgroups of BC-EVs in clinical serum samples, which may provide great opportunities for the accurate diagnosis and prognosis evaluation of breast cancer in a noninvasive manner.

MACHINE-LEARNING-BASED ASYMPTOTIC HOMOGENIZATION AND LOCALIZATION OF SPATIALLY VARYING MULTISCALE CONFIGURATIONS MADE OF MATERIALS WITH NONLINEAR ELASTIC STRESS-STRAIN RELATIONSHIPS

This article aims to propose a general method in support of efficient and reliable predictions of both the global and local behaviors of spatially varying multiscale configurations (SVMSCs) made of materials bearing nonlinear history-independent stress-strain relationships. The framework is developed based on a complementary approach that integrates asymptotic analysis with machine learning (ML). The use of asymptotic analysis is to identify the homogenized constitutive relationship and the implicit relationships that link the local quantities of interest, say, the site where the maximum von Mises stress (MVMS) lies, with other on-site mean-field quantities. As for the implementation of the proposed asymptotic formulation, the aforementioned relationships of interest are represented by neural networks (NNs) using training data generated following a guideline resulting from asymptotic analysis. With the trained NNs, the desired local behaviors can be quickly accessed at a homogenized level without explicitly resolving the microstructural configurations. The efficiency and accuracy of the proposed scheme are further demonstrated with numerical examples, and it is shown that even for fairly complex multiscale configurations, the predicting error can be maintained at a satisfactory level. Implications from the present study to speed up classical computational homogenization (CH) schemes are also discussed.

On the accuracy of a homogenization scheme for the linear buckling analysis of structures assembled from beam-based lattice plates

PurposeThis study examines the accuracy of a homogenization scheme for the linear buckling analysis of structures assembled from beam-based lattice plates. Regardless of in-plane acting loads, the buckling behavior is characterized by the abrupt out-of-plane deformation. Apparently, if the lattice plates are modeled as homogenized ones, the out-of-plane effective material properties should be considered. However, as prevalently implemented in literature, the in-plane effective material properties are assigned to the homogenized plates for the linear buckling analysis, and thus, the results are erroneous.Design/methodology/approachThe linear buckling analysis is performed by two finite element models, i.e. the high- and low-fidelity finite element models. In the former one, each strut of the lattice structures is modeled as an Euler–Bernoulli beam, and thus, all the geometrical features are explicitly simulated. On the other hand, the low-fidelity one involves the homogenized plates having the out-of-plane effective material properties determined from the lattice counterparts using an energy-based homogenization method.FindingsThe accuracy of the homogenization scheme is confirmed by the comparison of results obtained by the high- and low-fidelity finite element models. Six topological configurations of the unit cells are considered, and the first five buckling modes are inspected. In all examinations, the low-fidelity finite element model offers the acceptable level of accuracy, i.e. the relative difference between two finite element models is lower than 5%. Furthermore, it is recommended to use the out-of-plane effective material properties rather than the in-plane ones to ensure the precise simulation.Originality/valueThe current study is original. In literature, there are some studies regarding the buckling analysis of lattice plates or panels with out-of-plane material properties. However, these studies use the analytical approach, and consequently, they are confined to lattice structures whose geometry is simple. In the present paper, structures assembled from beam-based lattice plates are examined. It can be noticed that these structures can have complex geometry. Therefore, the feasibility and accuracy of using out-of-plane effective material properties with homogenized plates for the linear buckling analysis of lattice plates are validated.

Local charge homogenization strategy enables ultra-high voltage tolerance of polyether electrolytes for 4.7V lithium metal batteries.

In-situ fabricated polyether electrolytes have been regarded as one of the most promising solid electrolyte systems. Nevertheless, they cannot match high-voltage cathodes over 4.3V due to their poor oxidative stability. Herein, we propose an effective local charge homogenization strategy based on the triglycidyl isocyanurate (TGIC) crosslinker, achieving ultra-high-voltage electrochemical stability of polyether electrolytes (viz. PTIDOL) at cutoff voltages up to 4.7V. The introduction of TGIC optimizes the Li+ solvation environment, thereby homogenizing the charge distribution at ether oxygen (EO) sites, resulting in significantly enhanced oxidative stability of the polyether main chain. Consequently, the Li|PTIDOL|LiNi0.6Co0.2Mn0.2O2 (NCM622) cell achieves long-term operation at an ultra-high cutoff voltage with a capacity retention of 81.8% after 400 cycles, one of the best results reported for polyether electrolytes to date. This work provides significant insights for the development of polyether electrolytes with high-voltage tolerance and the advancement of high-energy-density batteries.

The effect of adding graphene oxide into CNT/polymer system on the CNT dispersion and mechanical properties of the hybrid nanocomposites

The influence of adding graphene oxide (GO) fillers into CNT nanocomposites on the formation of CNT agglomerates and on their synergistic effect to the mechanical properties are investigated in this paper. To this end, a two-scale homogenization scheme and a GO-dependent morphological model of CNT agglomeration is built to predict the effective elastic moduli and strain-hardening behaviors of the hybrid composite. We adopt the Mori-Tanaka method, self-consistent theory and field-fluctuation approach to derive the effective secant moduli and Mises stress of each phase in or outside CNT agglomerates. In addition, the interface effects including imperfect mechanical bonding and interfacial tangential sliding between fillers and matrix are also considered. The results show that addition of GO significantly reduces the size and volume fraction of CNT agglomerates, leading to an enhanced dispersion of CNTs within the PVA matrix. The effective mechanical properties of the hybrid nanocomposites, including tensile strength and Young’s modulus, are also improved. The combinatorial impact of GO and CNTs to the composites is found to be superior to one with either GO or CNTs alone.

Effective thermal conductivity of composites using homogenization

Composite materials are extensively used in engineering applications due to their customizable properties and high performance. Determining the equivalent homogenized properties of composites, such as thermal conductivity, is crucial for their effective use. Various theoretical, analytical, and experimental methods have been developed to assess these properties. This study investigates the effective thermal conductivity of composites using a deterministically based procedure for thermal analysis. This procedure accounts for the combined influences of the inclusions’ volume fractions, shapes, orientations, and locations within the matrix to determine the effective thermal conductivity of composites. The specific composite analyzed consists of a cubical PLA matrix with a single spherical or elliptical void inclusion with perfect interfaces. For that purpose, an analytical approach was developed, and MATLAB® code was created to calculate the effective thermal conductivity tensor. To benchmark the analytical results, comparisons were made against numerical finite element modeling (FEM) results conducted using ANSYS®; in addition, to previously reported analytical models from the literature. Corroboration was also obtained by comparing the results against experimental data from the literature. The accuracy of the proposed homogenization scheme was demonstrated by achieving a low mean absolute percentage error (MAPE) compared to FEM (2.88%) and to the experimental results (2.72% for void inclusion and 6.99% for filled inclusion). Additionally, a high R-squared (R2) value of 0.986 was achieved compared to FEM, and values of 0.97 and 0.998 were achieved compared to the experimental results for void and filled inclusions, respectively.

Size-dependent nonlinear dynamics of two-directional functionally graded microbeams in thermal environment under a moving mass

The size-dependent nonlinear dynamics of two-directional functionally graded (2D-FG) microbeams in a thermal environment under a moving mass is studied for the first time in the framework of the refined higher-order shear deformation theory (HSDT) and modified couple stress theory (MCST). The variation of the temperature-dependent material properties in the axial and thickness directions is estimated by the Mori–Tanaka homogenization scheme. Considering the rotary inertia and shear deformation, the nonlinear differential equations of motion, obtained from Hamilton’s principle, are discretized using an enriched beam element. Numerical results determined by the Newmark method in combination with Newton–Raphson iterative procedure confirm the efficiency of the derived beam formulation in predicting the nonlinear dynamics. The enriched beam element, which is derived herein by using hierarchical functions to enrich the conventional shape functions, is capable of furnishing accurate nonlinear dynamic characteristics with fewer elements compared to the conventional one. It is shown that the difference between the dynamic response predicted by the linear analysis and the nonlinear one increases by increasing the temperature, but it decreases by increasing the size scale parameter. The effects of the material gradation, temperature rise and micro-scale parameter on the nonlinear dynamic behavior of the 2D-FG microbeams are studied in detail and highlighted.

A homogenization scheme for viscoplastic composites based on the plane-wave decomposition of constitutive potentials

A homogenization scheme for nonlinear viscoplastic composites is developed on the basis of a plane-wave decomposition of the constitutive potentials and a scalar linearization of the generalized-secant type. Self-consistent predictions for rigidly reinforced blends flowing in accordance with a power law are reported and confronted to similar predictions obtained with a tensorial linearization of the same generalized-secant type. The two sets of predictions are found to agree for weak nonlinearities but to diverge for strong nonlinearities. Implications are discussed.

Volumetric Homogenization for Knitwear Simulation

This paper presents volumetric homogenization, a spatially varying homogenization scheme for knitwear simulation. We are motivated by the observation that macro-scale fabric dynamics is strongly correlated with its underlying knitting patterns. Therefore, homogenization towards a single material is less effective when the knitting is complex and non-repetitive. Our method tackles this challenge by homogenizing the yarn-level material locally at volumetric elements. Assigning a virtual volume of a knitting structure enables us to model bending and twisting effects via a simple volume-preserving penalty and thus effectively alleviates the material nonlinearity. We employ an adjoint Gauss-Newton formulation[Zehnder et al. 2021] to battle the dimensionality challenge of such per-element material optimization. This intuitive material model makes the forward simulation GPU-friendly. To this end, our pipeline also equips a novel domain-decomposed subspace solver crafted for GPU projective dynamics, which makes our simulator hundreds of times faster than the yarn-level simulator. Experiments validate the capability and effectiveness of volumetric homogenization. Our method produces realistic animations of knitwear matching the quality of full-scale yarn-level simulations. It is also orders of magnitude faster than existing homogenization techniques in both the training and simulation stages.

On the dispersion of bulk wave in hygrothermally affected poroelastic gymnastics beams based on refined higher-order shear deformation theory during athlete training

Poroelastic materials have gained prominence due to their beneficial characteristics, prompting the authors to investigate their behavior in wave propagation. Additionally, the balance beam used in gymnastics is a classic example of a beam structure. It is designed to support the weight of the gymnast while providing stability and strength. This paper focuses on analyzing wave dispersion behavior in a hygrothermally excited poroelastic gymnastics beam. It is considered that the beam is made of a composition of Alumina and Aluminum as ceramic and metallic phases, respectively. Initially, the basic characteristics are determined using an improved power-law homogenization scheme. Subsequently, a poroelastic beam is modeled based on a refined higher-order shear deformation theory, and based on it and Hamilton’s principle, the kinetic relations are obtained. The obtained governing equations are then solved through analytical schemes using harmonic functions, and the outcomes are presented. These results are afterward verified through comprehensive comparisons with existing literature. Furthermore, this paper findings shows that the phase velocity and wave frequency of the beam are influenced by gradient parameters, porosity, and environmental factors like temperature and humidity to gain further insights.

Controlled preparation of cellulose acetate by deep eutectic solvent homogeneous catalysis

This work proposed a homogeneous preparation strategy of cellulose acetate by using a deep eutectic solvent consisting of zinc chloride/phosphoric acid/water (ZnCl2/PA/H2O). The results showed that the DES (the molar ratio of ZnCl2: PA: H2O = 1:1:3) had good solubility for bamboo pulp with high degree of polymerization. The dynamic dissolution behavior of cellulose in DES was also studied. Cellulose was first moistened and swollen and then dissolved. The crystalline state of cellulose changed from type I to type II after regeneration. Under the synergistic effect of acetic anhydride (Ac2O), the dissolved cellulose in DES could be uniformly acetylated. The effects of temperature, reaction time and molar ratio of Ac2O/anhydrous glucose on degree of substitution (DS) were investigated in their respective ranges (30–50 °C, 2–10 h and 4–24). Cellulose acetate with DS of 0.42–1.81 was successfully prepared. The substituent distribution of the sample was analyzed as C-6 > C-2 > C-3. Moreover, the entire process required no additional catalysts or activation steps, reducing the difficulty of solvent recovery. The insight from this study provides a new idea for the development of greener methods for the homogeneous preparation of cellulose acetate.

A two‐scale numerical analysis of intra‐yarn hybrid natural/synthetic woven composites

AbstractThis paper investigates how combining natural and synthetic fibers within yarns, altering the degree of hybridisation, and varying weave architectures affect the homogenized elastic properties and stress distributions in 2D woven composite laminae using a two‐scale homogenization scheme. The novelty lies in integrating a micro‐scale representative volume element model with a meso‐scale repeating unit cell model to capture intra‐yarn natural/synthetic fiber hybridisation. The study focuses on 2/2 twill and 5‐harness satin woven laminae with flax/E‐glass, hemp/E‐glass and basalt/E‐glass hybrid yarns, all with a total fiber volume fraction of 0.6. Fiber distributions are created through a random sequential expansion algorithm for hybrid RVEs, while periodic meso‐structures are used to define weave architectures for RUCs. Results show that yarn‐level fiber hybridisation significantly influences matrix stress distributions, with variations of up to 22%. In contrast, weave architecture has a minimal effect, with variations in homogenized properties below 2%. Varying fiber types, degrees of hybridisation and weave architectures allow for the tailoring of yarn and lamina properties and altering the stress distributions at micro‐ and meso‐scales and potentially influencing damage mechanisms. The modeling approach for analyzing the mechanical behavior of intra‐yarn hybrid natural/synthetic woven laminae could potentially be used to tailor their tolerance to damage.Highlights Two‐scale homogenization integrates RVE and RUC for 2D woven hybrid composites. Analyzed flax/E‐glass, hemp/E‐glass, basalt/E‐glass in twill and satin weaves. Intra‐yarn hybridisation significantly affects properties and stress fields. Hybridizing fibers offers tailored properties and may improve damage tolerance.

An affine formulation of eigenstrain-based homogenization method and its application to polycrystal plasticity

Abstract Reduced order models (ROMs) are typically incorporated into concurrent multiscale approaches to allow for efficient nonlinear multiscale simulations and to alleviate high cost of direct nonlinear computational homogenization schemes. ROMs based on the ideas of transformation field analysis are among the most popular in the literature since they only require linear elastic simulations for model construction and typically have low number of degrees of freedom. However, these models have been shown to deliver overly stiff response in simulating wide range of materials. The present study focuses on mitigating this problem in the context of eigenstrain-based homogenization method (EHM) using instantaneous moduli information for polycrystal elastoviscoplasticity. For this purpose, a new EHM model is developed with the intention of using affine moduli for recomputation of the instantaneous localization tensors. The accuracy of the method is compared to the original EHM and direct crystal plasticity finite element simulations for several synthetic polycrystal microstructures, loading conditions and varying phase contrast. We show that the affine model delivers consistently softer response compared to the original EHM model. In particular, the affine model delivers notably more accurate response in the presence of high phase contrast. The affine EHM is able to capture local load redistribution through recomputation of the localization tensors.

An Overview of the Mechanical Behavior of Nanocomposites Considering the Interphase

ABSTRACTOver the past decade, nanocomposites with polymer matrices have garnered significant attention for their ability to enhance properties with minimal inclusion volume, thanks to nanoscale reinforcement. The key factor distinguishing them from microcomposites is the interphase, an area of interaction where matrix properties are influenced by the reinforcement. This induces a dependence on particle size that sets nanocomposites apart. Observation of the interphase is achieved through experimental methods like atomic force microscopy (AFM) and numerical approaches such as molecular dynamics (MD) modeling. Indirect determination involves the comparison of experimental results with predictive models, which may be numerical or analytical homogenization schemes. The widely used double inclusion scheme focuses on nanocomposites, but for a comprehensive mechanical behavior prediction, elastic behavior alone is not sufficient. Factors in the matrix (plasticity, viscosity, temperature) and morphology (dispersion, surface treatment, bonding) must be considered. This review explores various methods in the literature that address these aspects.

A mean field homogenization model for the mechanical response of ceramic matrix composites

SiC/SiC composites offer exceptional mechanical stability at high temperatures and under irradiation. These ceramic matrix composites are therefore strong candidate materials for future nuclear energy applications. Their mechanical response, which exhibits pseudo-plasticity, is mediated by matrix cracking, fiber debonding, and fiber pull-out due to slip. This study introduces a mechanistic model for the behavior of unidirectionally reinforced SiC/SiC composites. Specifically a mean field homogenization approach is proposed to account for all deformation and degradation modes during mechanical deformation. The homogenization scheme relies on a Mori Tanaka method that is extended to consider the effects of the coating’s elasto-plastic response on the development of micromechanical fields. Further, the model proposed introduces a method to effectively account for the role of localized damage (i.e., cracks) on mechanical fields within both the fiber and the matrix. Upon validating the model against experimental data, the roles of interface sliding, coating dimensions and intrinsic elastic response, as well as of microstructure (e.g. porosity, fiber volume fraction) are discussed.

Fatigue crack growth in functionally graded materials using an adaptive phase field method with cycle jump scheme

Functionally graded materials provide versatility in adjusting the volume fractions of constituent materials to meet specific design requirements. However, this customization often introduces mode-mixity at the crack tip, posing challenges in predicting fracture under cyclic loading with discrete approaches and computationally expensive with conventional phase-field fracture models. To address these issues, this paper introduces an adaptive phase-field fracture formulation with cycle jump scheme to elegantly predict fatigue crack nucleation and growth in functionally graded materials. Within this framework, the effective properties at a point are estimated using the Mori–Tanaka homogenization scheme, while the crack growth due to cyclic load is captured by incorporating an additional fatigue degradation parameter. Moreover, the computational efficiency of the proposed framework is improved through an adaptive mesh refinement and explicit cycle jump scheme. The adaptive refinement scheme utilizes an error indicator derived from both the displacement solution and phase-field variable. The adaptive refinement scheme is integrated with efficient quadtree decomposition, which generates a hierarchical mesh structure. Hanging nodes resulting from the quadtree decomposition are efficiently handled using a polygonal finite element method. The proposed framework is validated against experimental and numerical results reported in the literature. Furthermore, we investigate the fatigue crack growth resistance across a broad range of material gradation directions, gaining valuable insights and identifying functionally graded materials with high fatigue resistance.

Homogeneous Complexation Strategy to Manage Bromine for High‐Capacity Zinc–Bromine Flow Battery

AbstractZinc–bromine flow batteries (ZBFBs) have received widespread attention as a transformative energy storage technology with a high theoretical energy density (430 Wh kg−1). However, its efficiency and stability have been long threatened as the positive active species of polybromide anions (Br2n+1−) are subject to severe crossover across the membrane at a high concentration. Herein, a novel highly hydrophilic complexing agent, N‐methyl‐N, N‐bis(2‐hydroxyethyl)‐1‐propanaminium bromide (PMDA), is developed to effectively manage bromine in a homogeneous posolyte, which realizes a low bromine crossover at a high operating concentration in ZBFBs. Both theoretical and experimental results suggest that the PMDA interacts with Br2n+1− and forms a larger‐size complex PMDABr2n+1. When adding 0.40 m PMDA, the bromine stays homogeneous at a high concentration up to 1.20 m, and its permeability is remarkably decreased by 74%. For demonstration, the ZBFB achieves a operating capacity record of 57.2 Ah L−1 in a homogeneous bromine posolyte with a high Coulombic efficiency of ≈90.0% and superior cycling stability (capacity retention rate of 100.0% per cycle). This work provides one innovative bromine management strategy to realize a high capacity and superior stability in ZBFBs.