Homogeneous Elements Research Articles

Structural, thermophysical, mechanical and electrical properties of equimolar five-principal element fluorite-structured high-entropy oxides

Four kinds of high-entropy oxides (HEOs) with compositions of Y0.2Zr0.2Hf0.2Ce0.2X0.2O2−δ (X=La, Nd, Gd, Dy, abbreviated as HEO-La, Nd, Gd, Dy, respectively) are synthesized by solid-state-reaction method combined with conventional sintering in air atmosphere at 1600 °C for 10h. These HEOs have a fluorite-structured phase with homogeneous element distribution. The thermal conductivity (κ) of these four samples is in 1.68–2.18W·m-1·K-1 in 25–900 °C. At 800 °C and 900 °C, the κ value of HEO-Gd is lower than those of the HEO-La, Nd, Dy, yttria-stabilized zirconia (YSZ) and some other HEOs with various crystal structures ((Gd0.2Dy0.2Ho0.2Er0.2Tm0.2)Ta3O9, (La0.25Eu0.25Gd0.25Yb0.25)2Zr2O7, (Sm0.2Dy0.2Ho0.2Er0.2Yb0.2)NbO4, Hf0.25Zr0.25Ce0.25Gd0.125Ca0.125O2-δ and Sr(Y0.2Sm0.2Gd0.2Dy0.2Yb0.2)O4). The sample of HEO-Gd has the highest thermal expansion coefficient (CTE) (12.1×10-6K-1) and fracture toughness (KIC) (2.5MPa·m1/2) among HEO-La, Nd, Gd, Dy. Its KIC value is higher than those of other HEOs mentioned above. In addition, HEO-Gd exhibits a better oxygen barrier property compared with YSZ in 450–700 °C. These results indicate that HEO-Gd is a promising candidate as high-temperature thermal insulation ceramic.

A homogenization method for natural frequencies and damping of sandwich panels based on representative volume elements

The existing representative volume element (RVE) homogenization method, grounded in finite element analysis, assumes a planar configuration for the sections of sandwich panels, implying rigidity. To accommodate non-planar displacements, this study introduces a novel homogenization method reliant on the displacements obtained from four-point bending and four-point torsion. The present method is employed to investigate the mode shapes, natural frequencies, and loss factors of sandwich panels utilizing an equivalent single-layer shell model. Validation of the present method is conducted through the analysis of lattice sandwich panels and corrugated sandwich panels incorporating viscoelastic layers. Comparative analyses encompassing the results of the experiment, the conventional solid model method, the present method, and the conventional plane method are undertaken. The universality of the present method is substantiated. The present method enhances the precision of natural frequency prediction.

Some notes on graded weakly 1-absorbing primary ideals

Abstract A proper graded ideal P P of a commutative graded ring R R is called graded weakly 1-absorbing primary if whenever x , y , z x,y,z are nonunit homogeneous elements of R R with 0 ≠ x y z ∈ P 0\ne xyz\in P , then either x y ∈ P xy\in P or z z is in the graded radical of P P . In this article, we explore more results on graded weakly 1-absorbing primary ideals.

Some progress in the Dixmier conjecture for A 1

Let p and q, where p q − q p = 1 , be the standard generators of the first Weyl algebra A 1 over a field of characteristic zero. Then the spectrum of the inner derivation ad(pq) on A 1 are exactly the set of integers. The algebra A 1 is a Z -graded algebra with each i-component being the i-eigenspace of ad(pq), where i ∈ Z . Assume that z and w are elements of A 1 satisfying z w − w z = 1 . The Dixmier Conjecture for A 1 says that they always generate A 1. We show that if z possesses no component belonging to the negative spectrum of ad(pq), then z and w generate A 1. We give some generalization of this result, and some other useful criterions for z and w to generate A 1. It is shown that if z is a sum of not more than 2 homogeneous elements of A 1 then z and w generate A 1, which generalizes a known result due to Bavula and Levandovskyy.

Numerical and experimental investigation on the heat transfer and mass transport in LPBF in-situ alloying of Al/Cu alloy

PurposeLaser powder bed fusion (LPBF) in-situ alloying is a recently developed technology that provides a facile approach to optimizing the microstructural and compositional characteristics of the components for high performance goals. However, the complex mass and heat transfer behavior of the molten pool results in an inhomogeneous composition distribution within the samples fabricated by LPBF in-situ alloying. The study aims to investigate the heat and mass transfer behavior of an in-situ alloyed molten pool by developing a three-dimensional transient thermal-flow model that couples the metallurgical behavior of the alloy, thereby revealing the formation mechanism of composition inhomogeneity.Design/methodology/approachA multispecies multiphase computational fluid dynamic model was developed with thermodynamic factors derived from the phase diagram of the selected alloy system. The characteristics of the Al/Cu powder bed in-situ alloying process were investigated as a benchmark. The metallurgical behaviors including powder melting, thermal-flow, element transfer and solidification were investigated.FindingsThe Peclet number indicates that the mass transfer in the molten pool is dominated by convection. The large variation in material properties and temperature results in the presence of partially melted Cu-powder and pre-solidified particles in the molten pool, which further hinder the convection mixing. The study of simulation and experiment indicates that optimizing the laser energy input is beneficial for element homogenization. The effective time and driving force of the convection stirring can be improved by increasing the volume energy density.Originality/valueThis study provides an in-depth understanding of the formation mechanism of composition inhomogeneity in alloy fabricated by LPBF in-situ alloying.

On graded (1,r)-ideals

Let [Formula: see text] be a group with identity element [Formula: see text] and [Formula: see text] be a commutative [Formula: see text]-graded ring with nonzero unity [Formula: see text]. In this paper, we introduce the graded version of [Formula: see text]-ideals which is a generalization of graded [Formula: see text]-ideals. A proper graded ideal [Formula: see text] of [Formula: see text] is said to be a graded [Formula: see text]-ideal if whenever [Formula: see text] for some nonunits homogeneous elements [Formula: see text], then either [Formula: see text] or [Formula: see text]. We investigate some basic properties of graded [Formula: see text]-ideals. We show that if [Formula: see text] admits a graded [Formula: see text]-ideal that is not a graded [Formula: see text]-ideal, then [Formula: see text] is a [Formula: see text]-graded local ring. Also, we give a method to construct graded [Formula: see text]-ideals that are not graded [Formula: see text]-ideals. Furthermore, we prove that [Formula: see text] is a graded total quotient ring if and only if every proper graded ideal of [Formula: see text] is graded [Formula: see text]-ideal and also we present a counterpart of prime avoidance lemma for graded [Formula: see text]-ideals. Finally, an idea is given about some graded [Formula: see text]-ideals of the ring of fractions and the idealization.

Mechanical behavior of reservoirs with heterogeneous hydrate distribution: Analysis from the thickness and angle of the hydrate-bearing layer

The heterogeneity of natural hydrate-bearing sediments (HBSs) makes it of great engineering significance to investigate the mechanical properties of heterogeneous HBSs and develop an efficient method to determine their strength parameters. In this study, heterogeneous hydrate-bearing clayey sand specimens were prepared by controlling the water distribution in host specimens. The hydrate-bearing layers in the prepared specimens have similar hydrate saturation, different thicknesses and angles. Multistage triaxial experiments were conducted to investigate the effects of hydrate-bearing layer thickness (HBLT) and angle (HBLA) on the stress-strain behavior and strength parameters of the specimens under differing effective confining stresses. The results show that the specimens produce bulging deformation and strain-hardening failure mode. Within the study scope, the strain-hardening degree of the stress-strain curve decreases with increasing HBLT and decreasing HBLA. The failure strength of the specimen initially increases and then decreases with increasing HBLT, peaking at 6 cm HBLT; however, it is positively correlated with HBLA. As HBLT increases, the cohesion increases exponentially, while the internal friction angle initially increases and then decreases. HBLA contributes to a linear increase in both cohesion and internal friction angle. Empirical equations for the cohesion and internal friction angle of heterogeneous specimens were formulated by replacing the heterogeneity with homogeneous elements, and their validity was verified. Under high effective confining stress, in the initial deformation stage, the shear stress applied to specimens with HBLT larger than 6 cm gradually increases with the increasing HBLT, while the thickness of the hydrate-free layer, which is susceptible to deformation response under external load, decreases. Consequently, the number of broken and damaged hydrates in these specimens increases. In the following shear process, failed hydrates prevent the pores from being compressed and serve as lubrication, leading to a reduction in the strain-hardening degree of the stress-strain curve and a reduction in failure strength. HBLA changes the contact area between hydrate-bearing and hydrate-free layers, as well as the axial distribution of hydrates, thus influencing the mechanical behavior of the specimen.

FeFET-Based In-Memory Hyperdimensional Encoding Design

The data explosion of Internet-of-Things (IoTs) and machine learning tasks raises a great demand on highly efficient computing hardware and paradigms. Brain-inspired hyperdimensional computing (HDC) is becoming a promising computing paradigm, which encodes data as hypervectors with homogeneous elements instead of numbers, and can perform learning/classification tasks through simple logical or arithmetic operations on the encoded hypervectors. Therefore HDC has much lower computational complexity than conventional computational models such as neural networks. However, due to its high-dimensional data representation, processing and encoding hypervectors in conventional Von-Neumann architectures (e.g., CPU and GPU) requires a large amount of energy-and time-consuming data transfer, thus weakening its efficiency benefiting from low complexity. In this paper, we proposed an ultra-low power and fast computing-in-Memory (CiM) design based on non-volatile (NV) Ferroelectric FET (FeFET) for HDC encoding. The proposed design mainly support hyperdimensional bit-wise XOR and parallel majority vote (MAJ) operations for HDC encoding, which are implemented by FeFET based memories together with CMOS peripheral circuits. The 1FeFET1T based memory cell effectively mitigates the impact of transistor variations on the operation. A highly parallel and pipelined computing workflow of the proposed design further boosts the energy efficiency and performance with negligible extra area overhead. Experimental results demonstrate that our proposed design achieves 5.04× energy efficiency improvement over other CiM designs for HDC encoding.

Free limits of free algebras

Consider a diagram ⋯→F3→F2→F1 of algebraic systems, where Fn denotes the free object on n generators and the connecting maps send the extra generator to some distinguished trivial element. We prove that (a) if the Fi are free associative algebras over a fixed field then the limit in the category of graded algebras is again free on a set of homogeneous generators; (b) on the other hand, the limit in the category of associative (ungraded) algebras is a free formal power series algebra on a set of homogeneous elements, and (c) if the Fi are free Lie algebras then the limit in the category of graded Lie algebras is again free.

Usual breast lump with unusual features.

The co-existence of granulomatous mastitis and collagenous spherulosis in a breast lump is an uncommon finding. The awareness of cytomorphological features can help corroborate a cytological diagnosis. A palpable breast lump in an elderly female warrants urgent attention and fine needle aspiration is a rapid, reliable method of evaluation. An elderly female with a firm breast lump mimicking malignancy was subjected to fine needle aspiration cytology (FNAC). Smears showed ill-formed granulomas, inflammatory cells and homogeneous hyaline stromal globular elements intermingled with the benign ductal epithelial and myoepithelial cells.

Effect of Magnet Alternate Stirring on the Internal Quality of Sn-Pb Alloy

A permanent magnet stirrer was built to study the effect of different magnetic field stirring modes on the solidification quality of Sn-20 wt-% Pb alloy ingots. The internal quality of the ingot can be improved by adjusting both the stirring speed and the modes. When the continuous magnetic stirring mode was adopted, the higher the stirring speed, the higher the flutter height at the ingot edge. When the stirring speed was 200 rpm, the flutter height reached 4.12 mm. The rotating magnetic field can significantly refine the grain size of the ingot. When the stirring speed of the magnetic field was increased from 0 rpm to 200 rpm, the grain size of the ingot reduced from 301 μm to 241 μm. By fixing the magnetic field stirring speed to 200 rpm and adjusting the mode to the alternate stirring process, the flutter height at the ingot edge reduced to 1.86 mm, which stabilized the liquid level of the molten alloy in the crucible. In addition, the grain size of the ingot was shortened to 223 μm, and the elemental homogeneity within the ingot was optimized.

Immobilization-Free Photoelectrochemical Aptasensor for Atrazine Based on Bifunctional Graphene Signal Amplification and a Controllable Sulfhydryl-Assembled BiOBr/Ag NP Microinterface.

Immobilization-free sensors (IFSs), with no requirement of fixing the recognition element to the electrode surface, have received increasing attention due to their unique advantages of reusable electrodes, not being limited by the load of the recognition element, and not being easily changed to the structure of the probe. In the present work, an effective visible light-driven immobilization-free photoelectric aptasensor for ultrasensitive detection of atrazine (ATZ) was proposed based on a reusable BiOBr/Ag NP substrate electrode with ultrafast charge transfer. Controllable thiols were used as conditioning agents for the photoelectric signal. The ingeniously designed bifunctional graphene can act as not only a molecular "bridge" for the ATZ aptamer through a strong π-π stacking effect, obtaining a graphene-aptamer complex, serving as a homogeneous recognition element, but also a switch for signal modulation for quantitative detection of target substances. Benefiting from the synergistic effect of the above-mentioned factors, the proposed sensor is capable of ultrasensitive and highly selective detection of ATZ in real water samples with a low detection limit of 1.2 pM and a wide linear range from 5.0 pM to 10.0 nM. Furthermore, it shows high stability, good selectivity, and strong anti-interference ability. Thus, this work has provided a fresh perspective for designing advanced immobilization-free photoelectric sensors and convenient detection of environmental pollutants.

Fast estimation of bending stiffness in sandwich-structured composites with 3D printed TPMS core

This article presents a preliminary design methodology that enables rapid estimation of composite sandwich structures with bioinspired triply periodic minimal surfaces (TPMS) core originally employed in tissue engineering. The study employs representative volume element (RVE) homogenization analysis to calculate the stiffness matrix. Furthermore, the enhancement of bending stiffness through the incorporation of different material layers to the TPMS core is analyzed. This proposed design approach provides a time-saving alternative to extensive FEM analysis, particularly for large models. Initial estimations based on geometry, dimensions, material properties, and total weight considerations aid in selecting designs for further detailed FEM analysis.

A characterization of the natural grading of the Grassmann algebra and its non-homogeneous [formula omitted]-gradings

Let F be any field of characteristic different from two and let E be the Grassmann algebra of an infinite dimensional F-vector space L. In this paper we will provide a condition for a Z2-grading on E to behave like the natural Z2-grading Ecan. More specifically, our aim is to prove the validity of a weak version of a conjecture presented in [10]. The conjecture poses that every Z2-grading on E has at least one non-zero homogeneous element of L. As a consequence, we obtain a characterization of Ecan by means of its Z2-graded polynomial identities. Furthermore we construct a Z2-grading on E that gives a negative answer to the conjecture.

Theoretical and legal features of key institutions in Municipal Law

It has been established that the institutions of Municipal Law are the key elements of the studied branch of law. This is due to the fact that they are more clear, specific and homogeneous regulatory elements with regard to their subject matter, which allows making certain structural and substantive changes to them without affecting other components of the Municipal Law system. The division into institutes helps to group legal norms that are homogeneous in terms of subject matter and methods of regulation, which contributes to a clearer definition of the main directions of the regulatory impact of Municipal Law and ensures more meaningful and efficient regulation of relevant legal relations, as well as the internal integrity and autonomy of the Municipal Law system.
 The following are proposed to be classified as the institutions of Municipal Law: general principles of local self-government (constitutional and legal norms); guarantee of local self-government; exercise of power by the people through local self-government bodies; principles of organisation and operation of local self-government entities; local elections and referendums; various forms of direct participation of citizens in resolving local issues; territorial communities; executive bodies of village, town, city, district and city councils; village, town and city heads; institution of representative bodies of local self-government; communal property; local budget and local finance; responsibility of local self-government bodies and officials.
 It has been noted that the above-mentioned institutions of Municipal Law are not exhaustive, but they reveal the essence of the relevant branch of law in the most meaningful way. It has been emphasised that an important task of the legislator is to create appropriate legal and organisational conditions for ensuring high-quality and efficient functioning and interaction of all municipal law institutions.

Machine learning based inverse framework for predicting the transverse and shear modulus of carbon fiber

Evaluating the transverse and shear modulus of carbon fibers experimentally is challenging and are usually obtained by an inverse approach using a micromechanical model. This paper presents an inverse approach for predicting the fiber properties from experimentally evaluated properties of the unidirectional (UD) lamina, using a machine learning (ML) based surrogate model. The ML framework is based on Gaussian process regression (GPR), which also provides a measure of uncertainty in the predictions. The ML model is trained using synthetic data generated using Finite Element (FE) homogenization considering different fiber and matrix properties, volume fractions, and fiber distribution. The proposed inverse framework is demonstrated to predict the elastic properties of polyacrylonitrile (PAN)-based fibers used in carbon-epoxy composites that have significant variations (low to high modulus) in its properties (T300-M60J). The fiber properties predicted using the GPR surrogate shows good agreement with the values reported in the literature, with a difference of less than 1.5%. The computational framework is further extended to predict the elastic properties of the woven fabric laminate using multi-scale homogenization. In summary, the results show that the GPR-based surrogate model offers an accurate and computationally efficient alternative to FE-based forward model for predicting the properties of the fiber.

A simple route to synthesize high-entropy carbide (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)C1-δ nanoparticles with large covalent radius difference

Synthesis of high-entropy carbides containing lanthanide elements for improved high-temperature oxidation resistance is still a challenge due to the large covalent radius difference. Nanoparticles of a novel high-entropy carbide ceramic, (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)C1-δ were successfully synthesized by a combination of organic sol-gel route and carbothermal reduction. The (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)Ox crystals with average size of ∼3 nm were synthesized at 220 °C in benzyl alcohol bath, dominated by the nucleation kinetics mechanism. Phase-pure (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)C1-δ was achieved by using the (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)Ox crystals and glucose as the carbon source in Ar atmosphere at 1500 °C. Average crystal size of the (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)C1-δ nanoparticles was ∼30 nm estimated by XRD spectra and TEM, exhibited rock-salt phase and high elemental homogeneity. The synthesis of (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)C1-δ nanoparticles at low temperature was attributed to the fast nucleation that depending on high atomic homogeneity of the ultra-fine (Hf0.2Zr0.2Ti0.2Ce0.2La0.2)Ox crystals.

Hierarchical evaluation of effective thermal conductivities of needled composites

Thermal conductivity (TC) is essential to characterize for thin-walled parts made of needled carbon/carbon (C/C) composites in the aviation sector. This paper thus proposes a hierarchical multiscale model to predict the TCs of needled C/C composites. This model can comprehensively consider the effects of the anisotropy of pyrolytic carbon matrices and the orientation and elongation of pores. At the microscale, representative volume element models of the needled fibers and weftless plies are established, respectively, and their TCs are estimated using the finite element homogenization method. Meanwhile, a combination of the finite element and orientation average method is developed for short-cut fiber plies. At the macroscale, a generated needled laminated model consisting of the weftless plies, short-cut fiber plies, and needled region, is established, where input properties are from homogenization results of microscale models. By comparing with experimental results, the proposed multiscale model is validated. The results show that effective TCs in the directions perpendicular and parallel to needled fibers drop by 13.18% and 13.06% respectively as the porosity increases from 6% to 14%. Additionally, it is found by microstructural parameter studies that it is possible to realize needled C/C composites with isotropic TCs.

Preliminary Characterisation of New Reference Materials (CaW‐0, CaW‐1 and CaW‐3) for Microanalysis of Rare Earth Elements in Scheelite by Laser Ablation‐Inductively Coupled Plasma‐Mass Spectrometry

In this work, we prepared three CaWO4 single crystals (CaW‐0, CaW‐1 and CaW‐3) doped with rare earth elements (REEs) at nominal mass fractions of 50, 250 and 5000 μg g‐1 using the Czochralski method. Electron probe microanalysis (EPMA) and laser ablation‐inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS) were employed to evaluate the within‐ and between‐unit homogeneity of major elements and REEs, respectively. The within‐unit variation (sr) of 0.40–0.84% and between‐unit sr of 0.14–1.48% for major elements were obtained. Within‐ and between‐unit sr of 0.53–5.56% were also found for REEs by LA‐ICP‐MS spot analyses. A comparison of the sr of repeat analyses was compared with the analytical uncertainty (u), i.e., the mean square weighted deviation (MSWD), which is close to or slightly higher than 1, indicating that no obvious chemical heterogeneity was found in these crystals. Reference values for these elements were obtained through various analytical methods across four different laboratories and applications of the reference materials to calibrating REE mass fractions in a natural scheelite were performed. No significant difference of the results was found as t values are less than 2.75 at the 99% confidence interval. The excellent linearity (R2 > 0.98) between the REE mass fractions and both LA‐ICP‐MS signal intensity and wafer absorbance was found, but the crater height and the absolute mass transported into ICP‐MS decreased when REE mass fractions as well as the colour of crystals increased. These results suggest that the reference materials have the potential to calibrate REE mass fractions in natural scheelite.

Predicting effective thermal conductivity of fibrous and particulate composite materials using convolutional neural network

Thermal insulation composite materials, such as aerogels and cellular foams, typically exhibit great performance such as low thermal conductivity and complex microstructures at the nanometer or micrometer scale. However, traditional micromechanics-based methods like homogenization and finite element analysis may not accurately predict their effective thermal conductivity due to a limited understanding of microscopic heat transfer mechanisms and the vast amounts of multi-scale microstructural data. In this paper, the effective thermal conductivity of composite materials is predicted using a convolutional neural network (CNN). To model the microstructure of the composites, digital images are generated using the Quartet Structure Generation Set (QSGS) method and the Random Generation-Growth Method (RGGM). The Lattice Boltzmann Method (LBM) is then used to predict the effective thermal conductivities. The CNN model is trained and validated using the microstructural images as input data and the conductivities predicted by LBM as output data. Subsequently, Parametric studies are conducted to investigate the material characteristics, including volume fraction and microstructural anisotropy. Additionally, the CNN predictions are compared with the results of experiments, analytical models, and computational methods. Finally, the proposed CNN model is utilized to predict the thermal conductivity of materials with novel microstructures that are not included in the training set. By capturing the scattering characteristics of heterogeneous materials through artificial intelligence, the CNN model predicts thermal conductivity more efficiently than traditional methods. This highlights the potential of machine learning to advance materials science and accelerate development of materials with desired properties.