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At least 19 records

Magnetic and Electrical Characteristics of Cobalt-Based Amorphous Materials and Comparison to a Permalloy Type Polycrystalline Material

Magnetic component designers are always looking for improved soft magnetic core materials to increase the efficiency, temperature rating and power density of transformers, motors, generators and alternators, and energy density of inductors. In this paper, we report on the experimental investigation of commercially available cobalt-based amorphous alloys which, in their processing, were subjected to two different types of magnetic field anneals: A longitudinal magnetic field anneal or a transverse magnetic field anneal. The longitudinal field annealed material investigated was Metglas 2714A. The electrical and magnetic characteristics of this material were investigated over the frequency range of 1 to 200 kHz and temperature range of 23 to 150 C for both sine and square wave voltage excitation. The specific core loss was lower for the square than the sine wave voltage excitation for the same maximum flux density, frequency and temperature. The transverse magnetic field annealed core materials include Metglas 2714AF and Vacuumschmelze 6025F. These two materials were experimentally characterized over the frequency range of 10 to 200 kHz for sine wave voltage excitation and 23 C only. A comparison of the 2174A to 2714AF found that 2714AF always had lower specific core loss than 2714A for any given magnetic flux density and frequency and the ratio of specific core loss of 2714A to 2714AF was dependent on both magnetic flux density and frequency. A comparison was also made of the 2714A, 2714AF, and 6025F materials to two different tape thicknesses of the polycrystalline Supermalloy material and the results show that 2714AF and 6025F have the lowest specific core loss at 100 kHz over the magnetic flux density range of 0.1 to 0.4 Tesla.

Wieserman, William R.↗

Implementation and experimental validation of nonlocal damage in a large-strain elasto-viscoplastic FFT-based framework for predicting ductile fracture in 3D polycrystalline materials

Ductile materials, such as metal alloys, can undergo substantial deformation before failure. Additionally, these materials are usually of polycrystalline composition and exhibit strongly anisotropic behavior at small length scales. Previously developed fast Fourier transform (FFT)-based models can model ductile fracture of isotropic materials or the elastic–plastic behavior of anisotropic polycrystalline materials; however, there remains a need to couple both capabilities. This work extends a large-strain FFT-based crystal plasticity model to simulate ductile fracture of polycrystalline materials. In this work, a triaxiality-based continuum damage mechanics (CDM) formulation is incorporated into a large-strain elasto-viscoplastic FFT (LS-EVPFFT) framework. The CDM formulation is augmented with an integral-based nonlocal regularization approach that correctly handles gas-phase material necessary to model unconstrained surfaces. To validate the damage-enabled LS-EVPFFT framework, mesoscale copper tensile coupons were machined using microwire electrical discharge machining and experimentally characterized using electron backscatter diffraction. In-situ optical digital image correlation was performed during uniaxial testing to provide a side-by-side comparison of the experimental and computational strain fields and stress–strain responses. The damage-enabled LS-EVPFFT framework can simulate the complete macroscopic stress–strain response of ductile polycrystals to failure. The model reproduces necking behavior that qualitatively agrees with experimental observations. By leveraging the relatively low computational cost of the damage-enabled LS-EVPFFT framework, the framework presented here allows the ductile fracture response of 3D polycrystalline materials to be tractably predicted.

36 MATERIALS SCIENCE↗

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗

Preferred-orientation analysis of polycrystalline materials

Automatic device built around a goniometer examines characteristics of polycrystalline materials and determines preferred orientations of crystallites. It is automatically rotatable in each of two planes and has circuit regulated sequential rotation. A fixed X ray source in conjunction with a detector examines the material.

De Wys, E. C.↗

Autonomous Polycrystalline Material Decomposition For Hyperspectral Neutron Tomography

Hyperspectral neutron tomography is an effective method for analyzing crystalline material samples with complex compositions in a non-destructive manner. Since the counts in the hyperspectral neutron radiographs directly depend on the neutron cross-sections, materials may exhibit contrasting neutron responses across wavelengths. Therefore, it is possible to extract the unique signatures associated with each material and use them to separate the crystalline phases simultaneously.We introduce an autonomous material decomposition (AMD) algorithm to automatically characterize and localize polycrystalline structures using Bragg edges with contrasting neutron responses from hyperspectral data. The algorithm estimates the linear attenuation coefficient spectra from the measured radiographs and then uses these spectra to perform polycrystalline material decomposition and reconstructs 3D material volumes to localize materials in the spatial domain. Our results demonstrate that the method can accurately estimate both the linear attenuation coefficient spectra and associated reconstructions on both simulated and experimental neutron data.

Samin nur chowdhury, Mohammad↗

Review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semi-empirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produced predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis for fully-dense materials are in good agreement with those calculated from elastic properties.

Roth, D. J.↗

Review and statistical analysis of the use of ultrasonic velocity for estimating the porosity fraction in polycrystalline materials

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semiempirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produces predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis of fully-dense materials are in good agreement with those calculated from elastic properties.

Roth, D. J.↗

Review: Inelastic Constitutive Modeling: Polycrystalline Materials

This article provides a literature review that details the development of inelastic constitutive modeling as it relates to polycrystalline materials. This review distinguishes between inelastic constitutive models that account for nonlinear behavior at the microstructural level, time-independent classic plasticity models, and time-dependent unified models. Particular emphasis is placed on understanding the underlying theoretical framework for unified viscoplasticity models where creep and classical plasticity behavior are considered the result of applied boundary conditions instead of separable rates representing distinct physical mechanisms. This article establishes a clear understanding of the advantages of the unified approach to improve material modeling. This review also discusses recent topics in constitutive modeling that offer new techniques that bridge the gap between the microstructure and the continuum.

36 MATERIALS SCIENCE↗

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

Development of Ceramic Solid-State Laser Host Material

Polycrystalline ceramic laser materials are gaining importance in the development of novel diode-pumped solid-state lasers. Compared to single-crystals, ceramic laser materials offer advantages in terms of ease of fabrication, shape, size, and control of dopant concentrations. Recently, we have developed Neodymium doped Yttria (Nd:Y2O3) as a solid-state ceramic laser material. A scalable production method was utilized to make spherical non agglomerated and monodisperse metastable ceramic powders of compositions that were used to fabricate polycrystalline ceramic material components. This processing technique allowed for higher doping concentrations without the segregation problems that are normally encountered in single crystalline growth. We have successfully fabricated undoped and Neodymium doped Yttria material up to 2" in diameter, Ytterbium doped Yttria, and erbium doped Yttria. We are also in the process of developing other sesquioxides such as scandium Oxide (Sc2O3) and Lutesium Oxide (Lu2O3) doped with Ytterbium, erbium and thulium dopants. In this paper, we present our initial results on the material, optical, and spectroscopic properties of the doped and undoped sesquioxide materials. Polycrystalline ceramic lasers have enormous potential applications including remote sensing, chem.-bio detection, and space exploration research. It is also potentially much less expensive to produce ceramic laser materials compared to their single crystalline counterparts because of the shorter fabrication time and the potential for mass production in large sizes.

Prasad, Narasimha S.↗