Engineering PapersSearch

SEARCH · Engineering Papers

Results for “Magnetic materials”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Frontiers in Magnetic Materials

Magnetism is crucial to many modern technologies, a driver for condensed matter physics research and one of the most remarkable and diverse properties of matter. We propose to develop understanding of novel magnetism and magnetic related behavior in materials and use this to accelerate the discovery of forefront magnetic materials. The approach is via the connection of magnetic properties to specific structures and materials. Topics that will be addressed are (1) Metallic magnetic materials with unusually low carrier concentrations and/or moments (2) Magnetism arising from unusual chemistry including 4d and 5d magnetism and (3) Materials with strong spin-fluctuations, which can lead to quantum criticality, spin-fluctuation induced superconductivity and other novel quantum behavior. These topics overlap, for example, the 4d ruthenates include ferromagnets (perovskite SrRuO 3 ), extremely high ordering temperature antiferromagnets (honeycomb lattice SrRu 2 O 6 ) and well as quantum materials with strong spin fluctuations (layered perovskite Sr 2 RuO 4 and Sr 3 Ru 2 O 7 ). We will use of density calculations to connect magnetic properties with chemistry and structure and employ phenomenological theories to extend these results to properties that are not directly given by direct first principles methods and we will conduct tests to explore the limitations of density functional approximations and new functionals.

36 MATERIALS SCIENCE

The northeast materials database for magnetic materials

The discovery of magnetic materials with high operating temperature ranges and optimized performance is essential for advanced applications. Current data-driven approaches are limited by the lack of accurate, comprehensive, and feature-rich databases. This study aims to address this challenge by using Large Language Models (LLMs) to create a comprehensive, experiment-based, magnetic materials database named the Northeast Materials Database (NEMAD), which consists of 67,573 magnetic materials entries (www.nemad.org). The database incorporates chemical composition, magnetic phase transition temperatures, structural details, and magnetic properties. Enabled by NEMAD, we trained machine learning models to classify materials and predict transition temperatures. Our classification model achieved an accuracy of 90% in categorizing materials as ferromagnetic (FM), antiferromagnetic (AFM), and non-magnetic (NM). The regression models predict Curie (Néel) temperature with a coefficient of determination (R 2 ) of 0.87 (0.83) and a mean absolute error (MAE) of 56K (38K). These models identified 25 (13) FM (AFM) candidates with a predicted Curie (Néel) temperature above 500K (100K) from the Materials Project. This work shows the feasibility of combining LLMs for automated data extraction and machine learning models to accelerate the discovery of magnetic materials.

Ferromagnetism

Degradation of Magnetic Materials for High-Temperature Active Magnetic Bearing Applications in CO₂-Based Environments

High-temperature Active Magnetic Bearings (AMBs) are a promising alternative to conventional bearings in hermetically sealed turbomachinery for supercritical CO₂ (sCO₂) systems. They offer reduced CO₂ leakage, lower windage losses, enhanced misalignment tolerance, reduced wear, and built-in diagnostic capabilities. A critical challenge, however, is ensuring long-term material stability in harsh CO₂-rich environments. This study investigated the degradation behavior of permanent and soft magnetic materials (Alnico 9C, Alnico 5-7C, SmCo 18-T550, Hiperco-50, and coated variants) after up to 6,000 hours of exposure in gaseous CO₂, sCO₂, or air at 450 °C and 550 °C. The evaluation included post-exposure mass change measurements, scanning electron microscopy (SEM) analysis, and magnetic property assessments. The results demonstrate oxidation rates, microstructural evolution, and retention of magnetic performance across conditions. The findings offer essential insights into the thermal corrosion behavior of magnetic materials under CO₂ rich environments and serve as a reference for material selection in AMB system designs.

36 MATERIALS SCIENCE

Block copolymer self-assembly derived mesoporous magnetic materials with three-dimensionally (3D) co-continuous gyroid nanostructure

Magnetic nanomaterials are gaining interest for their many applications in technological areas from information science and computing to next-generation quantum energy materials. While magnetic materials have historically been nanostructured through techniques such as lithography and molecular beam epitaxy, there has recently been growing interest in using soft matter self-assembly. In this work, a triblock terpolymer, poly(isoprene-block-styrene-block-ethylene oxide) (ISO), is used as a structure directing agent for aluminosilicate sol nanoparticles and magnetic material precursors to generate organic–inorganic bulk hybrid films with co-continuous morphology. After thermal processing into mesoporous materials, results from a combination of small angle X-ray scattering (SAXS) and scanning electron microscopy (SEM) are consistent with the double gyroid morphology. Nitrogen sorption measurements reveal a type IV isotherm with H1 hysteresis, and yield a specific surface area of around 200 m 2 g −1 and an average pore size of 23 nm. The magnetization of the mesostructured material as a function of applied field shows magnetic hysteresis and coercivity at 300 K and 10 K. Comparison of magnetic measurements between the mesoporous gyroid and an unstructured bulk magnetic material, derived from the identical inorganic precursors, reveals the structured material exhibits a coercivity of 250 Oe, opposed to 148 Oe for the unstructured at 10 K, and presence of remnant magnetic moment not conventionally found in bulk hematite; both of these properties are attributed to the mesostructure. This scalable route to mesoporous magnetic materials with co-continuous morphologies from block copolymer self-assembly may provide a pathway to advanced magnetic nanomaterials with a range of potential applications.

Chemistry

High-throughput studies of novel magnetic materials in borides

Borides are a versatile material family with various properties for valuable applications. Conventional magnetism, such as ferromagnetism and antiferromagnetism in borides, have been extensively studied. However, research on unconventional magnetism in borides where quantum effects are dominant is scarce. Here, we implement a high-throughput workflow combining first-principles calculations, materials prediction, and magnetic properties calculations to discover novel magnetism and magnetic materials in borides. Successfully applying the workflow, we report three families of novel magnetic borides, including two families of borides exhibiting quantum magnetism. One is a family of dimerized quantum magnets among YCrB 4 -type borides, which provides a rare platform for studying the spin-gap quantum critical point. The other is a family of altermagnets among FeMo2B 2 -type borides, extending the magnetic orderings exhibited by borides beyond conventional ferromagnetism and antiferromagnetism. We also predict a family of magnetic laminate transition metal borides, known as the MAB phases, in the AlFe 2 B 2 -type family, which provide pure-phase or alloying candidates for studying magnetocaloric materials and the associated magnetic transitions. The workflow is expected to be used in further studies of novel magnetism and magnetic materials.

36 MATERIALS SCIENCE

Excitons in van der Waals magnetic materials

Two-dimensional magnetic semiconductors provide a unique platform where long-range magnetic order coexists with strongly bound excitons. Because excitonic states and magnetic moments originate from the same electronic orbitals and couple via intrinsic exchange interactions, optical excitations in these systems exhibit pronounced sensitivity to magnetic order. Recent experiments show unusually strong magneto-optical responses and direct exciton–magnon coupling, establishing new routes for controlling light–matter interactions with spin degrees of freedom. Here, this Review surveys key developments, focusing on representative material systems, experimental signatures, and theoretical frameworks used to describe these phenomena. We conclude with perspectives on how this rapidly evolving field could enable next-generation optoelectronic and quantum technologies leveraging the coupled dynamics of light, charge and spin.

36 MATERIALS SCIENCE

ENVIRONMENTAL DEGRADATION OF HARD AND SOFT MAGNETIC MATERIALS IN GASEOUS AND SUPERCRITICAL CO2 ENVIRONMENTS

It may be beneficial to use hermetic designs for supercritical CO2 (sCO2) cycles machinery as they would eliminate CO2 leakage through shaft end seals. This would reduce CO2 emissions and operating costs for makeup of lost process fluid. Those designs may replace traditional oil-lubricated bearings with actively controlled magnetic bearings operating at high temperatures in the process fluid environment (to reduce the need for active cooling). This paper investigates the material degradation of various types of magnets in CO2. Included are several permanent and soft magnetic materials (Alnico 9C, Alnico 5-7C, and 18-T550 grade SmCo, and Hiperco 50) with or without coatings (nickel plating or C5 coating). The materials were exposed to: (1) flowing gaseous CO2 at 1,022 °F (550 °C) and atmospheric pressure in a furnace and (2) sCO2 at 842 °F (450 °C) and 1,500 psi (103 bar) in an autoclave. The preliminary mass change measured after total exposures of 1,000 hours and 2,000 hours are included.

supercritical CO2, magnetic material

Leveraging the redox activities of cerium and dibenzotetrathiafulvalene to discover a photo-responsive magnetic material

Stimuli-responsive changes in lanthanide-based materials are a promising research direction. In this study, [DBTTF] 4 [Ce 2 Cl 10 ] DBTTF = dibenzotetrathiafulvalene (1) was synthesized by a light-induced crystallization, where photo-oxidation of DBTTF enables formation of the cerium dimer [Ce 2 Cl 10 ] 4− . Intermolecular interactions between the stacked organic units of the crystal result in charge transfer bands in the visible-NIR (near-infrared) region, evident in the solid-state absorption spectrum upon comparison with the solution spectrum. The assignments of the sublattice oxidation states were made with single-crystal X-ray diffraction (SC-XRD) structural characterization, Raman spectroscopy, X-ray absorption spectroscopy, and magnetometry. Continuous 532 nm laser irradiation of the microcrystalline solid modulates the redox states in 1, leading to ∼40% reduction in the observed magnetization at 2 K. Density functional theory PBE+U/HSE06 band structure calculations predict Mott insulating behavior in 1, with a bandgap of 0.54/0.81 eV, and further support the conjecture that the observed photo-induced change in magnetization results from electron transfer from the [Ce 2 Cl 10 ] 4− anions to the π-stacked [DBTTF] 2 2+ organic dimer subunits. An enhancement in conductivity is similarly observed upon 532 nm irradiation, determined by single-crystal transport measurements. The findings reveal that photo-responsive lanthanide-based materials can be achieved by integration of redox-active organic moieties with redox-active lanthanide cations for the realization of switchable, photo-magnetic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

High-performance permanent-magnet materials based on CeFe 12

We perform first-principles calculations on the Mo/Zr-alloyed ThMn 12 -structure prototype CeFe 12 to explore its electronic and magnetic properties and potential for permanent magnet applications. A recent experiment has shown that the Mo/Zr-alloyed CeFe 12 phase with the symmetry 𝐼⁢4/𝑚⁢𝑚⁢𝑚 can be stabilized in bulk. It encourages an investigation into the intrinsic magnetic characteristics of the base structure CeFe 12 and the effect of transition metal alloying in it. Our calculations reveal that the base structure prototype CeFe 12 in its tetragonal phase exhibits uniaxial magnetic anisotropy with a magnetic anisotropy energy (𝐾 1 ) ∼ 1 MJ/m −3 and a substantial magnetic moment of ∼ 1.8T, showing its promise as a permanent magnet. The introduction of the stabilizing transition metals Zr, Mo, and W reduces these values but still keeps the materials very promising. Notably, when 50% of Ce is substituted by Sm in Mo-alloyed CeFe 12 , the 𝐾 1 is significantly enhanced, accompanied by a fairly decent magnetic moment of ∼ 1.2T. These findings establish this alloy as a strong candidate for high-performance permanent magnet applications. In conclusion, this study emphasizes the importance of strategic element substitution and site selection in transition metal-alloyed CeFe 12 to achieve both structural stability and remarkable magnetic properties.

Density of states

Irradiation-induced gas production in REBCO-based magnet materials used for future compact fusion reactors

Nuclear fusion is an enticing alternative to current sources of energy, with multilayered Rare-Earth Barium Copper Oxide (REBCO) coated conductors deemed pivotal in the race toward fully realized, commercially viable, and magnetic confinement fusion reactors. In this study, we simulated the ion spectrum expected to evolve from REBCO's nickel-based Hastelloy C-276 substrate and copper stabilizer in an affordable robust compact-like reactor. We then emulated this gas production through helium implantation to investigate changes in materials and superconducting properties. Our results revealed that the substrate and stabilizer are capable of producing protons energetic enough to recoil throughout the tape thickness in appreciable doses, and alphas energetic enough to deposit 7.54 × 1014 ions/cm2 or 50.1 helium appm in the superconducting layer over a 30-year reactor lifetime. The superconducting layer of SuperPower® tapes exhibited at least double the swelling rate of the other major layers, and both SuperPower and Fujikura Ltd. tapes displayed microstructural changes in the REBCO layer not observed in isotropic metals. For the estimated lifetime fluence, the Fujikura tapes showed a ∼1 K reduction in critical temperature and a 32% degradation in critical current for compact reactor-relevant conditions (16 T, 20 K). Nuclear transmutation, low-temperature solder implantations, gas-ion evolution, the influence of gas production on vortex dynamics, and other related considerations are also discussed.

Reis, Chris

Review of honeycomb-based Kitaev materials with zigzag magnetic ordering

The search for a Kitaev quantum spin liquid in crystalline magnetic materials has fueled intense interest in the two-dimensional honeycomb systems. Many promising candidate Kitaev systems are characterized by a long-range-ordered magnetic structure with an antiferromagnetic zigzag-type order, where the static moments form alternating ferromagnetic chains. Recent experiments on high-quality single crystals uncovered the existence of intriguing multi-k magnetic structures, which evolved from zigzag structures. Those discoveries have sparked new theoretical developments and amplified interest in these materials. We present an overview of the honeycomb materials known to display this type of magnetic structure and provide detailed crystallographic information for the possible single- and multi-k variants.

36 MATERIALS SCIENCE

To Substitute Rather Than Intercalate: Chimie douce Approach to Induce Ferromagnetism in Metastable Pt 0.8 M 0.2 Se 2 ( M = Cr, Co, Ni)

Two-dimensional (2D) magnetic materials with exotic magnetic properties have garnered significant interest due to their potential applications in spintronics and data storage technologies. However, the limited availability of intrinsic 2D magnetic materials has driven efforts to induce and manipulate magnetism in otherwise nonmagnetic 2D systems through approaches such as chemical intercalation, defect engineering, and substitutional doping. Herein, we present a facile, chimie douce method for incorporating 3d transition metals (Cr, Co, and Ni) into the nonmagnetic PtSe 2 sublattice. This synthetic approach enables control over layer thickness of Pt 1–x M x Se 2 (M = Cr, Co, Ni) nanosheets by varying the M identity and annealing conditions. Comprehensive scattering and spectroscopic characterizations confirm the successful and homogeneous substitution of M atoms at the Pt site, rather than intercalation, and reveal a strong correlation between nanosheet thickness and the identity of the substituting metal. High-temperature annealing of the nanosheets promotes an irreversible transformation toward the bulk phase, allowing for detailed characterization of structural and magnetic properties. A case study of Pt 0.8 Cr 0.2 Se 2 reveals that nanosheet thickness plays a critical role in modulating local magnetic interactions. While Cr atoms in the as-synthesized few-layers-thick nanosheets exhibit predominantly short-range antiferromagnetic interactions, the emergence of short-range ferromagnetic exchange is revealed in the bulk material. Detailed ac susceptibility and remanent magnetization measurements further demonstrate that bulk Pt 0.8 Cr 0.2 Se 2 adopts a frustrated magnetic ground state with clear signatures of ferromagnetic cluster-glass behavior. The systematic investigation presented herein establishes a clear and robust protocol for the synthesis and in-depth characterization of 2D transition-metal-substituted PtSe2 materials with varying layer thickness and paves a path toward their realization in spintronic and magnetic device applications.

crystallinity

Self-Cooling Multiferroic Magnetic Devices

Increasing switching frequency reduces magnetic volume, but conventional ferrites, used from tens to hundreds of kilohertz, cannot sustain the temperature and frequency ranges demanded by current and emerging wide bandgap and ultrawide bandgap devices. Here, this work presents a novel magnetic material architecture combining nanocrystalline magnetic material and multiferroic layers for megahertz power conversion. The high saturation flux density of nanocrystalline alloys supports miniaturization but is traditionally constrained by excessive losses above 10 kHz. A revolutionary multiferroic material with solid-state cooling via caloric materials is defined that will enable the next generation of magnetic devices for wide-bandgap-integrated designs. This letter highlights the fundamental physics behind this capability alongside early development of a finite element analysis for the multiferroic-based magnetic device using ANSYS, showing that the core achieves more uniform thermal distribution and reduces peak temperature by 9 ° C compared to conventional ferrites.

Soft magnetic materials

Circumventing data imbalance in magnetic ground state data for magnetic moment predictions

Abstract Magnetic materials play a crucial role in the transition to more sustainable forms of energy and electric vehicles. There is an anticipated shortage in magnetic materials in the future, and as a result there is an urgent need to discover and design new magnetic materials. Computational magnetic material design using density functional theory is daunting because of the challenge in identifying magnetic ground states from a combinatorially large set of possibilities. Machine learning offers a path forward by enabling efficient surrogate models that can more readily enumerate these states, but there is a dearth of training data available, and what is available tends to be imbalanced with too much non-magnetic data. In this work we show that the discrete and previously tackled data imbalance that exists at the level of the magnetic ordering leads to an imbalanced continuous distribution with many zeros when the data is unraveled at the atomic magnetic moment level, which subsequently leads to models with low accuracy for magnetic properties. We mitigate this by using a two-part model framework. Our scheme is able to classify atoms into magnetic and non-magnetic with an F1 score and Matthew’s correlation coefficient (MCC) of ~91% and then to provide an implicit embedding representation that maps directly onto the magnitude of the magnetic moment with a mean absolute error of 0.1 μ B . Beyond screening for new magnetic materials, we demonstrate an additional practical use case of our scheme: the provision of good initial guesses for magnetic moments in first-principles electronic relaxations. Such initialization is shown to lead to faster convergence to configurations that lie closer to the ground state.

Computer Science

Systematic determination of a material’s magnetic ground state from first principles

Abstract We present a self-consistent method based on first-principles calculations to determine the magnetic ground state of materials, regardless of their dimensionality. Our methodology is founded on satisfying the stability conditions derived from the linear spin wave theory (LSWT) by optimizing the magnetic structure iteratively. We demonstrate the effectiveness of our method by successfully predicting the experimental magnetic structures of NiO, FePS 3 , FeP, MnF 2 , FeCl 2 , and CuO. In each case, we compared our results with available experimental data and existing theoretical calculations reported in the literature. Finally, we discuss the validity of the method and the possible extensions.

Chemistry

Zentropy Theory for Transformative Functionalities of Magnetic and Superconducting Materials

The proposed research developed the zentropy theory through applications to complex magnetic materials and superconductors under the hypothesis that the emergent properties of complex magnetic materials and superconductors can be predicted by statistical mechanics of ergodic microstates with their partition functions computed from DFT-predicted free energies. The key objective is to develop approaches to systematically determine the types and number of microstates and the supercell size in DFT-based calculations through convergency of macroscopic functionalities, with the incorporation of our mixed-space approach accounting for the interactions between periodic supercells. In addition to use scientific intuitions to guide the design of important microstates, the key innovation of the proposed research is to integrate the domain knowledge and the material-property-descriptor database (MPDD) with 4 million microstates, which is supported by our deep neural network machine learning models (SIPFENN: structure-informed prediction of formation energy using neural networks) and integrated with our high throughput DFT Tool Kit (DFTTK). For complex magnetic materials, one of the objectives is to develop approaches to calculate short-range ordering from the statistical distribution of each microstate. For superconductors, the divergency of quasiparticle effective mass at a quantum critical point will be investigated, and the superconducting and non-superconducting microstates will be delineated through analysis of electronic band structure, density of states, charge density, and Fermi surface.

36 MATERIALS SCIENCE

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE

Quantitative phase retrieval and characterization of magnetic nanostructures via Lorentz (scanning) transmission electron microscopy

Magnetic materials phase reconstruction using Lorentz transmission electron microscopy (LTEM) measurements have traditionally been achieved using longstanding methods such as off-axis holography (OAH) fast-Fourier transform technique and the transport-of-intensity equation (TIE). The increase in access to processing power alongside the development of advanced algorithms have allowed for phase retrieval of nanoscale magnetic materials with greater efficacy and resolution. Specifically, reverse-mode automatic differentiation (RMAD) and the extended electron ptychography iterative engine (ePIE) are two recent developments of phase retrieval that can be applied to analyzing micro-to-nano- scale magnetic materials. This work evaluates phase retrieval using TIE, RMAD, and ePIE in simulations of Permalloy (Ni 80 Fe 20 ) nanoscale islands, or nanomagnets. Extending beyond simulations, we demonstrate total phase retrieval and image reconstructions of a NiFe nanowire using OAH and RMAD in LTEM and ePIE in Lorentz-mode-4D scanning transmission electron microscopy experiments and determine the saturation magnetization through corroborations with micromagnetic modeling. Finally, we demonstrate the efficacy of these methods in retrieving the total phase and highlight its use in characterizing and analyzing the proximity effect of the magnetic nanostructures.

Lorentz transmission electron microscopy