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At least 91 records · Page 5

Magnetized Winds of M-type Stars and Star–Planet Magnetic Interactions: Uncertainties and Modeling Strategy

M-type stars are the most common stars in the Universe. They are ideal hosts for the search of exoplanets in the habitable zone (HZ), as their small size and low temperature make the HZ much closer-in than their solar twins. Harboring very deep convective layers, they also usually exhibit very intense magnetic fields. Understanding their environment, in particular their coronal and wind properties, is thus very important, as they might be very different from what is observed in the solar system. The mass-loss rate of M-type stars is poorly known observationally, and recent attempts to estimate it for some of them (e.g., TRAPPIST-1 and Proxima Centauri) can vary by an order of magnitude. In this work, we revisit the stellar wind properties of M dwarfs in the light of the latest estimates of $\dot{M}$ through Lyα absorption at the astropause and slingshot prominences. We outline a modeling strategy to estimate the mass-loss rate, radiative loss, and wind speed, with uncertainties, based on an Alfvén-wave-driven stellar wind model. We find that it is very likely that several TRAPPIST-1 planets lie within the Alfvén surface, which implies that these planets experience star–planet magnetic interactions (SPMIs). We also find that SPMIs between Proxima Cen b and its host star could be the reason for recently observed radio emissions.

M stars

Final Technical Report for DoE award DE‐SC0023367 “Energetic Electron Transport in Magnetized Plasma with Magnetic Islands”

This project investigated how plasmas interact with energetic particles and solid materials under extreme conditions relevant to fusion energy, space plasmas, and planetary environments. Using experiments on the DIII-D National Fusion Facility, the research first examined how high-energy electrons move, become trapped, and are released in plasmas containing magnetic islands—structures commonly found in fusion reactors and Earth’s magnetosphere—providing new insight into particle transport and acceleration processes. The project also explored plasma-driven chemical reactions that can occur during meteoroid entry into planetary atmospheres, demonstrating that simple molecules such as ammonia can be produced and survive in high-temperature plasma conditions. Together, these results improve understanding of plasma behavior across laboratory, space, and planetary systems while informing fusion plasma control and plasma–material interaction studies. The project additionally contributed to workforce development by training graduate students, undergraduates, and early-career researchers and by disseminating results through peer-reviewed publications and international scientific conferences.

Orlov, Dmitri Mikhailovich [UC San Diego] (ORCID:0

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING

Magnetic fly-ash geopolymer for heavy metal removal in aqueous solutions

Novel magnetic geopolymers were manufactured by synthesizing magnetic Fe 3 O 4 particles on the surface of prepared geopolymer (Method 1) or by incorporating pre-synthesized magnetic Fe 3 O 4 particles into the geopolymer during the manufacture of the geopolymer (Method 2). This study evaluated the effect of the incorporated magnetic Fe 3 O 4 on the geopolymer magnetic, physical, and adsorption properties and its separation in aqueous solutions. Based on several preliminary measurements on the synthesized magnetic geopolymers, Method 2 was found to be a better method for producing magnetic geopolymer. Magnetic geopolymer synthesized by Method 2 exhibited ferromagnetic properties comparable to that of magnetic Fe 3 O 4 , with a saturation magnetization of 8 emu·g −1 and an intrinsic coercivity of 265 Oe. The magnetic geopolymer was efficiently separated from an aqueous solution within 2 min using a 0.48-T magnetic field. In addition, the magnetic geopolymer has a maximum copper adsorption capacity of 111.1 mg·g −1 , which was similar to the non-magnetic reference geopolymer indicating that the addition of magnetic Fe 3 O 4 did not compromise the geopolymer adsorption capacity. The magnetic geopolymer is a promising material with good adsorption and separation properties that can be used for heavy metals removal and recovery in wastewater and metals separation in industrial processes.

fly ash

Modelling pulsed field magnetization of iron-based bulk superconductors

Abstract Bulk superconductors can be used as super-strength quasi-permanent magnets capable of providing magnetic flux densities considerably superior to conventional permanent magnets. This makes them attractive for several engineering applications that rely on strong magnetic fields like rotating machines, NMR/MRI and magnetic drug delivery systems. Recently, the authors reported a record trapped magnetic field in an iron-based bulk superconductor: 2.83 T was trapped in potassium-doped barium iron arsenide (Ba, K)Fe 2 As 2 (or Ba122) at 5 K. Of particular significance is that the strength and temporal stability of this magnetic field exceeds the requirements of MRI machines, indicating iron-based bulks can now perform at levels demanded by engineering applications. One crucial challenge for their practical use, however, is the need to apply and remove an external magnetic field to magnetize them. Pulsed field magnetization (PFM) shows great promise as a practical method of magnetizing bulks, but the process generates heat in the bulk that is detrimental to its superconducting performance and ability to act as a super-strength magnet. In this paper, coupled electromagnetic–thermal numerical models are used to simulate the PFM of iron-based bulk superconductors. Here we focus on the recent-record-breaking, fine-grain polycrystalline K-doped Ba122 bulks. The impact that the specific J c ( B ) characteristics and thermal properties of the Ba122 material—all of which have been experimentally measured from state-of-the-art samples—have on the magnetic flux dynamics and thermal behaviour during PFM, including the final trapped field, is investigated. We show that because the thermal properties are similar to those of REBa 2 Cu 3 O 7 −δ bulks, a similar response to pulsed fields is obtained. A maximum trapped field of ∼0.81 T (∼43.3% of the maximum trapped field capability under ideal, field-cooling conditions) was simulated at 5 K, with a magnetization efficiency of ∼54%. The modelling framework provides a fast and flexible tool for optimising the practical PFM process at different operating temperatures to maximise the trapped field in state-of-the-art Ba122 bulks and to guide the design of future experiments.

bulk superconductors

Distributed Magnetic Field and Temperature Monitoring for Superconducting Radio Frequency Cavities

The overall objective of the proposed Phase I program was to design, construct and demonstrate a fiber optic sensing system capable of providing temperature and magnetic field measurements with an enhanced spatial resolution that can be implemented over a large surface area (cryomodules) to survey superconducting radio frequency cavities and magnets. A magnetic field sensor capable of detecting fluxes on the order of 1 μT is required to detect the distribution of trapped flux on the cavity surface. A unique distributed magnetic field sensor was successfully designed and constructed to demonstrate the detection of magnetic fluxes less than 500 nT. The sensor leveraged the ultra-high sensitivity of Sentek’s picoDAS to measure the magnetostriction induced vibrations in a commercially available Metglas 2605 SC ribbon that was in physical contact with sensing fiber. Static magnetic fields were detected by applying an alternating current a copper wire proximate to the Metglas 2605SC ribbon to create an AC bias magnetic field. In an alternative approach, an AC bias magnetic field was applied to a special magnetic field sensing fiber with Metglas 2605SC cladding successfully detect a magnetic field flux of a 3 μT. Exhaustive testing was performed to characterize the dependency of sensor response on the direction of the applied magnetic field. Although the special sensing fiber based magnetic field sensor did not exhibit an observable dependence on the direction of the magnetic field, the Metglas 2605SC ribbon sensor exhibited a clear directional dependence. A wide variety of polymer materials were evaluated to enhance the temperature response of an FBG based sensor at cryogenic temperatures. The processing and performance challenges provided the motivation to develop a new simple cryogenic temperature sensor that uses a commercially available fiber optic splice protector. The EVA hot melt tube that becomes adhered to the optical fiber and the polyolefin outer tube that shrinks upon heating in the fusion splicer heater provide the high thermal expansion coefficient necessary to impart a significant strain on the FBG when exposed to cryogenic temperatures. The temperature sensitivity (Δ𝜆𝐵𝑟𝑎𝑔𝑔~ 62 𝑝𝑝𝑚/℃) of the FBG-based sensor was on par with the best reported to date. The simple design, use of readily available cost-effective materials, and well-established processing techniques lends this approach to the creation of hundreds to thousands of temperature sensors on one single optical fiber length. The inherently small form factor also allows for co-location with the distributed magnetic field sensor. In preparation for field testing of the prototype sensing system at the Jefferson Labs in potential Phase II program, several different cable designs were evaluated to package the sensors. The preliminary successful demonstration of fully functional sensing cables provides the foundation for subsequent development efforts to advance the Technology Readiness Level of the technology. The technical feasibility of the proposed approach was successfully demonstrated in this Phase I effort.

43 PARTICLE ACCELERATORS

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

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

Quantum Imaging of Ferromagnetic van der Waals Magnetic Domain Structures at Ambient Conditions

Recently discovered 2D van der Waals magnetic materials, and specifically iron–germanium–telluride (Fe5GeTe2), have attracted significant attention both from a fundamental perspective and for potential applications. Key open questions concern their domain structure and magnetic phase transition temperature as a function of sample thickness and external field, as well as implications for integration into devices such as magnetic memories and logic. Here we address key questions using a nitrogen-vacancy center based quantum magnetic microscope, enabling direct imaging of the magnetization of Fe5GeTe2 at submicrometer spatial resolution as a function of temperature, magnetic field, and thickness. This quantum imaging technique provides noninvasive, high-sensitivity measurements with high spatial resolution under ambient conditions, making it particularly well suited for probing 2D magnets. We employ spatially resolved measures, including magnetization variance and cross-correlation, and find a significant spread in transition temperature yet with no clear dependence on thickness down to 15 nm. We also identify previously unknown stripe features in the optical as well as magnetic images, which we attribute to modulations of the constituting elements during crystal synthesis and subsequent oxidation. Our results suggest that the magnetic anisotropy in this material does not play a crucial role in their magnetic properties, leading to a magnetic phase transition of Fe5GeTe2 which is largely thickness-independent down to 15 nm. Our findings could be significant in designing future spintronic devices, magnetic memories, and logic with 2D van der Waals magnetic materials.

Bindu, Bindu [Hebrew University of Jerusalem, Isra