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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.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Charge correlations and magnetoelastic coupling in intercalated transition metal dichalcogenides

The large van der Waals gap in transition metal dichalcogenides (TMDs) offers an avenue to tune the ground state of 2D materials through the intercalation of magnetic atoms. Here, we investigate the charge correlations in Fe 1/3 ⁢TaS 2 , Co 1/3 ⁢TaS 2 , and Fe 0.35 ⁢NbS 2 by combining angle-resolved photoemission spectroscopy (ARPES), x-ray scattering, magnetometry, and density functional theory (DFT). We find that, while short-range charge fluctuations develop in Ta-based compounds, Fe 0.35 ⁢NbS 2 exhibits long-range charge order which is strongly coupled with magnetic order and tunable by external magnetic field. Our electronic structure analysis reveals that intercalation reconstructs the Fermi surface via charge transfer and band renormalization, yet does not generate the nesting conditions compatible with the observed ordering vectors. Complementary phonon calculations further exclude a conventional electron-phonon origin of charge order. Together, these results establish magnetoelastic coupling as the dominant mechanism behind charge ordering in Fe 0.35 ⁢NbS 2 and highlight the contrasting role of Nb and Ta hosts in stabilizing correlated ground states in intercalated TMDs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Characterization of Impedance and Stability for Doubly-Fed Induction Generator Based on Voltage-Modulated Direct Power Control

Voltage-modulated direct power control (VM-DPC) applied to the doubly-fed induction generator (DFIG) offers superior steady-state and transient performance but remains underexplored for suppressing wideband oscillations. Here, this article proposes a comprehensive impedance for the VM-DPC-based DFIG, analyzing its impedance characteristics and stability mechanisms compared with the DFIG based on vector-oriented control (VOC). The unified power transfer function is defined for DFIGs employing VM-DPC or VOC to ensure consistent comparison benchmarks. The comprehensive impedance of VM-DPC-based DFIG, incorporating mechanical and grid-side converter (GSC) dynamics, is derived using complex vector modeling in the αβ -frame. Furthermore, the influence of VM-DPC parameters and grid strength on the stability of grid-connected DFIG systems is assessed through eigenvalue trajectory analysis. Impedance analysis reveals the significant contributions of mechanical and GSC dynamics to DFIG impedance, as well as the narrower frequency range of negative resistance in the VM-DPC-based DFIG compared to the VOC-based DFIG. Stability analysis identifies the VM-DPC parameters of the rotor-side converter as dominant factors affecting system stability and confirms that the VM-DPC-based DFIG achieves better stability under weak grid conditions than its VOC-based counterpart. These findings are validated through simulations and experiments.

42 ENGINEERING↗
DOE OSTI2025

Adiabatic quantum support vector machines

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic quantum approach for training support vector machines. We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach. Next, we compare the test accuracy of our quantum approach against a classical approach that uses the Scikit-learn library in Python across five benchmark datasets (Iris, Wisconsin Breast Cancer (WBC), Wine, Digits, and Lambeq). We show that our quantum approach obtains accuracies on par with the classical approach. Finally, we perform a scalability study in which we compute the total training times of the quantum approach and the classical approach with an increasing number of features and an increasing number of data points in the training dataset. In conclusion, our scalability results show that the quantum approach obtains a 3.5–4.5x speedup over the classical approach on datasets with many (millions of) features.

Computational Complexity↗
DOE OSTI2024

Minimum entropy filtering for a single output non-Gaussian stochastic system using state transformation

This paper presents a novel filter design for the single-output stochastic non-linear systems subjected to non-Gaussian noises and the proposed assumptions. Based on a state transformation, the unmeasurable states of the systems can be estimated where non-linear terms in the systems have been eliminated. It has been shown that the estimation error is linearly dynamical regarding to the presented vector-valued filter gain which can be optimised by minimising the entropy-based performance criterion. In addition, the convergence of the presented algorithm is analysed in mean-square sense and a numerical example is given to verify the effectiveness of the presented filtering algorithm. Meanwhile, the extended Kalman filter, unscented particle filter and minimum entropy filter are given for the comparisons of the filtering performance. Following the presented framework, some extensions of the presented filtering algorithm are discussed to indicate the flexibility of the filter design. The contribution of this paper can be summarised as establishing a novel minimum entropy filtering framework which consists of model transformation, entropy optimisation and convergence analysis.

42 ENGINEERING↗
DOE OSTI2026

Resonance contributions to radiative corrections in charged-current elastic (anti)neutrino-nucleon scattering at GeV energies

We present the first evaluation of virtual resonance contributions to the charged-current elastic (anti)neutrino-nucleon scattering at GeV energies, focusing on the dominant Δ(1232) resonance. We approximate the vector part of the N → Δ transition by the leading magnetic dipole term. Our results for the cross-section corrections at fixed neutrino energy indicate the permille-level contribution of resonance intermediate states to the elastic and radiative scattering cross sections. This calculation exhibits the expected infrared behavior of the invariant amplitudes and unpolarized cross sections. Our findings provide important insights into inelastic excitations in the charged-current elastic (anti)neutrino-nucleon scattering at GeV energies.

Electroweak interaction↗
DOE OSTI2025

Elucidating the Dynamics of Electroweak Symmetry Breaking through Study of High-Multiplicity Boson Final States at the LHC

To understand the full story of the electroweak symmetry breaking (EWSB) and how the universe arrived at today’s universe, the structure of the Higgs potential needs to be probed. We must carefully select and study processes at the LHC that are sensitive to the Higgs potential. In this context, longitudinal vector boson scattering (VBS) processes, V L V L →V L V L , and di-Higgs production, including V L V L →HH at the LHC have been studied for any potential deviation from SM prediction. However, many classes of models beyond the Standard Model (BSM) may result in the 2→2 process being perfectly well-behaved and SM-like but show interesting deviations in 2→3, 2→4, or 2→n(3) processes. If we are to complete the mission objectives the P5 laid out, then a large swath of 2→n(3) must be thoroughly searched and checked. The research supported by this award used data collected at the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) to explore VBS produced VVH process in the semi-merged channel. In addition, in the electroweak sector, there are open questions in the multi-gauge boson couplings and the Higgs couplings to the gauge bosons. The research supported by the award also studied the triboson production WWZ process at the LHC, which is a crossed diagram of a VBS process. During the funded period of 9 months, the analysis designs have been finalized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

XY-like incommensurate magnetic order in Ce 2 ⁢SnS 5

We report the synthesis of single crystals of Ce 2 ⁢SnS 5 through a two-stage chemical vapor transport method. The Ce 2 ⁢SnS 5 system is a member of the orthorhombic Pbam (No. 55) space group and realizes a distorted trigonal tricapped prism (TTP) crystal field around each cerium site. We characterized the sample through orientation-dependent magnetization and heat capacity measurements to probe the magnetic anisotropy in the system characteristic of XY-like anisotropic Heisenberg model behavior. Ce 2 ⁢SnS 5 furthermore enters a zero-field ordered phase under 𝑇 𝑁 =2.4 K; powder neutron diffraction measurements reveal incommensurate magnetic order near 𝑇 𝑁 . Furthermore, the system then locks into a commensurate, two-𝑞 magnetic structure below approximately 1.2 K. This commensurate structure belongs to the Shubnikov group 𝑃⁢𝑏′⁢𝑎′⁢𝑚′ ⁡(MSG 55.359) and realizes the propagation vectors $\overrightarrow{𝑞}$ = (1/3, 0, 0) and $\overrightarrow{𝑞}$ = (0, 0, 0).

Antiferromagnetism↗
DOE OSTI2026

Theory uncertainties of the irreducible background to VBF Higgs production

Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, we perform a detailed study of similarities and differences in existing event generators. We provide consistent setups for the simulations that can be used to obtain identical parametric precision in various programs used by experiments. We find that NLO calculations for the two-jet final state are essential to achieve reliable predictions.

Chen, Xuan [Shandong U.] (ORCID:0000000167722196)↗
DOE OSTI2025

Production cross sections of light and charmed mesons in 𝑒 + ⁢𝑒 − annihilation near 10.58 GeV

We report measurements of production cross sections for 𝜌 + , 𝜌 0 , 𝜔, 𝐾* + , 𝐾* 0 , 𝜙, 𝜂, 𝐾$^0_𝑆$, 𝑓 0 ⁡(980), 𝐷 + , 𝐷 0 , 𝐷$^+_𝑠$, 𝐷* + , 𝐷* 0 , and 𝐷*$^+_𝑠$ in 𝑒 + ⁢𝑒 − collisions at a center-of-mass energy near 10.58 GeV. The data were recorded by the Belle experiment, consisting of 571 fb −1 at 10.58 GeV and 74 fb −1 at 10.52 GeV. Production cross sections are extracted as a function of the fractional hadron momentum 𝑥 𝑝 . The measurements are compared to pythia Monte Carlo generator predictions with various fragmentation settings, including those that have increased fragmentation into vector mesons over pseudoscalar mesons. The cross sections measured for light hadrons are consistent with no additional increase of vector over pseudoscalar mesons. The charmed-meson cross sections are compared to earlier measurements—when available—including older Belle results, which they supersede. They are in agreement before application of an improved initial-state radiation correction procedure that causes slight changes in their 𝑥 𝑝 shapes.

fragmentation functions↗
DOE OSTI2025

Electronic and magnetic properties of hole-doped topological kagome Fe 1−𝑥 ⁢Mn 𝑥 ⁢Sn thin films

We have investigated the electronic and magnetic structures of topological kagome Fe 1−𝑥 ⁢Mn 𝑥 ⁢Sn (0 ≤ 𝑥 ≤ 0.3) thin films via neutron diffraction, electronic transport measurements, and ab initio density functional theory (DFT) to understand the interplay between hole doping, magnetism, and the electronic structures. Temperature-dependent neutron diffraction measurements on parent FeSn reveal the Néel temperature to be 𝑇 N ∼ 355 K and the underlying A-type antiferromagnetic ordering is associated with a wave vector 𝒒 = (001/2). Upon Mn doping to 𝑥 = 0.15, 𝑇 N decreases slightly while the magnetic ordering vector remains the same. Resistivity measurements show metallic characteristics and in-plane anisotropy down to 10 K for all the investigated samples. The effects of hole doping are mapped in terms of electronic ground state calculations via DFT which show that the Dirac point is moved closer to the Fermi level (𝐸 F ) and the flat bands get pushed away from 𝐸 F upon hole doping. However, a comparison between hole-doped Fe 1−𝑥⁢ Mn 𝑥⁢ Sn and electron-doped Fe 1−𝑥 ⁢Co 𝑥 ⁢Sn indicates that the Néel temperature does not scale with the position of 𝐸 F relative to the flat band. Furthermore, our results establish the antiferromagnetic state of FeSn and Fe 1−𝑥 ⁢Mn 𝑥⁢ Sn films at room temperature, laying the groundwork for future studies of magnetism in kagome heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Photoproduction of K0K0-bar with the GlueX Experiment

In this dissertation, we study photoproduction of K0 ?K 0 through the KSKLp and KSKSp ?nal states with the GlueX Phase-I (GlueX-I) data set. We measure the spin-density matrix elements (SDMEs) and di?erential cross section of ?(1020) ! KSKL to better understand photoproduction of light vector mesons. A mass independent Partial Wave Analysis (PWA) of the KSKL and KSKS meson spectrum below 2 GeV is also undertaken to study the meson spectrum with JPC = even++ and odd??. The ?(1020) di?erential cross section is measured at E = 8:2 ? 8:8 GeV and ?t = 0:15 ? 1:00 GeV2. The di?erential cross section is well described by an exponential decay with slope 4:44?0:01 GeV?2 and the integrated cross section is determined to be 295:7?0:4 nb, only statistical uncertainties are quoted. Both measurements are consistent and far more precise than the previous measurement by Ballam et al. [1]. The ?(1020) SDMEs were measured in nine bins of ?t in the same range. At low ?t, we ?nd the data were consistent with s-channel helicity conservation, SCHC, i. e. the only non-zero SDMEs were ?1 1?1 = ?Im(?2 1?1) = 1=2. At higher ?t, the SDMEs deviate from SCHC and the measurements indicate this is due to natural parity exchange since we observe that the SDMEs are consistent with zero unnatural exchange. We also ?find that the contribution from helicity double-flip amplitudes is consistent with zero. The measured SDMEs are in poor agreement with theoretical predictions put forward by JPAC [35]. These measurements will serve as input to re?ne models of production processes, which will be essential for the interpretation of possible signals of exotic mesons in GlueX. Analysis of the spectrum above the ?(1020) indicates the presence of at least three particles at ? 1:50, ? 1:75, and 2:20 GeV. We employ simple parametrizations of the resonance line shape based on relativistic Breit-Wigner functions considering cases with and without interference. The resonance at ? 1:50 GeV is not identifi?ed as any specifi?c resonance, but could be due to interference between the ?(1450) and !(1420). Our models favor the resonance at ~1:75 GeV as the X(1750) rather than the ?(1680). We ?find that introducing a third Breit-Winger into the models improves the ?t quality with the ?2/ndf going from 1.75 to 1.59 and 1.41 to 1.18 for models without and with interference respectively. A PWA of the KSKL spectrum indicates that the spectrum is consistent with exclusively spin-1 contribution up to ? 1:6 GeV. Above ? 1:6 GeV we ?find evidence for a small spin-3 contribution. We also ?nd that the spectrum predominantly positive reflectivity up to ? 1:6 GeV, after which the spectrum becomes a nearly equal mix of both. The KSKS system shows a rich spectrum with multiple resonance structures but is more statistically limited than the KSKL system. Modelling the line shape we ?find evidence at greater than 10? level in favor of a resonance at ? 1:75 GeV. The model parameters suggest this resonance is the f0(1710). The PWA of the KSKS system was inconclusive. However, using a small set of amplitudes suggests that the spin-2 contribution to the spectrum is primarily in the range 1:2?1:6 GeV, where f2(1270), a2(1320) and f02 (1525) are expected.

Linera, Gabriel Rodriguez↗
DOE OSTI2025

Electronic structure prediction of medium and high entropy alloys across composition space

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries while keeping descriptor-vector size nearly constant as alloy complexity increases. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

materials science↗
DOE OSTI2026

Machine Learning–Augmented Laser-Induced Breakdown Spectroscopy for Spectral Discrimination of Iron Oxalates

Enhanced characterization and phase identification of post-PUREX Pu Oxalates (PuOXA) are pivotal for nonproliferation and pre-detonation nuclear forensics. Despite significant advances in the characterization of PuO 2 samples, little is known about the impact of both the chemical structure and oxidation states of PuOXA (i.e., Pu(III) and Pu(IV)) have on optical emission signatures. Here, we demonstrate the analytical capabilities of laser-induced breakdown spectroscopy (LIBS) applied to Fe(II) and Fe(III) oxalate samples as surrogates for PuOXA, highlighting the discriminating features in the LIBS emission spectra arising from differences in the oxidation states within mixed FeOXA samples. We report the enhancement of spectral feature selection using Principal Component Analysis (PCA), which enables the analytical superiority of machine learning algorithms such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest Regression (RFR) over conventional univariate techniques for phase discrimination and chemometric analysis. Cluster analysis revealed how both matrix effects and laser ablation influence cluster separability by introducing spectral artifacts that misdirect the maximization of variance. PCA-selected emission lines were used in the regression models, demonstrating that both univariate and multivariate linear regression models (i.e., PLSR and SVR) can achieve acceptable performance, with machine learning models outperforming conventional calibration regressions. Furthermore, the application of non-linearly activated PCA-selected emission lines illustrates how simplifying the data while retaining captured variance enables the use of less complex and more computationally efficient models. Furthermore, this is particularly evident in the underperformance of RFR, which suffers from increased computational costs and overfitting owing to its high complexity.

Oxalates↗
DOE OSTI2026

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pyrrole‐Imine Macrocycle: Self‐Organizing Cross‐Reactive Anion Receptor and Sensor

Self-organizing macrocyclic receptor-sensors for phosphorus oxyanions, phosphates, and phosphonates comprising imine moieties were prepared by condensation of dipyrrolylmethane dicarbaldehyde with diethylene triamine. The incorporation of flexible ethylene moieties endows the macrocycle with unprecedented flexibility and ability to accommodate numerous phosphorus oxyanions from orthophosphate to large anions such as ATP or phosphonate glyphosate. The anion binding was elucidated by NMR titrations, low-temperature NMR, and NOESY NMR. The incorporation of dansyl fluorophore enables sensing of anions using the fluorescence signal, whereas the changes in fluorescence intensity, width of the fluorescence band, and position of the maxima are analyte-specific and useful in recognition and identification of eleven different P-oxyanions in water. The affinity (K assoc ) for Na + salts was H 2 PO 4 − ≈ Methylphosphonate > H 2 P 2 O 7 2− > Phenylphosphonate- > Glyphosate 2− > AMP 2− > ADP 2− > ATP 2− . Interestingly, phosphonates, including methylphosphonate and glyphosate anions, were also found to display a strong affinity (K assoc ∼10 6 M −1 ) while halides, nitrate, carbonates, or hydrogen sulfate did not show a significant affinity. The determined fluorescence spectral parameters were used to classify the 12 analytes (11 anions and water) using Linear Discriminant Analysis (LDA). Quantification was performed using LDA and Support Vector Machine (SVM), and the phosphonate concentrations in unknown samples were determined with an error of 3.5% or lower.

anions↗
DOE OSTI2024

Nonequivalent Atomic Vibrations at Interfaces in a Polar Superlattice

In heterostructures made from polar materials, e.g., AlN–GaN–AlN, the nonequivalence of the two interfaces is long recognized as a critical aspect of their electronic properties; in that, they host different 2D carrier gases. Interfaces play an important role in the vibrational properties of materials, where interface states enhance thermal conductivity and can generate unique infrared-optical activity. The nonequivalence of the corresponding interface atomic vibrations, however, is not investigated so far due to a lack of experimental techniques with both high spatial and high spectral resolution. Herein, the nonequivalence of AlN–(Al 0.65 Ga 0.35 )N and (Al 0.65 Ga 0.35 )N–AlN interface vibrations is experimentally demonstrated using monochromated electron energy-loss spectroscopy in the scanning transmission electron microscope (STEM-EELS) and density-functional-theory (DFT) calculations are employed to gain insights in the physical origins of observations. It is demonstrated that STEM-EELS possesses sensitivity to the displacement vector of the vibrational modes as well as the frequency, which is as critical to understanding vibrations as polarization in optical spectroscopies. The combination enables direct mapping of the nonequivalent interface phonons between materials with different phonon polarizations. Furthermore, the results demonstrate the capacity to carefully assess the vibrational properties of complex heterostructures where interface states dominate the functional properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Scalability Analysis of Quantum Models for Stress and Emotion Detection

Stress and emotion detection from high-dimensional physiological signals is a challenging task, particularly when aiming for accurate classification across diverse behavioral states. Quantum machine learning (QML) is promising for modeling such high-dimensional data, but scalability is limited by qubit resources and the exponential cost of classical statevector simulation. This work studies the scalability of quantum support vector machines (QSVMs) for binary stress detection and three-class emotion recognition (Negative/Neutral/Positive) under varying qubit counts and angle-encoding strategies. We also present a comparison study with one-feature-per-qubit (1:1) and two-features-per-qubit (2:1) mappings. Experiments are executed on HPC infrastructure using NVIDIA CUDA-Q to evaluate performance, variance, and class-dependent separability at higher-qubit setups. Results show that larger Hilbert spaces can improve peak accuracy but may increase instability. At the same time, dense 2:1 encoding yields more consistent stress detection performance. For emotion recognition, scaling improves discrimination for classes like Negative and Positive more than Neutral. We find that effective QML scaling is task-dependent and benefits more from encoding design than simply increasing qubit count.

Onim, Md. Saif Hassan [University of Tennessee, Kn↗
DOE OSTI2026

Pressure-Stabilized MnSb2 with Complex Incommensurate Magnetic Order

Marcasite-type compounds have been proposed as promising hosts of exotic magnetic quantum states, yet experimental realizations in stoichiometric, disorder-free systems remain limited. Here, we report the high-pressure stabilization and magnetic characterization of MnSb2, a marcasite-type compound that is thermodynamically metastable under ambient pressure. Single crystals were synthesized using a cubic multianvil press at 3.3 GPa and 490 °C for 24 h, and powder and single-crystal X-ray diffraction confirm the orthorhombic Pnnm structure. These crystals are stable at ambient pressure for a long time up to between 450 and 500 K. Heat-capacity measurements reveal phase transitions at approximately T0 ∼ 118 K and T1 ∼ 220 K. Neutron diffraction uncovers an unconventional magnetic state below T1 ∼ 220 K. Magnetic powder neutron diffraction refinements reveal possible multiple magnetic configurations that provide comparably acceptable fits to the experimental data. While most solutions are consistent with a spin-density-wave (SDW) description, helical models systematically yield inferior agreement factors. Across a broad range of models, the Mn ordered moment reaches a maximum value of approximately 2 μB and remains predominantly collinear, with minimal canting along the c-axis. At 200 K, the magnetic propagation vector is q = (0, 0.3975, 0.3783); upon cooling, the b component increases toward 0.5, reflecting a temperature-dependent evolution of the modulation. The need for modification of the magnetic model between high and low temperatures further highlights the complex and strongly temperature-dependent nature of the magnetic order in this system. These results establish MnSb2 as a pressure-stabilized marcasite magnet with a tunable, complex magnetic state and a compelling stoichiometric platform for exploring unconventional magnetic behavior, including potential altermagnetism.

Xu, Mingyu [Michigan State University , , , ,; Iow↗