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This repository contains the Bruker pulse program for acquire 2D HEAD data in addition to the C++ program used for data processing. Data must be acquired with identical digital resolution in both dimensions. The resulting 2D spectrum is converted to a ASCII file using the Topspin 'totxt' command. This file can be handled by the HEAD_processing program.
ASCII and machine readable data from the publication: High-field magnetic phase diagrams of RMn6Sn6 kagome metals
Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.
Lanthanides (Lns) are important to many technologies including magnets used in high-efficiency traction motors and generators. While commonly occurring in the environment and industrial waste streams, Ln are generally present at low concentrations. This work demonstrates synergistic Ln recovery from an aqueous magnet leachate to single ppm concentrations using Na 2 SO 4 addition and subsequent dimethyl ether-driven fractional crystallization (DME-FC) treatment. It is found that combining DME-FC with low concentrations of Na 2 SO 4 (≈0.1 M) results in synergistic isolation of Lns while making use of Na 2 SO 4 , an excessive byproduct of hydrometallurgical metal production. Combined Na 2 SO 4 + DME reduces Ln metal ion (Pr, Nd, Sm, Gd, Dy, and Ho) solubilities by 700–27,000x with final concentrations ranging from 2 ppm to 200 ppm. Separately, Na 2 SO 4 0.1 M provides a 10–200x reduction and DME provides a 90–1,400x reduction in Ln solubilities. Final Ln concentrations of the combined process are 99.8% lower than what is achieved with each individual process.
Samarium iron nitride (Sm-Fe-N) bonded magnets have emerged as promising candidates for various industrial applications due to their exceptional magnetic properties. Compounds with magnetic material 95 wt fraction (wt.%) (∼74 vol%) and 97 wt.% (∼81 vol%) of SmFeN in a polyamide (PA12) polymer binder are manufactured using a batch mixer followed by compression molding. A maximum energy product ( BH ) max of 186.21 kJ.m -3 (23.4 MGOe) is achieved in the 95 wt.% bonded magnets; 97 wt.% magnets had a ( BH ) max of 165.52 kJ.m -3 (20.8 MGOe). It is found that the degree of alignment (DoA) of 99 % is achieved in the 95 wt.% magnets, whereas the 97 wt.% magnets are limited to a DoA of 90 % respectively. The high DoA can be attributed to low particle-particle interaction during the post-magnetic field alignment process. Finally, this research provides a useful insight of binder-particle interactions at very high magnet weight fractions and their effect on magnetic strength and performance.
A predictive analytical model is presented for the electrical conductivity of multi-principal-element alloys (MPEAs), including those containing aluminum, transition metals, and refractory metals. Given that the lattice parameter of the Wigner-Seitz cell of an MPEA is similarly variable to a bulk metallic glass, it is postulated that electron scattering can be approximated by a series of two-level systems. Here, the resulting reduced-order model enabled an accurate determination of electrical resistivity and electron thermal conductivity based on the scattering of electrons in a two-level system across a Bloch-potential-based virtual crystal approximation. Model results are compared to experimental four-point probe electrical resistivity measurements between 300 K and 700 K for Al 0.3 CoCrCuFeNi, CoCrFeMnNi, (CoCrFeMnNi) 0.98 W 0.02 , (CoCrFeMnNi) 0.95 W 0.05 , and Nb 4 Ta 4 V 3 Ti, for model validation.
Two Al-Ce-Ni cast alloys, and an Al-Cu-Ce cast alloy, as candidate wet storage materials for spent nuclear fuels, were tested in 0.23 wt% H 3 BO 3 solution to assess the alloy corrosion resistance. Electrochemical and gravimetric corrosion data suggest that the three Al alloys are unlikely to undergo any severe corrosion in dilute H 3 BO 3 at or below 50 °C. Post-exposure characterization of the three Al alloys, including scanning and transmission electron microscopy and electron dispersive spectroscopy, revealed a corrosion product layer, mostly Al 2 O 3 , on the exposed surface and local penetration of oxygen into the alloy matrix. The degree of oxide layer growth and oxygen penetration is greater at 80 °C than the temperature at/below 50 °C. The Al-Cu-Ce alloy is considered less corrosion resistant than the other two alloys studied.
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The advection-diffusion equation is simulated via several quantum algorithms. Three formulations are considered: (1) Trotterization, (2) variational quantum time evolution (VarQTE), and (3) adaptive variational quantum dynamics simulation (AVQDS). These schemes were originally developed for the Hamiltonian simulation of many-body quantum systems. The finite-difference discretized operator of the transport equation is formulated as a Hamiltonian and solved without the need for ancillary qubits. Computations are conducted on a quantum simulator (IBM Qiskit Aer) and a superconducting quantum hardware (IBM Fez). The former emulates the latter without the noise. The actual hardware implementation experiences significant noise. The results of the quantum simulator are compared with data from direct numerical simulation (DNS) with infidelities of the order 10 −5 . In the quantum simulator, Trotterization is observed to have the lowest infidelity and is suitable for fault-tolerant computation. The AVQDS algorithm requires the lowest gate count and circuit depth. The VarQTE algorithm is the next best in terms of gate counts, but the number of its optimization variables is directly proportional to the number of qubits. Due to current hardware limitations, Trotterization cannot be implemented, as it has an overwhelmingly large number of operations. Meanwhile, AVQDS and VarQTE can be executed at the hardware level. These algorithms present a new paradigm for computational transport phenomena on quantum computers.
A rare realization of unconventional anomalous Hall effect (UAHE) both below and above the magnetic transition temperature (T C ) in a hexagonal noncentrosymmetric magnet Y 3 Co 8 Sn 4 , using a combined experimental and ab initio calculations. Occurrence of such UAHE is mainly attributed to the reciprocal ($\mathscr{KS}$) topology (i.e., the presence of topological Weyl points at/near the Fermi level), along with some contribution from the topological magnetic texture (at low temperatures), as inferred from the measured field-dependent ac susceptibility. The effect of UAHE on the measured transport behavior however evolves differently with temperature above and below T C = 53 K, suggesting different physical mechanism responsible in the two phases. A unique planar ferrimagnetic ordering is found to be the most stable state with ab-plane as the easy plane below T C . The simulated net magnetization and the moment per Co atom agrees fairly well with the experimentally measured values. A reasonably large anomalous Hall conductivity (AHC) is also observed in both the phases (above and below T C ) of the present compound, which is again not so ubiquitous. In conclusion, the results underscore the family of R 3 Co 8 Sn 4 (R = rare earth) polar magnets as a compelling backdrop for exploring the synergy of magnetism and topological non-trivial electronic states, pivotal for spintronic applications.
Functionalized magnetic nanoparticles are pivotal in magnetic resonance imaging, computed tomography, controlled drug delivery, and hyperthermia treatments due to their exceptional magnetic relaxation and functional properties. The magnetic core composition and structure significantly affects the complex magnetic properties of these nanoparticles necessitating a thorough examination of magnetism fundamentals related to these systems. One important aspect is the ability of magnetic nanoparticles to retain previous magnetic state configurations known as memory effect, primarily governed by domain structure and magnetic anisotropy. Despite its relevance to advanced applications, comprehensive studies on magnetic relaxation and memory effects remain limited. Here, the present review aims to bridge this gap by investigating relaxation mechanisms, synthesis strategies, and applications, fostering further innovation. It investigates the memory effects and their dependence on particle composition and morphology along with key synthesis techniques for large-scale production in industrial adoption. Structured into focused sections on magnetic properties and their influence on biomedical and technological applications, this review provides essential insights into memory effects, magneto-relaxation mechanisms, influencing factors, and both experimental and theoretical methodologies. It also delves into computational modelling and AI-driven design, which are revolutionizing the prediction, discovery, and optimization of materials with tailored properties.
In this work, the density fitting (DF) approximation is added to the restricted Hartree–Fock (RHF) implementation in the JuliaChem computational chemistry code. Utilizing a DF algorithm that uses symmetry and integral screening, a significant reduction in time to compute the Fock matrix is achieved. The symmetry and screening DF-RHF techniques were adapted to be performed on graphics processing units (GPUs), which are well suited to perform the matrix multiplications that comprise the bulk of the Fock build time in DF-RHF. The JuliaChem DF-RHF GPU algorithm employs a novel approach that automatically switches between two DF-RHF algorithms depending on the number of basis functions in the calculation. The JuliaChem GPU DF-RHF implementation demonstrates up to 2× speedup for Fock build times compared to the existing best-in-class GPU DF-RHF implementation by operating directly on screened intermediate matrices. Due to the high portability of the Julia language code, the JuliaChem CPU and GPU DF-RHF implementations could be benchmarked on a variety of CPU and GPU architectures from multiple hardware vendors.
The first conjugated polymers with functional Si–Si crosslinks are reported. In addition to complete structural characterization using solid-state NMR techniques, the electronic structure of the polymers are supported by electrochemical studies.
Using a computational crystal structure search in the Li-Fe-B ternary system, we predict a stable phase of Li 3 Fe 8 B 8 , featuring 1D channels that enable rapid Li-ion transport. Ab initio molecular dynamics simulations show that the Li-ion diffusion coefficient in Li 3 Fe 8 B 8 surpasses that of common electrode and conductive additive materials by several orders of magnitude. The high diffusion in Li 3 Fe 8 B 8 can be explained by the Frenkel–Kontorova model, which describes an incommensurate state between the Li diffusion chain and the periodic potential field caused by the FeB backbone structure. The favorable lithium-ion diffusivity and mechanical properties of Li 3 Fe 8 B 8 make it a promising conductive additive for battery materials. Furthermore, an external magnetic field can further manipulate the properties of this material due to its predicted itinerant ferromagnetism, which also offers a platform for exploring spin-dependent phenomena.
Understanding the origin of unconventional magnetic order is a central theme in the research field of functional quantum materials for spin-dependent applications. In general, a paramagnetic (PM) to antiferromagnetic (AFM) transition is of thermodynamically second order in nature in the absence of a magnetic field. In the magnetically frustrated corrugated-honeycomb lattice compounds (Ca, Sr) Mn 2 P 2 , electrical resistivity 𝜌 measurements in the 𝑎𝑏 plane are reported to exhibit sharp discontinuities at the respective PM to AFM ordering temperatures 𝑇 N = 69.5 and 53 K, respectively, signifying the unusual first-order nature of the AFM transition. To reveal the origin of such anomalous transitions, high-resolution linear thermal-expansion measurements are reported for both CaMn 2 P 2 and SrMn 2 P 2 in the 𝑎𝑏 plane and along the 𝑐 axis using capacitance dilatometry. The thermal expansion measurements show a sharp discontinuity in Δ𝐿/𝐿 at 𝑇 N , yielding a diverging behavior in the thermal expansion coefficient 𝛼(𝑇) associated with strong magnetoelastic coupling, driving the first-order AFM transition in CaMn 2 P 2 . However, this effect is weaker in SrMn 2 P 2 , consistent with the magnetic entropy changes 𝑆(𝑇) obtained from the heat-capacity measurements. Temperature-dependent 𝑎𝑏-plane x-ray diffraction measurements for CaMn 2 P 2 near its 𝑇 N yield a volume thermal expansion coefficient consistent with literature data for other materials. The uniaxial pressure derivatives of 𝑇 N in the two compounds are found to be respectively opposite in sign, presumably due to the different magnetic structures.
The axion is a hypothetical fundamental particle that is conjectured to correspond to the coherent oscillation of the θ field in quantum chromodynamics. Its existence would solve multiple fundamental questions, including the strong CP problem of quantum chromodynamics and dark matter, but the axion has never been detected. Electrodynamics of condensed-matter systems can also give rise to a similar θ, so far studied as a static, quantized value to characterize the topology of materials. Coherent oscillation of θ in condensed matter has been proposed to lead to physics directly analogous to the high-energy axion particle—the dynamical axion quasiparticle (DAQ). Here we report the observation of the DAQ in MnBi 2 Te 4 . By combining a two-dimensional electronic device with ultrafast pump–probe optics, we observe a coherent oscillation of θ at about 44 gigahertz, which is uniquely induced by its out-of-phase antiferromagnetic magnon. This represents direct evidence for the presence of the DAQ, which in two-dimensional MnBi 2 Te 4 is found to arise from the magnon-induced coherent modulation of the Berry curvature. The DAQ also has implications in light–matter interaction and coherent antiferromagnetic spintronics, as it might lead to axion polaritons and electric control of ultrafast spin polarization. Finally, the DAQ could be used to detect axion particles. We estimate the detection frequency range and sensitivity in the millielectronvolt regime, which has so far been poorly explored.
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Mesoporous silicon nitride (Si 3 N 4 ) enables access to chemisorbed group IV organometallics catalysts active for propane dehydrogenation (PDH) compared to the organometallic analogues on mesoporous silica under the same reaction conditions. The series of Si 3 N 4 -supported materials are active catalysts, (Zr > Hf > Ti k f = 290, 232, and 162 mol mol Metal -1 h -1 at 450 °C with 2% C 3 H 8 in Ar, respectively) with selectivity above 95%, demonstrating additional examples of Ti and Hf systems for PDH. However, the underlying mechanism of the improved performance relative to oxide supported homologues is not well-understood. Characterization of thermally treated samples (DRIFTS, XAS and SSNMR) and computational modeling of this catalyst series was utilized to differentiate between potential amido - (C-H activation along the M-N bond) and imido - (C-H activation along the M=N bond) mechanisms. Due to remaining mechanistic ambiguity, a Ga analogue was synthesized and evaluated for PDH activity as an indirect probe to experimentally differentiate pathways. An inversion of the oxide/nitride performance trend is observed for the Ga congener which does not form a Ga=N bond, most consistent with different mechanisms dictating the performance of the group IV/Si 3 N 4 catalysts vs Ga/Si 3 N 4 .