22 Search Results

Perovskite manganites are quantum materials exhibiting competing interactions inducing colossal magnetoresistance (CMR). The prevailing theory of CMR highlights the essential role of electron-phonon coupling (EPC), but mounting evidence suggests the underlying mechanism is more complicated. Here, we investigate phonons and spin-phonon coupling in ferromagnetic CMR manganites La1−xSrxMnO3 (x=0.2,0.3) with relatively small CMR associated with melting of the magnetic order above room temperature. High-resolution neutron scattering experiments combined with density functional theory (DFT) show that the low-temperature ferromagnetic phase is conventional: neutron scattering from phonons agrees with DFT predictions and magnons follow sinusoidal dispersions. Fluctuating magnetic moments and low-energy phonons remainmore » conventional in the high-temperature paramagnetic phase, indicating the Mn and La/Sr sublattices are not strongly perturbed by melting of ferromagnetism. In contrast, the Jahn–Teller-active optical oxygen vibrations collapse entirely above the Curie temperature, despite low CMR in these compositions, with some of the lost spectral weight reappearing as quasielastic scattering. We attribute this highly anomalous behavior to giant EPC in the charge and/or orbital channel. It drives cooperative diffusive motion of quasistatic carrier-trapping oxygen sublattice distortions once ferromagnetism disappears. We hypothesize the magnitude of magnetoresistance correlates with the rate of diffusion rather than with the strength of Jahn–Teller EPC.« less

Inelastic neutron scattering (INS) experiments utilizing modern time-of-flight spectrometers enable the comprehensive mapping of the energy (E)- and momentum (Q)-resolved dynamical structure factor of single crystals, probing both the lattice and magnetic excitations. Yet, the large size and complexity of four-dimensional INS data are challenging current analysis workflows, often resulting in an underutilization of the measured information. To help address this issue, this paper introduces new software interfaced with the Mantid framework, pathSQE, designed to streamline the processing, analysis and interpretation of 4D single-crystal INS data. By automating key tasks such as 1D/2D slicing, symmetrization, Brillouin zone folding, data visualization,more » prioritization and filtering, and comparisons with simulations, pathSQE facilitates and accelerates INS data analysis workflows. Here, this paper outlines the features and implementation and provides several illustrations of the use of pathSQE on data collected on single crystals using direct-geometry time-of-flight spectrometers at the Spallation Neutron Source, including Ge, FeSi, MnO and SnS single-crystal measurements on the ARCS, HYSPEC and CNCS neutron spectrometers. Beyond streamlining post-experiment data processing, pathSQE establishes an automated and modular processing pipeline that could support future real-time experiment steering.« less

SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.

Elemental iridium presents surprising challenges for both inelastic neutron scattering (INS) and theoretical thermal transport calculations due to its high neutron absorption cross-section and strong electron-phonon interactions, respectively. Here, in this study, we overcome these challenges to measure temperature-dependent phonon dispersion curves, compare these with calculations based on density functional theory (DFT), and ultimately examine the electron-phonon limited transport behaviors of this material. Our DFT calculations demonstrate Kohn anomalies, near the 𝐾 point of the iridium Brillouin zone, indicating coupling between electrons and phonons. Strong electron-phonon coupling can compete with anharmonic effects to determine electrical and thermal transport behaviors andmore » make the Kohn anomalies challenging to observe. Nonetheless, our INS measurements map these anomalies and other dispersion features over the Brillouin zone from 100 to 700 K. These measurements also uncover unexpectedly large mode specific Grüneisen parameters obtained from the temperature-dependent phonon energies, highlighting strong anharmonicity in iridium. DFT-based Boltzmann transport calculations demonstrate how anharmonicity and electron-phonon couplings determine electronic and lattice transport behaviors. Furthermore, we correlate the Kohn anomalies with calculated electron-phonon nesting functions, Fermi surfaces, and DFT-derived coupling strengths. This study provides detailed insights into the temperature-dependent mode-resolved lattice dynamics and anharmonicity, transport behavior, and electron-phonon interactions.« less

Conventional wisdom dictates that quantum effects become unimportant at high temperatures. In magnets, when the thermal energy exceeds interactions between atomic magnetic moments, the moments are usually uncorrelated, and classical paramagnetic behavior is observed. This thermal decoherence of quantum spin behaviors is a major hindrance to quantum information applications of spin systems. Remarkably, our neutron scattering experiments on Yb chains in an insulating perovskite crystal defy these conventional expectations. We find a sharply defined spectrum of spinons, fractional quantum excitations of spin-1/2 chains, to persist to temperatures much higher than the scale of the interactions between Yb magnetic moments. Themore » observed sharpness of the spinon continuum’s dispersive upper boundary indicates a spinon mean free path exceeding ≈ 35 inter-atomic spacings at temperatures more than an order of magnitude above the interaction energy scale. We thus discover an important and highly unique quantum behavior, which expands the realm of quantumness to high temperatures where entropy-governed classical behaviors were previously believed to dominate. Our results have profound implications for spin systems in quantum information applications operating at finite temperatures and motivate new developments in quantum metrology.« less

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIREDmore » (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.« less

Knowledge about nonequilibrium dynamics in spin systems is of great importance to both fundamental science and technological applications. Inelastic neutron scattering (INS) is an indispensable tool to study spin excitations in complex magnetic materials. However, conventional INS spectrometers currently only perform steady-state measurements and probe averaged properties over many collision events between spin excitations in thermodynamic equilibrium, while the exact picture of re-equilibration of these excitations remains unknown. In this paper, we report on the design and implementation of a time-resolved laser–neutron pump–probe capability at hybrid spectrometer (beamline 14-B) at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory.more » This capability allows us to excite out-of-equilibrium magnons with a nanosecond pulsed laser source and probe the resulting dynamics using INS. Here, we discussed technical aspects to implement such a capability in a neutron beamline, including choices of suitable neutron instrumentation and material systems, laser excitation scheme, experimental configurations, and relevant firmware and software development to allow for time-synchronized pump–probe measurements. We demonstrated that the laser-induced nonequilibrium structure factor is able to be resolved by INS in a quantum magnet. In conclusion, the method developed in this work will provide SNS with advanced capabilities for performing out-of-equilibrium measurements, opening up an entirely new research direction to study out-of-equilibrium phenomena using neutrons.« less

Here, we report inelastic neutron scattering measurements of magnetic excitations in YbMnSb₂, a low-carrier-density Dirac semimetal in which the antiferromagnetic Mn layers are interleaved with Sb layers that host Dirac fermions. We observe a measurable broadening of spin waves, which is consistent with substantial spin-fermion coupling. The spin-wave damping γ in YbMnSb₂ is roughly twice larger compared to that in a sister material, YbMnBi₂, where an indication of a small damping consistent with a theoretical analysis of the spin-fermion coupling was reported. The interplane interaction between the Mn layers in YbMnSb₂ is also much stronger, suggesting that the interaction mechanismmore » is rooted in the same spin-fermion coupling. Our results establish the systematics of spin-fermion interactions in layered magnetic Dirac materials.« less

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressedmore » into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.« less

Here, we developed the Autonomous Neutron Diffraction Explorer (ANDiE) to autonomously perform neutron diffraction measurements to discover the magnetic ordering behavior in a material. Neutron diffraction is one of the few techniques that can directly probe the magnetic ordering of the atoms in a material. As such beamtime at neutron diffraction facilities is in high demand.