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Real-Time Mapping of Structural and Magnetic Phase Transitions with Neutron Wavelength-Resolved Laue Diffraction

ORAL

Abstract

The TOPAZ single-crystal diffractometer at the ORNL Spallation Neutron Source (SNS) employs a wavelength-resolved Laue technique, which extends traditional 2D diffraction patterns into a third dimension along the neutron time-of-flight (TOF) axis, producing wavelength-resolved data in 3D Q-space for volumetric mapping of reciprocal space. The broad 3D Q-space coverage, combined with advanced software tools developed at TOPAZ, facilitates the determination of both nuclear and magnetic structures from the same dataset.

Unlike conventional white-beam Laue diffraction, which offers broad coverage but lacks wavelength resolution, neutron TOF Laue diffraction provides precise wavelength information for individual diffraction events. This enables detailed mapping of reciprocal space and enhances the resolution of subtle structural and magnetic features. Additionally, neutron data at SNS is collected in event mode, where each detection is time-stamped [1]. This enables both live analysis and post-processing of data in 4D temporal space, allowing retrospective investigation of phase transitions and order parameters as though measured in real-time.

The combination of wavelength-resolved Laue diffraction, event-mode data, and comprehensive reciprocal space mapping at TOPAZ offers unique insights into the nuclear and magnetic phase transtions of complex materials. We will present studies investigating molecular-level order-to-disorder transformations in hybrid perovskite [2] and hysteretic structural and magnetic phase transitions in α-RuCl3[3]. TOPAZ’s extensive 3D Q-space coverage allows us to track fine changes in magnetic ordering and structural transitions across large volumes of reciprocal space. This capability to analyze data in multidimensional diffraction and parameter spaces is particularly valuable for understanding the evolution of order parameters and phase behavior during transitions. In addition, advanced tools leveraging machine learning have been developed for live data processing and experiment steering [4].

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Publication: [1] Fancher C.M., Hoffmann C., Sedov V.N., Parizzi A., Zhou W., Schultz A.J., Wang X.P., Long D., "Time filtering of event based neutron scattering data: A pathway to study the dynamic structural responses of materials", Review of Scientific Instruments, 89, 9, 092803 (2018).<br>[2] Yang B., Ming W., Du M., Keum J.K., Puretzky A., Rouleau C.M., Huang J., Geohegan D.B., Wang X.P., Xiao K., "Real‐Time Observation of Order‐Disorder Transformation of Organic Cations Induced Phase Transition and Anomalous Photoluminescence in Hybrid Perovskites", Advanced Materials, 30, 22, 1705801 (2018).<br>[3] Mu S., Dixit K.D., Wang X.P., Abernathy D.L., Cao H.B., Nagler S.E., Yan J.Q., Lampen-Kelley P., Mandrus D., Polanco C.A., Liang L., Halasz G.B., Cheng Y.Q., Banerjee A., Berlijn T., "Role of the third dimension in searching for Majorana fermions in α−RuCl3 via phonons", Physical Review Research, 4, 013067 (2022).<br>[4] Yin J., Liu S., Reshniak V., Zhang G., Wang X.P., Xiao Z., Morgan Z., Pawledzio S., Proffen T., Hoffmann C., Cao H., Chakoumakos B. C., Liu Y. "Integrated Edge-to-Exascale Workflow for Real-Time Steering in Neutron Scattering Experiments", Structural Dynamics, Submitted.

Presenters

  • Xiaoping Wang

    Oak Ridge National Laboratory

Authors

  • Xiaoping Wang

    Oak Ridge National Laboratory