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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Chemical abundances of the Typhon stellar stream

ABSTRACT We present the first high-resolution chemical abundances of seven stars in the recently discovered high-energy stream Typhon. Typhon stars have apocentres r ≳ 100 kpc, making this the first detailed chemical picture of the Milky Way’s very distant stellar halo. Though the sample size is limited, we find that Typhon’s chemical abundances are more like a dwarf galaxy than a globular cluster, showing a metallicity dispersion and no presence of multiple stellar populations. Typhon stars display enhanced α-element abundances and increasing r-process abundances with increasing metallicity. The high-α abundances suggest a short star formation duration for Typhon, but this is at odds with expectations for the distant Milky Way halo and the presence of delayed r-process enrichment. If the progenitor of Typhon is indeed a new dwarf galaxy, possible scenarios explaining this apparent contradiction include a dynamical interaction that increases Typhon’s orbital energy, a burst of enhanced late-time star formation that raises [α/Fe], and/or group pre-processing by another dwarf galaxy before infall into the Milky Way. Alternatively, Typhon could be the high-energy tail of a more massive disrupted dwarf galaxy that lost energy through dynamical friction. We cannot clearly identify a known low-energy progenitor of Typhon in the Milky Way, but 70 per cent of high-apocentre stars in cosmological simulations are from high-energy tails of large dwarf galaxies. Typhon’s surprising combination of kinematics and chemistry thus underscores the need to fully characterize the dynamical history and detailed abundances of known substructures before identifying the origin of new substructures.

Astronomy & Astrophysics↗
DOE OSTI2022

Molecular interactions in diffusion-controlled aldol condensation with mesoporous silica nanoparticles

The aldol reaction of p-nitrobenzaldehyde in amino-catalyzed mesoporous silica nanoparticles (MSN) has revealed varying catalytic activity with the size of the pores of MSN. The pore size dependence related to the reactivity indicates that the diffusion process is important. A detailed molecular-level analysis for understanding diffusion requires assessment of the noncovalent interactions of the molecular species involved in the aldol reaction with each other, with the solvent, and with key functional groups on the pore surface. Such an analysis is presented here based upon the effective fragment potential (EFP). The EFP method can calculate the intermolecular interactions, decomposed into Coulomb, polarization, dispersion, exchange-repulsion, and charge-transfer interactions. In this study, the potential energy surfaces corresponding to each intermolecular interaction are analyzed for homo- and hetero-dimers with various configurations. The monomers that compose dimers are five molecules such as p-nitrobenzaldehyde, acetone, n-hexane, propylamine, and silanol. The results illustrate that the dispersion interaction is crucial in most dimers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probing shocks interacting with radiation waves with the Radishock experiment

Both radiation flows and shocks have been extensively studied in the laboratory in the past few decades due to their critical roles in many astrophysical and high-energy density physics processes. In the Radishock experiment, a halfraum-powered radiation wave is driven into a low-density foam and interacts with an ablatively driven, counter-propagating shock. The interacting waves produce a spike in energy density with a temperature greater than the local temperature of the individual waves. As in the successful predecessor experiment, COAX, the primary diagnostic uses absorption spectroscopy at many locations down the cylindrical target, enabling a spatial temperature inference of the radiation wave and its interactions with the shock. Combined with a radiography diagnostic that is capable of imaging the shock and interaction features, we are able to study and inform model predictions of the interaction spike phenomenon. We describe the underlying physics behind the shock interactions with the radiation front and the implications of this experimental study for a broad range of astrophysical phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Fluorescence-mediated postcollision interaction in x-ray photoionization of the Xe 𝐾 edge

Postcollision interaction (PCI) in near-threshold photoionization of the K shell of atomic Xe is investigated with hard-x-ray synchrotron radiation. Applying Auger electron spectroscopy, line-shape distortion is monitored in the K-L 2 → L 2 M 4,5 M 4,5 decay channel, where the initial K-L 2 (Kα 2 ) x-ray-emission step mediates the emission of the two continuum electrons. The K-edge result is compared to similar data obtained on direct L 2 M 4,5 M 4,5 decay at the L 2 edge without x-ray-emission. In conclusion, it is found that the evolution of the PCI shift with excess photon energy is very similar at both edges, but a subtle decrease in the PCI shift is observable at the K edge due to the effect of the ultrafast x-ray emission step delaying the PCI energy exchange by a few attoseconds.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Interactions between atmospheric pressure plasmas and metallic catalyst particles in packed bed reactors

Atmospheric-pressure plasmas sustained in packed bed reactors (PBRs) are being investigated for chemical conversion of gases and pollution control. Metallic catalysts added to the surfaces of the dielectric beads of PBRs can increase the energy efficiency and selectivity of chemical processes by reducing operating temperature and providing additional reaction pathways. In this paper, results from a computational investigation of plasma surface interactions between micron-scale metallic catalysts and humid-air plasmas in PBRs are discussed. Here we found that high plasma density regions form in the proximity of the metallic catalysts. These higher-density plasma regions were confirmed experimentally using ICCD imaging. The intense plasmas result from geometrical electric field enhancement and redistribution of charges within the conductive particles, leading to further enhancement. The high electric field at the triple points of the catalysts can produce electric field emission of electrons, which provides a pre-ionization source or additional source of electrons. These regions of high electric field and sources of electrons guide discharges towards the catalysts and increases fluxes of excited species, ions, electrons and photons to their surfaces. These fluxes are focused primarily at the triple points between the metal, dielectric and gas. As a result, the catalyst is locally heated, which could lead to further increased rates of thermocatalytic reactions on the surface. Surface roughness of the metal inclusions can lead to additional electric field enhancement, which changes the character of the discharges in the vicinity of the catalysts while reducing breakdown voltage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Beyond integration: modeling every pixel to obtain better structure factors from stills

Most crystallographic data processing methods use pixel integration. In serial femtosecond crystallography (SFX), the intricate interaction between the reciprocal lattice point and the Ewald sphere is integrated out by averaging symmetrically equivalent observations recorded across a large number (10 4 -10 6 ) of exposures. Although sufficient for generating biological insights, this approach converges slowly, and using it to accurately measure anomalous differences has proved difficult. This report presents a novel approach for increasing the accuracy of structure factors obtained from SFX data. A physical model describing all observed pixels is defined to a degree of complexity such that it can decouple the various contributions to the pixel intensities. Model dependencies include lattice orientation, unit-cell dimensions, mosaic structure, incident photon spectra and structure factor amplitudes. Maximum likelihood estimation is used to optimize all model parameters. The application of prior knowledge that structure factor amplitudes are positive quantities is included in the form of a reparameterization. The method is tested using a synthesized SFX dataset of ytterbium(III) lysozyme, where each X-ray laser pulse energy is centered at 9034 eV. This energy is 100 eV above the Yb 3+ L -III absorption edge, so the anomalous difference signal is stable at 10 electrons despite the inherent energy jitter of each femtosecond X-ray laser pulse. This work demonstrates that this approach allows the determination of anomalous structure factors with very high accuracy while requiring an order-of-magnitude fewer shots than conventional integration-based methods would require to achieve similar results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ion‐Specific Interactions Engender Dynamic and Tailorable Properties in Biomimetic Cationic Polyelectrolytes

Abstract Biomaterials such as spider silk and mussel byssi are fabricated by the dynamic manipulation of intra‐ and intermolecular biopolymer interactions. Organisms modulate solution parameters, such as pH and ion co‐solute concentration, to effect these processes. These biofabrication schemes provide a conceptual framework to develop new dynamic and responsive abiotic soft material systems. Towards these ends, the chemical diversity of readily available ionic compounds offers a broad palette to manipulate the physicochemical properties of polyelectrolytes via ion‐specific interactions. In this study, we show for the first time that the ion‐specific interactions of biomimetic polyelectrolytes engenders a variety of phase separation behaviors, creating dynamic thermal‐ and ion‐responsive soft matter that exhibits a spectrum of physical properties, spanning viscous fluids to viscoelastic and viscoplastic solids. These ion‐dependent characteristics are further rendered general by the merger of lysine and phenylalanine into a single, amphiphilic vinyl monomer. The unprecedented breadth, precision, and dynamicity in the reported ion‐dependent phase behaviors thus introduce a broad array of opportunities for the future development of responsive soft matter; properties that are poised to drive developments in critical areas such as chemical sensing, soft robotics, and additive manufacturing.

Aubrecht, Filip J.↗
DOE OSTI2020

Constraint on the matter–antimatter symmetry-violating phase in neutrino oscillations

The charge-conjugation and parity-reversal (CP) symmetry of fundamental particles is a symmetry between matter and antimatter. Violation of this CP symmetry was first observed in 1964, and CP violation in the weak interactions of quarks was soon established. Sakharov proposed that CP violation is necessary to explain the observed imbalance of matter and antimatter abundance in the Universe. Yet, CP violation in quarks is too small to support this explanation. So far, CP violation has not been observed in non-quark elementary particle systems. It has been shown that CP violation in leptons could generate the matter–antimatter disparity through a process called leptogenesis. Leptonic mixing, which appears in the standard model’s charged current interactions, provides a potential source of CP violation through a complex phase δ CP , which is required by some theoretical models of leptogenesis. This CP violation can be measured in muon neutrino to electron neutrino oscillations and the corresponding antineutrino oscillations, which are experimentally accessible using accelerator-produced beams as established by the Tokai-to-Kamioka (T2K) and NOvA experiments. Until now, the value of δ CP has not been substantially constrained by neutrino oscillation experiments. Here we report a measurement using long-baseline neutrino and antineutrino oscillations observed by the T2K experiment that shows a large increase in the neutrino oscillation probability, excluding values of δ CP that result in a large increase in the observed antineutrino oscillation probability at three standard deviations (3σ). The 3σ confidence interval for δ CP , which is cyclic and repeats every 2π, is [-3.41, -0.03] for the so-called normal mass ordering and [-2.54, -0.32] for the inverted mass ordering. Our findings indicate CP violation in leptons and our method enables sensitive searches for matter–antimatter asymmetry in neutrino oscillations using accelerator-produced neutrino beams. Future measurements with larger datasets will test whether leptonic CP violation is larger than the CP violation in quarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Long-term leaf C:N ratio change under elevated CO 2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO 2 (eCO 2 ) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon-nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO 2 and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO 2 and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO 2 and ΔMAT rather than ΔMAP and ecosystem types. In this work, process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO 2 led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using CESM-RESFire to understand climate–fire–ecosystem interactions and the implications for decadal climate variability

Large wildfires exert strong disturbance on regional and global climate systems and ecosystems by perturbing radiative forcing as well as the carbon and water balance between the atmosphere and land surface, while short- and long-term variations in fire weather, terrestrial ecosystems, and human activity modulate fire intensity and reshape fire regimes. The complex climate–fire–ecosystem interactions were not fully integrated in previous climate model studies, and the resulting effects on the projections of future climate change are not well understood. Here we use the fully interactive REgion-Specific ecosystem feedback Fire model (RESFire) that was developed in the Community Earth System Model (CESM) to investigate these interactions and their impacts on climate systems and fire activity. We designed two sets of decadal simulations using CESM-RESFire for present-day (2001–2010) and future (2051–2060) scenarios, respectively, and conducted a series of sensitivity experiments to assess the effects of individual feedback pathways among climate, fire, and ecosystems. Our implementation of RESFire, which includes online land–atmosphere coupling of fire emissions and fire-induced land cover change (LCC), reproduces the observed aerosol optical depth (AOD) from space-based Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products and ground-based AErosol RObotic NETwork (AERONET) data; it agrees well with carbon budget benchmarks from previous studies. We estimate the global averaged net radiative effect of both fire aerosols and fire-induced LCC at –0.59±0.52 W m –2 , which is dominated by fire aerosol–cloud interactions (–0.82±0.19 W m –2 ), in the present-day scenario under climatological conditions of the 2000s. The fire-related net cooling effect increases by ~170 % to –1.60±0.27 W m –2 in the 2050s under the conditions of the Representative Concentration Pathway 4.5 (RCP4.5) scenario. Such considerably enhanced radiative effect is attributed to the largely increased global burned area (+19 %) and fire carbon emissions (+100 %) from the 2000s to the 2050s driven by climate change. The net ecosystem exchange (NEE) of carbon between the land and atmosphere components in the simulations increases by 33 % accordingly, implying that biomass burning is an increasing carbon source at short-term timescales in the future. High-latitude regions with prevalent peatlands would be more vulnerable to increased fire threats due to climate change, and the increase in fire aerosols could counter the projected decrease in anthropogenic aerosols due to air pollution control policies in many regions. We also evaluate two distinct feedback mechanisms that are associated with fire aerosols and fire-induced LCC, respectively. On a global scale, the first mechanism imposes positive feedbacks to fire activity through enhanced droughts with suppressed precipitation by fire aerosol–cloud interactions, while the second one manifests as negative feedbacks due to reduced fuel loads by fire consumption and post-fire tree mortality and recovery processes. These two feedback pathways with opposite effects compete at regional to global scales and increase the complexity of climate–fire–ecosystem interactions and their climatic impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhanced resistance to helium irradiations through unusual interaction between high-entropy-alloy and helium

Finding high performance plasma-facing materials (PFMs) is one of the most important and challenging tasks for realizing the commercial application of fusion reactors. Herein, we found the CrMoTaWV high entropy alloy (HEA) is highly resistant to low-energy and high-flux He plasma exposure. The nanochannel HEA film has 20 times higher initial fluence for the formation of fuzz and a remarkable 8.9 times slower fuzz growth rate than those of W. Combining the in-situ TEM observation and the Molecular dynamics (MD) simulation of the He bubble growth process, a new mechanism for the enhanced radiation resistance in HEA with the unusual interaction between HEA and He is found, where, differing from traditional metal, bubble growth in HEA leads to non-directional emission of interstitial atoms while HEA greatly suppress the growth of He bubbles. Additionally, the special nanochannel structure further rise the radiation resistance through releasing He out of the HEA film and reducing the He concentration. This new nanochannel refractory HEA material presents a promising choice as the PFMs with excellent performance and a much longer serving lifetime for future commercial fusion reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dative Epitaxy of Commensurate Monocrystalline Covalent van der Waals Moiré Supercrystal

Realizing van der Waals (vdW) epitaxy in the 1980s represents a breakthrough that circumvents the stringent lattice matching and processing compatibility requirements in conventional covalent heteroepitaxy. However, due to the weak vdW interactions, there is little control over film qualities by the substrate. Typically, discrete domains with a spread of misorientation angles are formed, limiting the applicability of vdW epitaxy. In this study, the epitaxial growth of monocrystalline, covalent Cr 5 Te 8 2D crystals on monolayer vdW WSe 2 by chemical vapor deposition is reported, driven by interfacial dative bond formation. The lattice of Cr 5 Te 8 , with a lateral dimension of a few tens of micrometers, is fully commensurate with that of WSe 2 via 3 × 3 (Cr 5 Te 8 )/7 × 7 (WSe 2 ) supercell matching, forming a single-crystalline moiré superlattice. This work establishes a conceptually distinct paradigm of thin-film epitaxy, termed “dative epitaxy”, which takes full advantage of covalent epitaxy with chemical bonding for fixing the atomic registry and crystal orientation, while circumventing its stringent lattice matching and processing compatibility requirements; conversely, it ensures the full flexibility of vdW epitaxy, while avoiding its poor orientation control. Cr 5 Te 8 2D crystals grown by dative epitaxy exhibit square magnetic hysteresis, suggesting minimized interfacial defects that can serve as pinning sites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Strong-field physics in three-dimensional topological insulators

We investigate theoretically the strong-field regime of light-matter interactions in the topological-insulator class of quantum materials. In particular, we focus on the process of nonperturbative high-order harmonic generation from the paradigmatic three-dimensional topological insulator bismuth selenide (Bi 2 Se 3 ) subjected to intense midinfrared laser fields. We analyze the contributions from the spin-orbit-coupled bulk states and the topological surface bands separately and reveal a major difference in how their harmonic yields depend on the ellipticity of the laser field. Furthermore, bulk harmonics show a monotonic decrease in their yield as the ellipticity increases, in a manner reminiscent of high harmonic generation in gaseous media. However, the surface contribution exhibits a highly nontrivial dependence, culminating with a maximum for circularly polarized fields. We attribute the observed anomalous behavior to (i) the enhanced amplitude and the circular pattern of the interband dipole and the Berry connections in the vicinity of the Dirac point and (ii) the influence of the higher-order, hexagonal warping terms in the Hamiltonian, which are responsible for the hexagonal deformation of the energy surface at higher momenta. The latter are associated directly with spin-orbit-coupling parameters. Our results thus establish the sensitivity of strong-field-driven high harmonic emission to the topology of the band structure as well as to the manifestations of spin-orbit interaction.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Enabling scientific machine learning in MOOSE using Libtorch

A neural-network-based machine learning interface has been developed for the Multiphysics Object-Oriented Simulation Environment (MOOSE). The interface relies on Libtorch, the C++ front-end of PyTorch, and enables an online interaction between modern machine learning algorithms and all the existing simulation, modeling, and analysis processes available in MOOSE. New capabilities in MOOSE include the native generation and training of artificial neural networks together with options to load pretrained neural networks in TorchScript format. Furthermore, the MOOSE stochastic tools module (MOOSE-STM) has been enhanced with neural network-based surrogate and reduced-order model generation options for efficient stochastic analyses. Lastly, a reinforcement learning capability has been added to MOOSE-STM for the interactive control and optimization of complex multiphysics problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Non-Loudon-Fleury Raman scattering in spin-orbit coupled Mott insulators

In this work we revisit the theory of magnetic Raman scattering in Mott insulators with strong spin-orbit coupling, with a major focus on Kitaev materials. We show that Kitaev materials with bond-anisotropic interactions are generally expected to show both one- and two-magnon responses. It is further shown that, in order to obtain the correct leading contributions to the Raman vertex operator R, one must take into account the precise, photon-assisted microscopic hopping processes of the electrons and that, in systems with multiple hopping paths, R contains terms beyond those appearing in the traditional Loudon-Fleury theory. Most saliently, a numerical implementation of the revised formalism to the case of the three-dimensional hyperhoneycomb Kitaev material β– Li 2 Ir O 3 reveals that the non-Loudon-Fleury scattering terms actually dominate the Raman intensity. In addition, they induce a qualitative modification of the polarization dependence, including, e.g., the emergence of a sharp one-magnon peak at low energies, which is not expected in the traditional Loudon-Fleury theory. This peak is shown to arise from microscopic photon-assisted tunneling processes that are of similar type with the ones leading to the symmetric off-diagonal interaction Γ (known to be present in many Kitaev materials), but take the form of a bond-directional magnetic dipole term in the Raman vertex. These results are expected to apply across all Kitaev materials and mark a drastic change of paradigm for the understanding of Raman scattering in materials with strong spin-orbit coupling and multiple exchange paths.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗