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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 OSTI2025

Bayesian inference analysis of jet quenching using inclusive jet and hadron suppression measurements

The JETSCAPE Collaboration reports a new determination of the jet transport parameter $\hat{q}$ in the quark-gluon plasma (QGP) using Bayesian inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). This multi-observable analysis extends the previously published JETSCAPE Bayesian inference determination of $\hat{q}$, which was based solely on a selection of inclusive hadron suppression data. jetscape is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of $\hat{q}$ utilizes active learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data; on jet or hadron data separately; and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Strong coupling from hadronic τ -decay data including τ → π − π 0 ν τ from Belle

In previous work we have combined the π − π 0 , 2 π − π + π 0 , and π − 3 π 0 spectral data obtained from hadronic τ decays measured by the ALEPH and OPAL experiments, together with electroproduction data for several of the subleading hadronic modes and data for the K K ¯ mode to construct an inclusive nonstrange vector spectral function entirely based on experimental data, with no Monte-Carlo generated input. In this paper, we include, for the first time, the Belle τ → π − π 0 ν τ high-statistics decay data to construct a new inclusive nonstrange vector spectral function that combines more of the world’s available data. As no Belle data are at present available for the two 4 π modes, this requires a revised data analysis in comparison with our previous work. From the resulting new spectral function, we obtain a new determination of the strong coupling, α s , using our previously developed strategy based on finite-energy sum rules. We find, at the Z mass scale, α s ( m Z 2 ) = 0.1159 ( 14 ) . We discuss the smaller central value and larger error of our new result compared to our previous result, showing the shifts to be due mainly to significant changes in updated HFLAV results for the π − 3 π 0 decay mode. Published by the American Physical Society 2025

Boito, Diogo (ORCID:0000000244267984)↗
DOE OSTI2025

Intrinsic Defect-Induced Local Semiconducting-to-Metallic Regions Within Monolayer 1T-TiS2 Displayed by First-Principles Calculations and Scanning Tunneling Microscopy

Using density functional theory (DFT) and scanning tunneling microscopy (STM), the intrinsic point defects, formation energy, and electronic structure of 1T-TiS2 were investigated. Defect systems include single-atom vacancies, interstitial and adatom additions, and direct atomic substitution. Using a collective approach for analyzing realistic systems for point defect investigation, we provide a more straightforward comparison to the experimental measurements, reproducing more realistic environmental conditions related to thin film growth. STM images are compared to computationally simulated electron density images to identify specific geometries that result from favorable point defects. DFT suggests that titanium interstitials are the most energetically favorable intrinsic defect, and sulfur vacancies are more likely to form than titanium vacancies within this realistic analysis, which is in agreement with STM data. A pristine, stoichiometric monolayer system is calculated to have a direct band gap of 0.422 eV, which varies based on local point defects. Local semiconducting-to-metallic electronic transitions are predicted to occur based on the presence of Ti interstitials.

Keeney, P. J.↗
DOE OSTI2025

Ab initio investigation of a hypersonic double cone experiment

This article presents a direct molecular simulation (DMS) of a reactive Mach 8.2 oxygen flow over a double cone geometry. The free stream conditions and article configuration generate a flow with thermal and chemical nonequilibrium, which are common attributes of hypersonic flight. This scenario was first studied experimentally at Calspan University of Buffalo Research Center’s test facility. DMS is a particle method that uses quantum mechanically derived interaction potentials to simulate molecular collisions within a flow field. Since these interaction potentials are the only modeling inputs used in the simulation, all flow features can solely be attributed to the ab initio potential energy surfaces. Hence, providing a comparison of a hypersonic ground test and numerical data anchored to quantum mechanics. The fundamental nature of DMS is leveraged to investigate molecular level mechanisms prevalent in the flow, and comparisons with lower fidelity simulations are presented to highlight the role of these first principles calculations as benchmark solutions.

Science & Technology - Other Topics↗
DOE OSTI2024

Designing Particle Morphologies for Materials with Solid Transport Limitations: A Case Study of Lithium and Manganese Rich Cathode Oxides

A lithium and manganese rich nickel-manganese-cobalt oxide (LMR-NMC) cathode is a promising candidate for next-generation batteries due to its high specific capacity, low cost, and low cobalt content. However, the material suffers from poor rate capability due to the diffusion limitations of lithium in the cathode particles. Understanding the material performance requires careful control of the morphology of the cathode particles, taking into account the primary and agglomerated diffusion pathways and the presence of pores, some of which could be closed from electrolyte infiltration. Here, in this study, we use a microstructure-based mathematical model combined with experimental data to understand the role of the complex cathode particle morphology in the rate performance of the material. Scanning electron microscopy images of cathodes made under different synthesis conditions, which results in different agglomerate morphologies, serve as the input into the mathematical model. The model is then compared to rate data to understand the controlling parameters. The presence of intra-agglomerate closed pores results in a large agglomerate diffusion length in comparison to the ideal condition, where the primary particles are agglomerated in an open and dispersed manner such that the entire interfacial area is available for electrochemical reaction. Smaller primary and agglomerate diffusion lengths result in better electrochemical performance. This points us toward designing the morphology of the cathode particles to compensate for the diffusion limitation of LMR-NMC while maximizing the density.

Tewari, Deepti↗
DOE OSTI2025

Bottom-Up Simulation, Reconstruction, and Quantification of Macromolecule Sequences from Experimental Polymerizations

Motivated by the canonical sequence–structure–function paradigm, tools to characterize chemical patterning in natural biomacromolecules, from proteins to nucleic acids, have grown exponentially in recent years. However, analogous strategies for synthetic macromolecules remain in nascent stages, complicated by sequence polydispersity and analytical limitations. To address this, we have developed a comprehensive and open-source Python package, PRISM (polymer rate insights and sequence modeling), an end-to-end workflow that provides a path from experimental kinetics measurements to quantitative and qualitative metrics for describing chemical patterning in stochastic polymers. First, a numerical integration strategy was constructed to simulate and fit experimental data from reversible addition–fragmentation chain transfer (RAFT) polymerization kinetics, enabling the facile estimation of relevant reactivity ratios. These ratios were then used in a mechanism-specific stochastic kinetic simulation strategy to simulate sequence ensembles corresponding to model systems spanning experimental copolymers, classes of statistical polymers (e.g., alternating, block, and gradient), and multiblock copolymers. Lastly, inspired by sequence homology metrics from bioinformatics, we introduce visualization strategies and quantitative metrics to facilitate comparisons of different sequence ensembles. As the sequence–structure–function paradigm becomes increasingly central in de novo design of synthetic macromolecules, this toolkit provides a first step toward accurate and representative sequence description and featurization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Electromagnetic and two-photon transition form factors of the pseudoscalar mesons: An algebraic model computation

We compute electromagnetic and two-photon transition form factors of ground-state pseudoscalar mesons: π , K , η c , η b . To this end, we employ an algebraic model based upon the coupled formalism of Schwinger-Dyson and Bethe-Salpeter equations. Within this approach, the dressed quark propagator and the relevant Bethe-Salpeter amplitude encode the internal structure of the corresponding meson. Electromagnetic properties of the meson are probed via the quark-photon interaction. The algebraic model employed by us unifies the treatment of all ground-state pseudoscalar mesons. Its parameters are carefully fitted performing a global analysis of existing experimental data including the knowledge of the charge radii of the mesons studied. We then compute and predict electromagnetic and two-photon transition form factors for a wide range of probing photon momentum-squared which is of direct relevance to the experimental observations carried out thus far or planned at different hadron physics facilities such as the Thomas Jefferson National Accelerator Facility (JLab) and the forthcoming Electron-Ion Collider. We also present comparisons with other theoretical models and approaches and lattice quantum chromodynamics. Published by the American Physical Society 2024

Higuera-Angulo, I. M. (ORCID:0000000256008875)↗
DOE OSTI2026

Deimos: HALEU TRISO Heated Critical Experiment Data

Deimos was the first critical experiment using high-assay low-enriched uranium (HALEU) TRistructural ISOtropic (TRISO) fuel in over 40 years. HALEU TRISO is the desired fuel form for many of the advanced reactor designs in development; however, very little experimental data are available for this fuel type. Deimos was designed to utilize existing HALEU TRISO fuel in a large graphite moderator to obtain nuclear and reactor physics data to fill the gaps surrounding this fuel type and enrichment. In addition to cold critical data, three separate heated experiments were conducted to measure the temperature reactivity coefficient for this type of system. These measured coefficients were then compared to simulated coefficients to a first level order of fidelity. This comparison showed very good agreement for the experiment where only the inner core was heated and good agreement for the other two configurations, which included heating portions of the outer core. Less agreement when the outer core was heated is attributed to potential heating in the beryllium reflector, which has a positive temperature reactivity coefficient and was unaccounted for in the first-order models. Future heated experiments with Deimos will include temperature monitoring of the beryllium reflector to account for beryllium heating in the simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Toward machine-learning-assisted PW-class high-repetition-rate experiments with solid targets

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)

The Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2) is a natural progression of previous and ongoing model intercomparison exercises that have focused on the simulation of ice-sheet and ocean processes in Antarctica. The previous exercises motivate the move towards realistic configurations, as well as more diverse model parameters and resolutions. The main objective of MISOMIP2 is to investigate the performance of existing ocean and coupled ice-sheet–ocean models in a range of Antarctic environments through comparisons to observational data. We will assess the status of ice-sheet–ocean modelling as a community and identify common characteristics of models that are best able to capture observed features. As models are highly tuned based on present-day data, we will also compare their sensitivity to prescribed abrupt atmospheric perturbations leading to either very warm or slightly warmer ocean conditions compared to the present day. The approach of MISOMIP2 is to welcome contributions of models as they are, including global and regional configurations, but we request standardized variables and common grids for the outputs. We target the analysis at two specific regions, the Amundsen Sea and the Weddell Sea, since they describe two different ocean environments and have been relatively well observed compared to other areas of Antarctica. An observational “MIPkit” synthesizing existing ocean and ice-sheet observations for a common period is provided to evaluate ocean and ice-sheet models in these two regions.

58 GEOSCIENCES↗
DOE OSTI2024

Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons

Abstract. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.

17 WIND ENERGY↗
DOE OSTI2024

Pivotal Roles of Triple Screening-Topological, Electrostatic, and Hydrodynamic-On Dynamics in Semidilute Polyelectrolyte Solutions

For semidilute polyelectrolyte solutions, it is generally assumed that topological, electrostatic, and hydrodynamic interactions are screened (called triple screening). Despite a large body of research focused on polyelectrolyte solutions, the concept of triple screening has never been rigorously verified. In this work, we test the concept by probing concentration fluctuations in aqueous solutions containing a well-studied polyelectrolyte, sodium poly(styrenesulfonate) (NaPSS) with neutron scattering, theory, and molecular dynamics simulations. Neutron spin–echo (NSE) and small-angle neutron scattering (SANS) data from semidilute solutions of NaPSS are presented at different polymer and salt (NaCl) concentrations. A combined theory for structure (J. Chem. Phys. 105, 5183 (1996)) and dynamics (J. Chem. Phys. 107, 2619 (1997)), which captures effects of hydrodynamic, topological, and electrostatic screening, is used to interpret the experimental results. Here, the theory quantitatively predicts the decay rate obtained from the NSE measurements while capturing the shape and concentration dependencies of the polyelectrolyte peak observed in the SANS spectra. Detailed comparisons of the theory and the experiments reveal that the wavevector-dependent decay rate of concentration fluctuations in semidilute solutions of polyelectrolytes is dictated by the screening of hydrodynamic, topological, and electrostatic interactions. This conclusion is corroborated by coarse-grained molecular dynamics simulations, executed without any hydrodynamic interactions, which fail to capture the correct wavevector dependence of the decay rate. These results highlight that the theories based on the concept of triple screening provide a quantitative framework for predicting a relation between the structure and dynamics of polyelectrolyte solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

AWSD reactive flow model for PBX 9404

An Arrhenius–Wescott–Stewart–Davis (AWSD) reactive flow model for high explosive PBX 9404 is developed. We specifically calibrate an AWSD model for PBX 9404 by fitting equations of state for reactants and detonation products to the results of thermochemical calculations and to experimental data from multiple sources. The calibrated equations of state are then coupled with an Arrhenius rate law based on shock temperature that describes the reaction progress during PBX 9404 detonation. The parameter values in the rate law are calibrated to experimental gas-gun data and diameter effect results. The results of the calibrated AWSD model are in strong agreement with available experimental data for PBX 9404. A similar level of agreement between predicted and experimental results is observed when the calibrated model is validated on data that were not used in the model parameterization procedure. Our results illustrate that the AWSD model is capable of accurately describing the many important properties and observables in the reactive burn of PBX 9404. Because of the historical significance of PBX 9404 in high explosives research and its current use in aging studies, this work provides an important model of a legacy material, which can be used to make comparisons to new high explosive formulations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Constitutive model development of aluminum alloy 1100 for elevated temperature forming process

Commercially pure aluminum alloy, AA1100, presents good electrical and thermal conductivity, high formability, and low cost. Those favorable characteristics have the potential to enable bipolar plates with improved economics and enhanced performance compared to current stainless steel bipolar plates for proton exchange membrane fuel cells. An accurate constitutive model is essential to develop and optimize processing parameters and effectively control the forming process. Here, the objective of this work is to develop a constitutive model of AA1100 that is able to simulate stress-strain relation, formed geometry, and predict the onset of fracture strain to avoid forming failure. Initially, a set of tensile tests at temperature between 300 and 500°C and strain rate between 0.005 and 1.0/s were conducted to examine the deformation behavior. Then, a set of damage-based unified visco-plastic constitutive equations is proposed and calibrated based on the results of stress-strain data. A genetic algorithm optimization method is applied to search for best fitting material constants in constitutive equations. The proposed model shows good predictability of both the stress-strain relation and fracture strain at low strain rate and high temperature conditions. The accuracy of proposed model is also evaluated statistically. A comparison of the proposed model with three popular models (Arrhenius-type mode, Johnson-Cook model and Zerilli-Armstrong model) was made. The proposed model shows the best experimental agreement with correlation coefficient of 0.96 in contrast to 0.25, 0.38 and 0.75 for the popular models, respectively. The proposed model can help to optimize the elevated temperature forming process and guide die design to enable optimal geometric features in the formed components.

08 HYDROGEN↗
DOE OSTI2024

Determining the Reaction Kinetics and Thermodynamics of a Diels–Alder Network Using Dynamic Gel Criteria

We undertook a detailed rheological investigation to evaluate the kinetic parameters of the forward and reverse Diels–Alder (DA) reactions of a model network cross-linked using a furan prepolymer and a common aromatic bismaleimide. At high temperature where the Winter–Chambon’s criterion of frequency-independence was more applicable, a multiwave technique permitted van’t Hoff analysis and calculation of the reaction thermodynamic parameters, specifically the enthalpy and entropy of the reaction: ΔH° = –38.3 ± 5.2 kJ mol –1 and ΔS° = –94.3 ± 13.4 J mol –1 . At mild temperatures where the G'–G" crossover point is experimentally convenient to measure gelation, isothermal tests were used to obtain reasonable fDA kinetic parameters from Eyring analysis such as the apparent activation enthalpy and entropy of ΔH$^{‡}_{fDA}$ = 76.8 ± 6.9 kJ mol –1 and ΔS$^{‡}_{fDA}$= –82.8 ± 22.2 J mol –1 K –1 . Comparable rheokinetic methods include cross-linking density measurements and stress relaxation tests to calculate effective kinetics, whereas the critical gel conversion was consistently applied here. As a result, rate data are fitted with the Arrhenius equation for comparison purposes and the Eyring equation to demonstrate its broader utility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Results from the Muon g-2 experiment at Fermilab

The goal of the Muon g-2 experiment at Fermilab is to measure the muon magnetic momentanomaly with a final accuracy of 140 parts per billion (ppb). The experiment has published tworesults based on the data collected in 2018 (Run-1) and 2019-2020 (Run-2/3), respectively. These results confirm the previous measurement performed 20 years ago at Brookhaven National Laboratory, and their combination reaches the unprecedented uncertainty of 200 ppb. This proceeding presents a brief overview of the Standard Model prediction for the muon g-2. It then summarizes the experimental measurement technique and the Run-1 and Run-2/3 measurements, detailing the improvements in their systematic and statistical uncertainties. Finally, it illustrates the comparison between theory and experiment and discusses future prospects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Experimental evidence for nonspherical magnetic form factor in Ru 3 +

The Mott insulator ..alpha..-RuCl3 has generated great interest in the community due to its possible field-induced Kitaev quantum spin liquid state. Despite enormous effort spent trying to obtain the form of the low-energy Hamiltonian, there is currently no agreed upon set of parameters which is able to explain all of the data. A key piece of missing information lies in the determination of the magnetic form factor of Ru3+, particularly for a true quantitative treatment of inelastic neutron scattering data. Here we present the experimentally derived magnetic form factor of Ru3+ in the low spin 4d5 state using polarized neutron diffraction within the paramagnetic regime on high-quality single crystals of ..alpha..-RuCl3. We observe strong evidence of an anisotropic form factor, expected of the spin-orbit coupled jeff=12 ground state. We model the static magnetization density in increasing complexity from simple isotropic cases, to a multipolar expansion, and, finally, ab initio calculations of the generalized jeff=12 ground state. Comparison of both single ion models and inclusion of Cl- anions support the presence of hybridization of Ru3+ with the surrounding Cl- ligands.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗