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DOE OSTI2020

Δ$\textit{K}=0 \textit{M}1$ Excitation Strength of the Well-Deformed Nucleus 164 Dy from $\textit{K}$ Mixing

We report the size of a Δ$\textit{K}=0 \textit{M}1$ excitation strength has been determined for the first time in a predominantly axially deformed even-even nucleus. It has been obtained from the observation of a rare $\textit{K}$-mixing situation between two close-lying $J^π = 1^+$ states of the nucleus 164 Dy with components characterized by intrinsic projection quantum numbers $\textit{K}$ = 0 and $\textit{K}$ = 1. Nuclear resonance fluorescence induced by quasimonochromatic linearly polarized γ-ray beams provided evidence for $\textit{K}$ mixing of the 1 + states at 3159.1(3) and 3173.6(3) keV in excitation energy from their γ-decay branching ratios into the ground-state band. The Δ$\textit{K}$ = 0 transition strength of $B(M1; 0^+_1 → 1^+_{K=0}) = 0.008(1)μ^2_N$ was inferred from a mixing analysis of their $\textit{M}$1 transition rates into the ground-state band. It is in agreement with predictions from the quasiparticle phonon nuclear model. This determination represents first experimental information on the $\textit{M}$1 excitation strength of a nuclear quantum state with a negative $\mathcal{R}$-symmetry quantum number.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Quantifying Spin-Mixed States in Ferromagnets

We quantify the presence of spin-mixed states in ferromagnetic 3D transition metals by precise measurement of the orbital moment. While central to phenomena such as Elliot-Yafet scattering, quantification of the spin-mixing parameter has hitherto been confined to theoretical calculations. We demonstrate that this information is also available by experimental means. Comparison of ferromagnetic resonance spectroscopy with x-ray magnetic circular dichroism results show that Kittel’s original derivation of the spectroscopic g factor requires modification, to include spin mixing of valence band states. Our results are supported by ab initio relativistic electronic structure theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Diagnostics of Mixed-State Topological Order and Breakdown of Quantum Memory

Topological quantum memory can protect information against local errors up to finite error thresholds. Such thresholds are usually determined based on the success of decoding algorithms rather than the intrinsic properties of the mixed states describing corrupted memories. Here we provide an intrinsic characterization of the breakdown of topological quantum memory, which both gives a bound on the performance of decoding algorithms and provides examples of topologically distinct mixed states. We employ three information-theoretical quantities that can be regarded as generalizations of the diagnostics of ground-state topological order, and serve as a definition for topological order in error-corrupted mixed states. We consider the topological contribution to entanglement negativity and two other metrics based on quantum relative entropy and coherent information. In the concrete example of the two-dimensional (2D) Toric code with local bit-flip and phase errors, we map three quantities to observables in 2D classical spin models and analytically show they all undergo a transition at the same error threshold. This threshold is an upper bound on that achieved in any decoding algorithm and is indeed saturated by that in the optimal decoding algorithm for the Toric code. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Understanding Mixed Precision GEMM with MPGemmFI: Insights into Fault Resilience

Emerging deep learning workloads urgently need fast general matrix multiplication (GEMM). Thus, one of the critical features of machine-learning-specific accelerators such as NVIDIA Tensor Cores, AMD Matrix Cores, and Google TPUs is the support of mixed-precision enabled GEMM. For DNN models, lower-precision FP data formats and computation offer acceptable correctness but significant performance, area, and memory footprint improvement. While promising, the mixed-precision computation on error resilience remains unexplored. To this end, we develop a fault injection framework that systematically injects fault into the mixed-precision computation results. We investigate how the faults affect the accuracy of machine learning applications. Based on the characteristics of error resilience, we offer lightweight error detection and correction solutions that significantly improve the overall model accuracy by 75% if the models experience hardware faults. The solutions can be efficiently integrated into the accelerator's pipelines.

Fang, Bo↗

DOE OSTI2026

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation recalibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis. Our integrated taxonomy is available in the form of a web application on https://smonadjemi.github.io/miva.

Monadjemi, Shayan [ORNL] (ORCID:0000000293855969)↗

DOE OSTI2021

Validation Metrics for Fixed Effects and Mixed-Effects Calibration

The modern scientific process often involves the development of a predictive computational model. To improve its accuracy, a computational model can be calibrated to a set of experimental data. A variety of validation metrics can be used to quantify this process. Some of these metrics have direct physical interpretations and a history of use, while others, especially those for probabilistic data, are more difficult to interpret. In this work, a variety of validation metrics are used to quantify the accuracy of different calibration methods. Frequentist and Bayesian perspectives are used with both fixed effects and mixed-effects statistical models. Through a quantitative comparison of the resulting distributions, the most accurate calibration method can be selected. Two examples are included which compare the results of various validation metrics for different calibration methods. It is quantitatively shown that, in the presence of significant laboratory biases, a fixed effects calibration is significantly less accurate than a mixed-effects calibration. This is because the mixed-effects statistical model better characterizes the underlying parameter distributions than the fixed effects model. The results suggest that validation metrics can be used to select the most accurate calibration model for a particular empirical model with corresponding experimental data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Mixing in Low Reynolds Number Reacting Impinging Jets in Crossflow

Previous efforts to model uranyl fluoride formation in an impinging jet gas reactor underpredicted spatial mixing and overpredicted chemical conversion into particulates. The previous fluid dynamics model was based on the solution of the Reynolds Averaged Navier Stokes equations. After simulating fluid dynamics, aerosol dynamics were superimposed onto CFD-simulated gas reactant species concentrations. The current work explores the influence of complex unsteady flow features on the overall flow physics and chemistry for a low Reynolds number, opposed flow, impinging jet gas reactor where there is a low Reynolds number cross flow. The objective of this study was to assess the impact of model formulation on scalar mixing and transport. Here, transient flow simulations were performed using Scale Resolving Simulations. Large-Eddy Simulations with the dynamic Smagorinsky turbulence model were performed along with simulations which directly resolved the flow. Average and root-mean-square (RMS) velocities and species concentrations were computed along with modeled and resolved turbulence kinetic energy (TKE), modeled turbulence dissipation, and modeled turbulent viscosity. Lagrangian flow tracers were also used to quantify species concentrations along path lines emanating from the jet tips. Transient simulation data were compared to results from RANS simulations using the k-ω shear stress transport (SST) model and Reynolds Stress Model (RSM). Transient simulations showed spatial mixing patterns which were more consistent with experimental data and helped elucidate the process of particle formation observed in experiments.

42 ENGINEERING↗

DOE OSTI2020

Traffic Prediction for Merging Coordination Control in Mixed Traffic Scenarios

Connected and autonomous vehicles (CAVs) have the potential to bring in safety, mobility, and energy benefits to transportation. The control decisions of CAVs are usually determined for a look-ahead horizon based on previewed traffic information. This requires an effective prediction of future traffic conditions and its integration with the CAV control framework. However, the short-term traffic prediction using information from connectivity is a challenging research topic, especially for mixed traffic scenarios. This work focuses on the development of a traffic prediction framework for a merging coordination controller. The previously developed merging controller coordinates the merging sequence and travel speed of CAVs to maximize the energy efficiency and overall mobility. In mixed traffic scenarios, the controller receives information regarding the position of all the vehicles traveling inside a control zone and controls the desired speed of all CAVs. The controller has no control on the human-driven vehicles. The merging controller does not have direct information or an explicit prediction on the behaviors of human-driven vehicles. Aiming to improve the performance of the merging controller in various mixed traffic conditions, a traffic prediction algorithm is developed and evaluated in this work. The performance of this traffic prediction algorithm is investigated for various penetration rates of connectivity for a single-lane secondary road merging to a single-lane primary road. The results show that compared to a constant speed assumption of human-driven vehicles, the proposed traffic prediction algorithm is able to reduce the prediction error of the arrival time of human-driven vehicles at the merging zone by more than 50%.

Shao, Yunli↗

DOE OSTI2021

Performance-limiting formation dynamics in mixed-halide perovskites

Wide-bandgap (WBG) mixed-halide perovskites as the front cell absorber are accomplishing perovskite-based tandem solar cells with over 29% power conversion efficiency. However, their large voltage deficits limit their ultimate performance. Only a handful of studies probe the fundamental mechanisms underlying the voltage deficits, which remain an unsolved challenge in the field. In this study, we investigate the formation dynamics and defect physics of WBG mixed-halide perovskites in contrast with their corresponding triiodide-based perovskites. Our results show that the inclusion of bromide introduced a halide homogenization process that occurs during the perovskite growth stage from an initial bromide-rich phase toward the final target stoichiometry. We further elucidated a physical model that correlates the role of bromide with the formation dynamics, defect physics, and eventual optoelectronic properties of the film. This work provides a fundamental and unique perspective toward understanding the performance-limiting factors affecting WBG mixed-halide perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Lightwave-electronic harmonic frequency mixing

Electronic frequency mixers are fundamental building blocks of electronic systems. Harmonic frequency mixing in particular enables broadband electromagnetic signal analysis across octaves of spectrum using a single local oscillator. However, conventional harmonic frequency mixers do not operate beyond hundreds of gigahertz to a few terahertz. If extended to the petahertz scale in a compact and scalable form, harmonic mixers would enable field-resolved optical signal analysis spanning octaves of spectra in a monolithic device without the need for frequency conversion using nonlinear crystals. Here, we demonstrate lightwave-electronic harmonic frequency mixing beyond 0.350 PHz using plasmonic nanoantennas. We demonstrate that the mixing process enables complete, field-resolved detection of spectral content far outside that of the local oscillator, greatly extending the range of detectable frequencies compared to conventional heterodyning techniques. Our work has important implications for applications where optical signals of interest exhibit coherent femtosecond-scale dynamics spanning multiple harmonics.

Science & Technology - Other Topics↗

DOE OSTI2020

Editors’ Choice—Review—Recent Advances in Mixed Potential Sensors

Gas sensors are widely used in environmental monitoring and provide controls especially when working with toxic gases. YSZ based λ-sensors have been utilized in the automobile industry for exhaust gas monitoring for more than 40 years. However, recent regulations on emissions reduction has forced further development of toxic gases monitoring in various applications. Mixed potential sensors with YSZ electrolyte are receiving increased attention due to their higher sensitivity and durability under harsh conditions. This review focuses on recent (past 5 years) developments made on electrode and electrolyte structure along with new sensing electrode materials towards detecting gases such as NO x , NH 3 , H 2 , CO and hydrocarbons (HCs). The theory of mixed potential sensors is discussed along with recent developments in detection of multi-gas mixtures using the output from an array of sensors in a mathematical model. Future directions for mixed potential sensor research, and methodologies to improving sensing characteristics are also outlined

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Electrochemical Performance of Mixed Redox-Active Organic Molecules in Redox Flow Batteries

Designing electrolytes based on mixture of different organic redox active molecules brings the opportunity of enhancing the volumetric energy density of flow batteries and removes the requirement of high solubility for individual organic species in the mixture. Here, in the present work, we conduct computational and experimental analysis to investigate the electrochemical performance of mixed redox-active organic molecules. A zero-dimensional transient model is employed to investigate the changes in the half-cell potential and the concentrations and partial currents of individual redox reactions in a mixture of organic molecules over time. The model demonstrates the effects of individual properties of species such as kinetic rate constants, mass transfer coefficients, concentration ratios and standard redox potentials and reports the effect of energy-losing homogenous chemical redox reaction on the voltage efficiency and concentration ratios of the mixed species. Pairs of anthraquinone negolyte species were selected for an experimental case study. A mixture of 2,6-N-TSAQ and 2,6-DHAQ showed 40% increase in the volumetric energy density compared to the performance of 2,6-DHAQ alone. Based on the results of the experimental and computational analysis, we propose guidelines for the design of suitable mixed redox-active organic species.

25 ENERGY STORAGE↗

DOE OSTI2023

High-Performance GMRES Mixed-Precision (HPG-MxP) Benchmark

SAND2024-08539O The High Performance GMRES Mixed-Precision (HPG-MxP) is a benchmark for ranking high-performance supercomputers, allowing use of mixed-precision. Similar to HPCG benchmark, it is designed to profile the computers' capabilities to perform the computational and communication tasks that are commonly found in important classes of real-world applications. At the same time, like HPL-MxP benchmark, it allows the use of mixed-precision arithmetic, while ensuring the double-precision accuracy of the computed solution. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

DOE OSTI2024

Cloud-Resolving ICON Simulations of Secondary Ice Production in Arctic Mixed-Phase Stratocumuli Observed during M-PACE

Field measurements and modeling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations ni. Here, we explore sensitivities with respect to the complexity of different INP parameterizations under the premise that ni is governed by SIP. Idealized, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during the Mixed-Phase Arctic Cloud Experiment (M-PACE) with the Icosahedral Nonhydrostatic (ICON) model. The impact of the droplet shattering (DS) of raindrops and collisional breakup (BR) in addition to the existing Hallet–Mossop rime splintering mechanism were investigated. Overall, 12 different model experiments (12-h runs) were performed and analyzed. Despite the considerable amount of uncertainty remaining with regard to SIP mechanisms and their process representation in numerical models, we conclude from these experiments that (i) only simulations where DS dominates the SIP signal (potentially amplified by BR) capture observed ice-phase and liquid-phase cloud properties, and (ii) SIP events cluster around the convective outflow region and are structurally linked to mesoscale cloud organization. In addition, interactions with primary nucleation parameterizations of varied complexity were investigated. Here, our simulations show that (i) a stable long-lived mixed-phase cloud (MPC) can be maintained in the absence of primary nucleation once SIP is established, (ii) experiments using a computationally more efficient relaxation-based parameterization of primary nucleation are statistically invariant from simulations considering prognostic INP, and (iii) primary nucleation at cloud-top controls the areal extent of the mixed-phase cloud region, and reduces SIP efficacy via DS due to increased depletion of cloud liquid throughout the entire cloud column.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Effects of Testosterone on Mixed-Muscle Protein Synthesis and Proteome Dynamics During Energy Deficit

Effects of testosterone on integrated muscle protein metabolism and muscle mass during energy deficit are undetermined. The objective was to determine the effects of testosterone on mixed-muscle protein synthesis (MPS), proteome-wide fractional synthesis rates (FSR), and skeletal muscle mass during energy deficit. This was a randomized, double-blind, placebo-controlled trial. The study was conducted at Pennington Biomedical Research Center. Fifty healthy men. The study consisted of 14 days of weight maintenance, followed by a 28-day 55% energy deficit with 200 mg testosterone enanthate (TEST, n = 24) or placebo (PLA, n = 26) weekly, and up to 42 days of ad libitum recovery feeding. Mixed-MPS and proteome-wide FSR before (Pre), during (Mid), and after (Post) the energy deficit were determined using heavy water (days 1-42) and muscle biopsies. Muscle mass was determined using the D3-creatine dilution method. Mixed-MPS was lower than Pre at Mid and Post (P < 0.0005), with no difference between TEST and PLA. The proportion of individual proteins with numerically higher FSR in TEST than PLA was significant by 2-tailed binomial test at Post (52/67; P < 0.05), but not Mid (32/67; P > 0.05). Muscle mass was unchanged during energy deficit but was greater in TEST than PLA during recovery (P < 0.05). The high proportion of individual proteins with greater FSR in TEST than PLA at Post suggests exogenous testosterone exerted a delayed but broad stimulatory effect on synthesis rates across the muscle proteome during energy deficit, resulting in muscle mass accretion during subsequent recovery.

Endocrinology & Metabolism↗

DOE OSTI2020

AmeriFlux US-Jo2 Jornada Experimental Range Mixed Shrubland

This is the AmeriFlux version of the carbon flux data for the site US-Jo2 Jornada Experimental Range Mixed Shrubland. Site Description - The study area is in a mixed shrub-dominated portion of the San Andres Mountain piedmont, along the southeastern boundary of the Jornada Experimental Range (JER) in southern New Mexico, USA. The JER was established in 1912 as a response of scientis and landowner to the shrub enchroachment and loss of grasses due to extended grazing during the late 1800s, fire and climate change. JER has been a NSF LTER site since 1981.The study site is a small watershed (4.67 ha) in an alluvial slope or bajada, with three major areas (north-, south- and west-facing hillslopes) with low to moderate slopes (∼0–6°) with a mean slope of 2.6°, while the channel banks and propagating channel heads have higher slopes (∼15–25°). The site is charactetized by a high bare soil coverage (∼66%), ∼28% of mixed shrubs coverage and a low coverage of grass (∼4%) and weeds (∼2%).

Vivoni, Enrique R.↗

DOE OSTI2022

AmeriFlux FLUXNET-1F CA-Cbo Ontario - Mixed Deciduous, Borden Forest Site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-Cbo Ontario - Mixed Deciduous, Borden Forest Site. This is the FLUXNET version of the carbon flux data for the site CA-Cbo Ontario - Mixed Deciduous, Borden Forest Site produced by applying the standard ONEFlux (1F) software. Site Description - Mixed deciduous forest from natural regrowth.

Staebler, Ralf↗

DOE OSTI2020

A Computational-experimental Study to Simulate Mixing and Thermal Stratification in SFRs

This NEUP project 16-10579 entitled “A Computational-Experimental Study to Simulate Mixing and Thermal Stratification in SFRs”, has investigated important phenomena of thermal stratification and mixing in Sodium-cooled Faster reactors (SFRs). A liquid metal experimental set-up was built at Kansas State University to generate high fidelity experimental data and validate computational models. The scope of the work involved - scaled down design of experimental facility, construction and commissioning of the new facility, conducting thermal-hydraulics experiments relevant to the physics of thermal stratification and mixing in the plena, developing 3D CFD models of the experiments, developing SAS4A/SASSYS-1 system model of the liquid metal experimental facility , survey of previous data in literature on stratification experiments and recommendations for improved models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗