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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. Cis SERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated to enhance the usefulness of the software. Cis SERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, Cis SERS utilizes the REBASE enzyme database. Results from Cis SERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. Cis SERS is a java based graphical user interface built around a perl backbone. Several of the applications of Cis SERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool Cis SERSand results from in-silico and corresponding wet-lab analyses demonstrating that Cis SERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Identification of high-dielectric constant compounds from statistical design

Abstract The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries. Here, we report three previously unexplored materials with very high dielectric constants (69 < ϵ < 101) and large band gaps (2.9 < E g (eV) < 5.5) obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks (ANN). Two of these new dielectrics are mixed-anion compounds (Eu 5 SiCl 6 O 4 and HoClO) and are shown to be thermodynamically stable against common semiconductors via phase diagram analysis. We also uncovered four other materials with relatively large dielectric constants (20 < ϵ < 40) and band gaps (2.3 < E g (eV) < 2.7). While the ANN training-data are obtained from the Materials Project, the search-space consists of materials from the Open Quantum Materials Database (OQMD)—demonstrating a successful implementation of cross-database materials design. Overall, we report the dielectric properties of 17 materials calculated using ab initio calculations, that were selected in our design workflow. The dielectric materials with high-dielectric properties predicted in this work open up further experimental research opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2015

Thermodynamic analysis of binary Fe{sub 85}B{sub 15} to quinary Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} alloys for primary crystallizations of α-Fe in nanocrystalline soft magnetic alloys

Fe-based Fe{sub 85}B{sub 15}, Fe{sub 84}B{sub 15}Cu{sub 1}, Fe{sub 82}Si{sub 2}B{sub 15}Cu{sub 1}, Fe{sub 85}Si{sub 2}B{sub 12}Cu{sub 1}, and Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} (NANOMET{sup ®}) alloys were experimental and computational analyzed to clarify the features of NANOMET that exhibits high saturation magnetic flux density (B{sub s}) nearly 1.9 T and low core loss than conventional nanocrystalline soft magnetic alloys. The X-ray diffraction analysis for ribbon specimens produced experimentally by melt spinning from melts revealed that the samples were almost formed into an amorphous single phase. Then, the as-quenched samples were analyzed with differential scanning calorimeter (DSC) experimentally for exothermic enthalpies of the primary and secondary crystallizations (ΔH{sub x1} and ΔH{sub x2}) and their crystallization temperatures (T{sub x1} and T{sub x2}), respectively. The ratio ΔH{sub x1}/ΔH{sub x2} measured by DSC experimentally tended to be extremely high for the Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} alloy, and this tendency was reproduced by the analysis with commercial software, Thermo-Calc, with database for Fe-based alloys, TCFE7 for Gibbs free energy (G) assessments. The calculations exhibit that a volume fraction (V{sub f}) of α-Fe tends to increase from 0.56 for the Fe{sub 85}B{sub 15} to 0.75 for the Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} alloy. The computational analysis of the alloys for G of α-Fe and amorphous phases (G{sub α-Fe} and G{sub amor}) shows that a relationship G{sub α-Fe} ∼ G{sub amor} holds for the Fe{sub 85}Si{sub 2}B{sub 12}Cu{sub 1}, whereas G{sub α-Fe} < G{sub amor} for the Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} alloy at T{sub x1} and that an extremely high V{sub f} = 0.75 was achieved for the Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} alloy by including 2.8 at. % Si and 4.5 at. % P into α-Fe. These computational results indicate that the Fe{sub 85}Si{sub 2}B{sub 8}P{sub 4}Cu{sub 1} alloy barely forms amorphous phase, which, in turn, leads to high V{sub f} and resultant high B{sub s}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Theoretical search for possible Li–Ni–B crystal structures using an adaptive genetic algorithm

The structural diversity of rare-earth and transition metal borides indicates that alkali-transition metal borides (A-T-B) show tremendous promise in exhibiting a variety of crystal structures with different dimensionalities of T-B frameworks. On the other hand, the A-T-B ternary systems are severely underexplored because of the synthetic challenges associated with their preparation. Accurate and efficient computational predictions of low-energy stable and metastable phases can identify the optimal compositions of the hypothetical compounds in the A-T-B systems to guide the synthesis. As such, in this work, we have computationally discovered several new phases in the Li–Ni–B ternary system. The newly discovered LiNiB, Li 2 Ni 3 B, and Li 2 NiB phases expand the existing theoretical database, and the convex-hull surface of Li–Ni–B has been re-constructed. The lowest energy structure of the LiNiB compound has been found by an adaptive genetic algorithm with layered motif, which matches with the experimentally determined structure. According to our electrochemical calculations, LiNiB and another predicted layered Li 2 NiB compounds have great potential as anode materials for lithium batteries. The Li 2 Ni 3 B compound with the space group P4 3 32 was predicted to crystallize in a cubic structure composed of distorted octahedral units of BNi 6 , which is isostructural to two noncentrosymmetric superconductors Li 2 Pd 3 B and Li 2 Pt 3 B. While we were unable to experimentally confirm the Li 2 Ni 3 B compound utilizing the hydride synthetic route, attempts to synthesize this compound by alternate methods remain highly desirable, considering its potential superconducting properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Emerging opportunities for hybrid perovskite solar cells using machine learning

While there are several bottlenecks in hybrid organic–inorganic perovskite (HOIP) solar cell production steps, including composition screening, fabrication, material stability, and device performance, machine learning approaches have begun to tackle each of these issues in recent years. Different algorithms have successfully been adopted to solve the unique problems at each step of HOIP development. Specifically, high-throughput experimentation produces vast amount of training data required to effectively implement machine learning methods. Here, we present an overview of machine learning models, including linear regression, neural networks, deep learning, and statistical forecasting. Experimental examples from the literature, where machine learning is applied to HOIP composition screening, thin film fabrication, thin film characterization, and full device testing, are discussed. These paradigms give insights into the future of HOIP solar cell research. As databases expand and computational power improves, increasingly accurate predictions of the HOIP behavior are becoming possible.

Hering, Abigail R. (ORCID:0000000270806953)↗
DOE OSTI2023

Validation of density pump-out by pedestal-foot magnetic island formation prior to ELM suppression in KSTAR and DIII-D tokamaks

Abstract TM1 nonlinear two-fluid simulations reveal key characteristics of density pump-out caused by pedestal-foot island formation when applying resonant magnetic perturbation (RMP). These characteristics include a bifurcation in pump-out with a low RMP coil current threshold, a sensitivity of pump-out magnitude to q 95 , and the magnitude of pump-out scaling as the square root of the RMP coil current. Dedicated experiments are carried out in the KSTAR and DIII-D tokamaks to validate these features and show that: (1) a staircase bifurcation in density pump-out is observed when slowly ramping up the n = 1 RMP current, and the density fluctuations are found to be slightly decreased from the pedestal-foot to the pedestal-top; (2) the magnitude of density pump-out becomes weaker when decreasing q 95 from 5.5 to 4.9, and a partial recovery of density pump-out is observed when q 95 is ramped down to lower than 4.9; and (3) analysis of a DIII-D database of n = 3 RMP edge-localized mode control experiments finds that the magnitude of density pump-out is proportional to the square root of RMP coil current Δ n e / n e ∝ I RMP 0.5 . These experimental observations are consistent with TM1 simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1997

Proceedings of the Twenty-First NASA Propagation Experiments Meeting (NAPEX XXI) and the Advanced Communications Technology Satellite (ACTS) Propagation Studies Miniworkshop

The NASA Propagation Experimenters (NAPEX) meeting is convened each year to discuss studies supported by the NASA Propagation Program. Representatives from the satellite communications industry, academia and government who have an interest in space-ground radio wave propagation are invited to NAPEX meetings for discussions and exchange of information. The reports delivered at this meeting by program managers and investigators present recent activities and future plans. This forum provides an opportunity for peer discussion of work in progress, timely dissemination of propagation results, and close interaction with the satellite communications industry. NAPEX XXI took place in El Segundo, California on June 11-12, 1997 and consisted of three sessions. Session 1, entitled "ACTS Propagation Study Results & Outcome " covered the results of 20 station-years of Ka-band radio-wave propagation experiments. Session 11, 'Ka-band Propagation Studies and Models,' provided the latest developments in modeling, and analysis of experimental results about radio wave propagation phenomena for design of Ka-band satellite communications systems. Session 111, 'Propagation Research Topics,' covered a diverse range of propagation topics of interest to the space community, including overviews of handbooks and databases on radio wave propagation. The ACTS Propagation Studies miniworkshop was held on June 13, 1997 and consisted of a technical session in the morning and a plenary session in the afternoon. The morning session covered updates on the status of the ACTS Project & Propagation Program, engineering support for ACTS Propagation Terminals, and the Data Center. The plenary session made specific recommendations for the future direction of the program.

Golshan, Nasser↗
NASA NTRSDate not supplied

Characterization of CO 4th Positive Radiation in CO2-Ar Mixtures

This paper presents measurements and simulations of CO 4th Positive spectra obtained in NASA Ames Research Center's Electric Arc Shock Tube (EAST) and CentraleSupelec's Plasma Torch. The experiments were aimed at measuring optically thin emission for the main band features of CO 4th Positive by using test gas mixtures of CO2 and Ar. By using mixtures of CO2 and Ar, the temperature of the flow (and consequently black-body curve) is increased compared to using pure CO2 (or CO2 / N2 mixtures). This temperature increase allows for emission spectroscopy of features that would nominally be black-body limited for conditions relevant to Mars entry. The CO 4th Positive system is the focus of this study as it accounts for a large percentage of the emitted radiation for Martian entry, and also due to the difficulties of obtaining experimental validation data due to the emission appearing in the Vacuum Ultraviolet (VUV) spectral range. The focus of this paper is to provide a comprehensive comparison between the EAST and plasma torch data along with various CO 4th Positive databases available in the literature. Previously reported VUV CO2 / N2 EAST data required a larger temperature than would be predicted based upon equilibrium shock relations. The need for the temperature increase implies that the EAST experiment did not fully equilibrate. Thus, it is presumed that the EAST data did not obtain an equilibrium condition. The plasma torch data, on the other hand, is very consistent with equilibrium assumptions. Thus, the equilibrium data obtained in the plasma torch is utilized to construct the CO 4th Positive emission model, which is then applied to the EAST data with a non-equilibrium interpretation.

A. M. Brandis↗
NASA NTRSDate not supplied

LAVA CFD Analysis of the Check Standard Model within the Langley Unitary Plan Wind Tunnel

This paper is part of an e ort to assess the current capability of Computational Fluid Dynamics (CFD) to accurately predict the experimental forces and base pressure on the Check Standard Model (CSM). The wind tunnel data for this model is gathered during annual monitoring of test-to-test repeatability for the Langley Unitary Plan Wind Tunnel (LUPWT). A blind database designed to help quantify the uncertainty of simulating LUPWT for the CSM repeatability tests was run using the Launch, Ascent and Vehicle Aerodynamics (LAVA) CFD code. The Reynolds-averaged Navier-Stokes equations were used for the predictions presented in the paper. Prior to running the database, best practices were established both for simulating and characterizing the ow of the high-speed legof the LUPWT where the test took place, as well the CSM when inserted within its test section.

ARMD↗
DOE OSTI2019

Numerical and Experimental Analysis of Dissimilar Repair Welding Residual Stress in P91 Steel Considering Solid-State Phase Transformation

Repair welding is a popular method to repair the cracked zones of pipes in power plants. However, residual stresses induced by repair welding are inevitably generated and have a significant effect on the performance of repair-welded components during service. The purpose of this research is to investigate the effects of solid-state phase transformation (SSPT) on the repair welding residual stress distribution of multi-layer and multi-pass welding in P91 steel. Based on thermal elastic-plastic theory, a three-dimensional thermal–metallurgical–mechanical finite element model considering the SSPT is established, and shielded metal arc welding (SMAW) heat input is modelled as one double elliptical heat source. The effect of phase transformation on residual stress is investigated by considering effects with and without phase transformation in the database of materials. The results show that transverse compressive stress and a low longitudinal stress area are generated in the final pass due to martensite transformation. Compared with different zones along the thickness direction, the effect of SSPT is greater around the outer surface than around the internal fusion zone. The rationality of the developed finite element model is verified by the experimental method, and good agreement is obtained between those results from the numerical analysis and experimental methods.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗
DOE OSTI2018

Status Report on the Development of a Thermodynamic Database for Use with Metallic Fuel Design

The scope of this FY18 milestone involves the development of a high fidelity thermodynamic database for the U-Mo-Ti-Zr system to support the accelerated design of new pseudo binary U-xM metallic fuel, where M is a ternary metallic additive composed of Mo, Ti and Zr and x is the additive amount. Based on the previous assessment of the Mo-Ti-Zr ternary system performed in FY17, a complete set of thermodynamic model parameters describing the U-Mo-Ti-Zr quaternary system over the entire composition and temperature range have been developed in this work using the CALPHAD (CALculation of PHAse Diagrams) approach with inputs from both experimental measurements and density functional theory (DFT) total energy calculations. The two ternary intermetallic compounds, the delta phase in the U-Ti-Zr system and the cubic C15 Laves phase in the Mo-Ti-Zr system, are modeled using physically-based two-sublattice compound energy formalism. The liquid, bcc and hcp phases are described using the random solution model. Using the present database, the melting temperatures and bcc onset temperatures of U-xM metallic fuels are predicted as a function of both additive composition and amount. An optimal metallic additive composition has been identified in this work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1996

Performance of the NASA Airborne Radar with the Windshear Database for Forward-Looking Systems

This document describes the simulation approach used to test the performance of the NASA airborne windshear radar. An explanation of the actual radar hardware and processing algorithms provides an understanding of the parameters used in the simulation program. This report also contains a brief overview of the NASA airborne windshear radar experimental flight test results. A description of the radar simulation program shows the capabilities of the program and the techniques used for certification evaluation. Simulation of the NASA radar is comprised of three steps. First, the choice of the ground clutter data must be made. The ground clutter is the return from objects in or nearby an airport facility. The choice of the ground clutter also dictates the aircraft flight path since ground clutter is gathered while in flight. The second step is the choice of the radar parameters and the running of the simulation program which properly combines the ground clutter data with simulated windshear weather data. The simulated windshear weather data is comprised of a number of Terminal Area Simulation System (TASS) model results. The final step is the comparison of the radar simulation results to the known windshear data base. The final evaluation of the radar simulation is based on the ability to detect hazardous windshear with the aircraft at a safe distance while at the same time not displaying false alerts.

Switzer, George F.↗
NASA NTRS2013

The Evaluation of a Test Device for Human Occupant Restraint (THOR) Under Vertical Loading Conditions: Part 1 - Experimental Setup and Results

A series of 16 vertical tests were conducted on a Test Device for Human Occupant Restraint (THOR) - NT 50th percentile Anthropomorphic Test Device (ATD) at NASA Langley Research Center (LaRC). The purpose of the tests conducted at NASA LaRC was threefold. The first was to add vertical response data to the growing test database for THOR-NT development and validation. Second, the THOR-NT analytical computational models currently in development must be validated for the vertical loading environment. The computational models have been calibrated for frontal crash environments with concentration on accurately replicating head/neck, thoracic, and lower extremity responses. Finally, familiarity with the THOR ATD is necessary because NASA is interested in evaluating advanced ATDs for use in future flight and research projects. The THOR was subjected to vertical loading conditions ranging between 5 and 16 g in magnitude and 40 to 120 milliseconds (msec) in duration. It was also tested under conditions identical to previous tests conducted on the Hybrid II and III ATDs to allow comparisons to be made. Variations in the test setup were also introduced, such as the addition of a footrest in an attempt to offload some of the impact load into the legs. A full data set of the THOR-NT ATD will be presented and discussed. Results from the tests show that the THOR was largely insensitive to differences in the loading conditions, perhaps due in part to their small magnitudes. THOR responses, when compared to the Hybrid II and III in the lumbar region, demonstrated that the THOR more closely resembled the straight spine Hybrid setup. In the neck region, the THOR behaved more like the Hybrid III. However in both cases, the responses were not identical, indicating that the THOR would show differences in response than the Hybrid II and III ATDs when subjected to identical impact conditions. The addition of a footrest did not significantly affect the THOR response due to the nature of how the loading conditions were applied.

Littell, Justin D.↗
DOE OSTI2022

Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation

Significant variety is observed in spherical crystal x-ray imager (SCXI) data for the stagnated fuel–liner system created in Magnetized Liner Inertial Fusion (MagLIF) experiments conducted at the Sandia National Laboratories Z-facility. As a result, image analysis tasks involving, e.g., region-of-interest selection (i.e. segmentation), background subtraction and image registration have generally required tedious manual treatment leading to increased risk of irreproducibility, lack of uncertainty quantification and smaller-scale studies using only a fraction of available data. We present a convolutional neural network (CNN)-based pipeline to automate much of the image processing workflow. This tool enabled batch preprocessing of an ensemble of N scans = 139 SCXI images across N exp = 67 different experiments for subsequent study. The pipeline begins by segmenting images into the stagnated fuel and background using a CNN trained on synthetic images generated from a geometric model of a physical three-dimensional plasma. The resulting segmentation allows for a rules-based registration. Our approach flexibly handles rarely occurring artifacts through minimal user input and avoids the need for extensive hand labelling and augmentation of our experimental dataset that would be needed to train an end-to-end pipeline. Here we also fit background pixels using low-degree polynomials, and perform a statistical assessment of the background and noise properties over the entire image database. Our results provide a guide for choices made in statistical inference models using stagnation image data and can be applied in the generation of synthetic datasets with realistic choices of noise statistics and background models used for machine learning tasks in MagLIF data analysis. We anticipate that the method may be readily extended to automate other MagLIF stagnation imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Mechanisms of Plutonium Redox Reactions in Nitric Acid Solutions

Plutonium (Pu) exhibits a complex redox behavior in acidic solutions due to its ability to adapt a wide range of oxidation states typically from +3 to +6 and the tendency for dynamic interconversion between the oxidation states that depends upon electrochemical potential, acid concentration and coordination environments. In particular, the accurate redox speciation of Pu in nitric acid solutions and mapping the interconversion between the various oxidation states mechanistically is challenging due to overlapping chemical and electrochemical reactions leading to significant experimental uncertainties. The last several decades have seen the extensive use of spectroscopic methods to identify and characterize Pu solution species in the various oxidation states. However, dynamic redox mobility of Pu has led to discrepancies among the relevant spectral databases for Pu in nitric acid solutions. This work utilizes a combination of voltammetry and controlled-potential in-situ vis–NIR spectroelectrochemistry to overcome these challenges, and map the interconversion between Pu species in +3, +4, and +6 oxidation states. This allowed elucidation of the mechanisms of the involved redox reactions and an in-depth understanding of the relative stability of the Pu oxidation states through mapping of the Pu redox processes as a function of redox potentials and nitric acid concentrations. The NIR-spectroelectrochemistry studies used to spectroscopically map the redox speciation of Pu as a function of oxidation potentials with varying HNO3 concentrations allows a new perspective into the plutonium redox transformations.

Chatterjee, Sayandev↗