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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Stabilizing a strongly nonlinear structure through shaker dynamics in fixed frequency voltage control tests

Bifurcations are commonly encountered during force controlled swept and stepped sine testing of nonlinear structures, which generally leads to the so-called jump-down or jump-up phenomena between stable solutions. There are various experimental closed-loop control algorithms, such as control-based continuation and phase-locked loop, to stabilize dynamical systems through these bifurcations, but they generally rely on specialized control algorithms that are not readily available with many commercial data acquisition software packages. A recent method was developed to experimentally apply sequential continuation using the shaker voltage that can be readily deployed using commercially available software. By utilizing the stabilizing effects of electrodynamic shakers and the force dropout phenomena in fixed frequency voltage control sine tests, this approach has been demonstrated to stabilize the unstable branch of a nonlinear system with three branches, allowing for three multivalued solutions to be identified within a specific frequency bandwidth near resonance. Recent testing on a strongly nonlinear system with vibro-impact nonlinearity has revealed jumping behavior when performing sequential continuation along the voltage parameter, like the jump phenomena seen during more traditional force controlled swept and stepped sine testing. Here, this paper investigates the stabilizing effects of an electrodynamic shaker on strongly nonlinear structures in fixed frequency voltage control tests using both numerical and experimental methods. The harmonic balance method is applied to the coupled shaker-structure system with an electromechanical model to simulate the fixed voltage control tests and predict the stabilization for different parameters of the model. The simulated results are leveraged to inform the design of a set of experiments to demonstrate the stabilization characteristics on a fixture-pylon assembly with a vibro-impact nonlinearity. Through numerical simulation and experimental testing on two different strongly nonlinear systems, the various parameters that influence the stability of the coupled shaker-structure are revealed to better understand the performance of fixed frequency voltage control tests.

42 ENGINEERING↗
DOE OSTI2022

Reynolds number dependence of Lagrangian dispersion in direct numerical simulations of anisotropic magnetohydrodynamic turbulence

Large-scale magnetic fields thread through the electrically conducting matter of the interplanetary and interstellar medium, stellar interiors and other astrophysical plasmas, producing anisotropic flows with regions of high-Reynolds-number turbulence. It is common to encounter turbulent flows structured by a magnetic field with a strength approximately equal to the root-mean-square magnetic fluctuations. In this work, direct numerical simulations of anisotropic magnetohydrodynamic (MHD) turbulence influenced by such a magnetic field are conducted for a series of cases that have identical resolution, and increasing grid sizes up to $2048^3$ . The result is a series of closely comparable simulations at Reynolds numbers ranging from 1400 up to 21 000. We investigate the influence of the Reynolds number from the Lagrangian viewpoint by tracking fluid particles and calculating single-particle and two-particle statistics. The influence of Alfvénic fluctuations and the fundamental anisotropy on the MHD turbulence in these statistics is discussed. Single-particle diffusion curves exhibit mildly superdiffusive behaviours that differ in the direction aligned with the magnetic field and the direction perpendicular to it. Competing alignment processes affect the dispersion of particle pairs, in particular at the beginning of the inertial subrange of time scales. Scalings for relative dispersion, which become clearer in the inertial subrange for a larger Reynolds number, can be observed that are steeper than indicated by the Richardson prediction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Destabilization of binary mixing layer in supercritical conditions

Compressible mixing layer instabilities are of importance to a wide range of environmental and industrial applications. Past studies have focused on either ideal-gas or real-fluid thermodynamic regimes of single-species mixing layers. However, mixing layers of binary mixtures at supercritical conditions, commonly encountered in fuel injection systems, introduce additional complexities due to the added compositional degree-of-freedom. Moreover, the effect of strong variations in thermodynamic response functions across the Widom line on the binary mixing layer stability remains poorly understood. Thus, the objective of this study is to examine the coupling between the hydrodynamic instability and the real-fluid thermodynamics across the Widom line and its effects on the overall binary mixing layer dynamics. To this end, we develop a linear stability analysis of the full binary-species compressible transport equations coupled with the PC-SAFT equation of state. Analysis shows the existence of a novel instability mechanism that arises from juxtapositioning of the Widom-line transition and the hydrodynamic inflection point. This novel thermodynamically induced instability mechanism has the net effect of destabilizing the binary mixing layer at lowering supercritical conditions towards the critical pressure point. This is in contrast to previous stability analyses of supercritical single-species mixing layers, where increasing pressure destabilizes the flow due to its effect on reducing the density stratification. The discovered thermodynamically induced instability mechanism of binary mixing flows highlights the need for an extension of classical instability criteria to incorporate the effect of strong variations in the thermodynamic response functions across the Widom line on mixing layer instability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Optimising the processing and storage of visibilities using lossy compression

The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, largely through increasing the number of stations in the array and the frequency span sampled. The two primary problems encountered when processing the resultant avalanche of data are the need for abundant storage and the constraints imposed by I/O, as I/O bandwidths drop significantly on cold storage. An example of this is the data deluge expected from the SKA Telescopes of more than 60 PB per day, all to be stored on the buffer filesystem. While compressing the data is an obvious solution, the impacts on the final data products are hard to predict. In this paper, we chose an error-controlled compressor – MGARD – and applied it to simulated SKA-Mid and real pathfinder visibility data, in noise-free and noise-dominated regimes. As the data have an implicit error level in the system temperature, using an error bound in compression provides a natural metric for compression. MGARD ensures the compression incurred errors adhere to the user-prescribed tolerance. To measure the degradation of images reconstructed using the lossy compressed data, we proposed a list of diagnostic measures, exploring the trade-off between these error bounds and the corresponding compression ratios, as well as the impact on science quality derived from the lossy compressed data products through a series of experiments. We studied the global and local impacts on the output images for continuum and spectral line examples. We found relative error bounds of as much as 10%, which provide compression ratios of about 20, have a limited impact on the continuum imaging as the increased noise is less than the image RMS, whereas a 1% error bound (compression ratio of 8) introduces an increase in noise of about an order of magnitude less than the image RMS. For extremely sensitive observations and for very precious data, we would recommend a 0.1% error bound with compression ratios of about 4. These have noise impacts two orders of magnitude less than the image RMS levels. At these levels, the limits are due to instabilities in the deconvolution methods. We compared the results to the alternative compression tool DYSCO, in both the impacts on the images and in the relative flexibility. MGARD provides better compression for similar error bounds and has a host of potentially powerful additional features.

Techniques: interferometric↗
DOE OSTI2023

A fast, accurate and easy to implement Kapur–Rokhlin quadrature scheme for singular integrals in axisymmetric geometries

Many applications in magnetic confinement fusion require the efficient calculation of surface integrals with singular integrands. The singularity subtraction approaches typically used to handle such singularities are complicated to implement and low-order accurate. In contrast, we demonstrate that the Kapur–Rokhlin quadrature scheme is well-suited for the logarithmically singular integrals encountered for a toroidally axisymmetric confinement system, is easy to implement and is high-order accurate. As an illustration, we show how to apply this quadrature scheme for the efficient and accurate calculation of the normal component of the magnetic field due to the plasma current on the plasma boundary, via the virtual-casing principle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Insights into Mechanisms of Screw Feeder Plugging by Heated Pine Forestry Residues Using in-situ and Correlative Microscopy

Increasing concerns about global carbon emissions due to fossil fuel use has created interest in renewable fuel alternatives, such as lignocellulosic biomass. With an estimated global biomass production probability ten-fold higher than projected need, functionalizing and scaling biomass conversion processes, like pyrolysis, is a promising component of a diverse sustainable energy program (Kan, Strezov, & Evans, 2016). Pyrolysis reactors employed in biomass conversion often encounter the known problem of screw feeder plugging, halting work and reducing efficiency of biorefineries. Although the screw feeder is not heated directly, conductive heat transfer from the fluidized bed pyrolysis reactor creates a temperature gradient, where particles experience temperatures between 22°C and 500°C from the time they enter the feeder to being emptied into the reactor (Digman, Joo, & Kim, 2009; Nieminen & Folke, 1982). The impact of unintentional heating on this highly variable feedstock may result in particle morphology modification, surface texture transformation, and the evolution of viscous compounds and may contribute to screw feeder plugging (Haas, Nimlos, & Donohoe, 2009; Ingram et al., 2008). We hypothesized that particles of various anatomical fractions (including needles, branches, bark, cambium, and whitewood) will experience dramatic changes during this heating regime, which will be characterized by decreased particle size, increased surface roughness, degradation of key structural macromolecules, and generation of viscous compounds that would result in increased particle friction and cohesion, contributing to screw feeder plugging.

biofuels↗
DOE OSTI2021

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Data Science Meets Physical Organic Chemistry

At the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate. In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔ G ‡ = - RT ln[( S )/( R )], where ( S ) and ( R ) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way. Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design. In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Pressure-Sensitive Adhesive Combined with Paper Spray Mass Spectrometry for Low-Cost Collection and Analysis of Drug Residues

Illicit drug use causes over half a million deaths worldwide every year. Drugs of abuse are commonly smuggled through customs and border checkpoints and, increasingly, through parcel delivery services. Improved methods for detection of trace drug residues from surfaces are needed. Such methods should be robust, fieldable, sensitive, and capable of detecting a wide range of drugs. In this work, commercially produced paper with a pressure-sensitive adhesive coating was utilized for the collection and analysis of trace drug residues by paper spray mass spectrometry (MS). This modified substrate was used to combine sample collection of drug residues from surfaces with rapid detection using a single paper spray ticket. The all-in-one ticket was used to probe different surfaces commonly encountered in forensic work including clothing, cardboard, glass, concrete, asphalt, and aluminum. A total of 10 drugs (acetyl fentanyl, fentanyl, clonazolam, cocaine, heroin, ketamine, methamphetamine, methylone, U-47700, and XLR-11) were evaluated and found to be detectable in the picogram range using a benchtop mass spectrometer and in the low nanogram range using a portable ion trap MS. Finally, the novel approach demonstrates a simple yet effective sampling strategy, allowing for rapid identification from difficult surfaces via paper spray mass spectrometry.

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

Scanning Electrochemical Microscopy for Kinetic Investigations in Viscous Deep Eutectic Solvents: Identifying Practical Approach Curves and Deviations from Electron Transfer Models

Determining heterogeneous electrochemical electron transfer (ET) kinetics in electrolytes with a wide range of physical properties is of great interest for achieving high-performance redox flow batteries. Among such electrolytes, concentrated hydrogen-bonded electrolytes (CoHBEs), including deep eutectic solvents (DESs), have recently garnered significant attention. Unfortunately, traditional Tafel analysis using macroelectrodes often encounters issues with mass transfer limitations in CoHBEs with high viscosities, thereby restricting kinetic analysis to a narrow potential window. Here, in this work, we introduce a methodology for evaluating ET kinetics in viscous DES using the scanning electrochemical microscopy (SECM). We first determined practical solutions to SECM tip positioning in ethaline DES, which yield pseudopositive feedback responses. Lattice Boltzmann method (LBM) simulations helped us rationalize the impact of the fluid and concentration fields, as well as tip geometry, tip approach velocity v, and the solvent viscosity ηs, on the shape of the approach curves. In addition to successfully recreating approach curves over a variety of conditions, we found that approaching a conductor ensured a practical point where the normalized tip response (Ni T = 2) converged at L = 0.7 within ∼10% error regardless of tip velocity. With positioning capabilities at hand, we investigated the kinetics of Fe 3+ /Fe 2+ redox couple in aqueous and the ethaline media. The experimental kinetic results were interpreted using the Butler–Volmer (BV) and Marcus–Hush–Chidsey (MHC) models. For ethaline, a nonideal kinetic behavior was observed, potentially attributed to solvent dynamics within DESs or to the interplay of chloride anions in the charge transfer process.

electrodes↗
DOE OSTI2026

Single-Particle Isotopic Analysis Using the Liquid Sampling-Atmospheric Pressure Glow Discharge Microplasma Coupled to an Orbitrap Mass Spectrometer

Isotope ratio (IR) determinations on individual particles can provide valuable information relative to the sample, including processing and dating, which could be valuable to geological and nuclear material analysis communities. In comparison to “bulk” measurements, in which all particle information is lost and homogenized within a sample, “particle” measurements allow for fingerprinting and can provide unique insights related to the sample’s nano- and micro- compositions. Furthermore, the complex nature of particles, with potential isobaric interferences from either the matrix or other elements within the same particle, poses a significant analytical challenge for conventional mass spectrometry platforms employed for elemental analysis due to their limited mass resolution. Presented here is the first demonstration of an ultrahigh resolution method for single particle (SP) isotopic analysis using the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an Orbitrap mass spectrometer and FTMS Booster X2T acquisition/processing system. For proof of concept, well-characterized CeO 2 microparticles with a nominal diameter of 1.0 μm were analyzed at a mass resolution of ∼330,000. Important instrumental parameters were optimized to enable the detection of single particles. The 142 Ce/ 140 Ce ratio of individual particles and the population average were determined and compared to an SP inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) analysis. The isotopic accuracy and precision were determined by two methods and found to be in good agreement with the SP-ICP-TOF-MS method, with the linear regression slope method providing a more accurate ratio, showing a ∼1.4% relative difference from the ratio determined from a particle digest. The encouraging performance of the method was further supported by a determined detection limit of 2.9 fg ( 142 Ce). The developed method is anticipated to overcome many of the challenges posed by isobaric interferences encountered in conventional mass spectrometry techniques when analyzing real-world samples for particle isotopic composition.

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

Reactions of Studtite UO 4 ·4H 2 O in Alkali Hydroxides: Isolation of Single-Crystal Uranate Phases under Mild Hydrothermal Conditions

Uranyl peroxide complexes, particularly studtite (UO 4 ·4H 2 O), are important phases within the nuclear fuel cycle, forming through radiolysis-induced reactions on the surfaces of spent fuel and in waste environments. Studtite has been identified in Hanford’s irradiated fuel storage basins, Chornobyl’s corium lavas, and is anticipated on Fukushima’s fuel debris. While its formation and stability have been extensively studied, the reactivity of UO 4 ·4H 2 O in highly alkaline environments such as those encountered in high-level nuclear waste remains underexplored. These environments contain molar concentrations of [OH - ] and present a chemically dynamic and reactive environment where actinide behavior is not well understood. Reported here are investigations of uranium reactions in concentrated alkali hydroxides under mild hydrothermal conditions (<200 °C) that have resulted in the isolation of the alkali metal uranates Li 2 UO 4 , α-Na 2 UO 4 , γ-Na 2 U 2 O 7 , and K 2 U 2 O 7 . In contrast to conventional solid-state methods (>800 °C) that typically yield polycrystalline powders, our approach enables the isolation of these uranates as single crystals, allowing us to provide single-crystal structure solutions of certain uranates for the first time. Our findings match the results of high-level waste tank sampling, confirming that sodium diuranate (Na 2 U 2 O 7 ) is the most persistent uranium phase, potentially forming through reactions of uranyl peroxide intermediates with NaOH under radiolytic and highly alkaline conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

The Intermetallic Reactivity Database: Compiling Chemical Pressure and Electronic Metrics toward Materials Design and Discovery

Here, the advent of high-throughput Density Functional Theory (DFT) calculations has supported the creation of large databases containing the quantitative output necessary for constructing theoretical phase diagrams and predicting physical properties. In this Article, we present a complementary resource, the Intermetallic Reactivity Database (IRD), focused on the chemical bonding features of solid-state structures and indicators of potential structural transformations. Each IRD entry augments common features, such as band structures and density of states (DOS) distributions, with chemically motivated information including DFT-Chemical Pressure (CP) schemes and visualizable representations of the atomic charges. Together, these data types enable the rationalization and prediction of potential structural phenomena encountered in intermetallic chemistry, as we illustrate with four examples: the origins of the Y 2 Ni 2 Mg structure in terms of CP features of its parent structures, the anticipation of intergrowth phases from the net atomic CPs collected in Al-containing binary phases, the correlation between trends in the CP schemes of CaCu 5 -type phases and experimentally observed structural variations, and finally, the development of theoretical methodology with the testing of a streamlined method generating DFT-CP schemes. Altogether, these examples highlight how the IRD supports the creation of models of structural chemistry that extend beyond the bounds of its entries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Static and Dynamic Intensification of Water–Ethylene Glycol Separation Using a Dividing Wall Column

This paper makes several first-of-a-kind contributions toward “double intensification” (static/dynamic) of distillation systems, focusing in particular on the energy-intensive separation of a mixture of water and ethylene glycols. First, we demonstrate that a dividing wall column (DWC) can be an appropriate choice for separating wide-boiling zeotropic mixtures. Additionally, we show that the conventional DWC configuration where the wall is in the “middle” should be discarded in favor of a less frequently encountered “common-bottom” setup. For the mixture considered, choosing a DWC in lieu of a conventional two-column sequence can lead to over 6% energy cost savings and a 5% reduction in the number of stages compared to the conventional direct sequence two-column counterpart. The second part of this paper focuses on applying the previously introduced concept of dynamic process intensification to the DWC, the first time that such an effort is reported in the literature, to our knowledge. Here, we show that an additional 1.4% energy savings can be unlocked in this way, and confirm the stable operation of the column via dynamic simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Enhancing the Chemical Energy Flux in a High-Temperature Tubular Counterflow Solid Fuel Synthesis Reactor Using a Bypass

Redox reactions of metal oxides offer a path towards using intermittent renewable resources for high-density thermochemical energy storage. Thermochemical energy storage often involves the flow of a particulate media. We describe a novel method to increase the throughput in a gravity-driven high-temperature thermochemical storage reactor flowing pelletized MgMnO. The moving bed reactor operates under counter-flow conditions and encounters particle flowability problems at temperatures of 1500 °C leading to sintering of the bed. Inertial forces of a counter-flowing gas can overcome the gravitational forces on the particles and limit the chemical energy storage rate of the reactor. We found that the insertion of a gas bypass (a slotted tube) into the reactor results in a 100% increase of the flow rates and achieved a 50% higher chemical energy storage flux compared to the operation without a bypass tube while mitigating the effects of sintering on the particles. As a result, the higher solid flow rates require a longer heated zone to reach a comparable residence time and extent of reduction compared to the lower flow rates.

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

A Semi-Empirical Density Law for Ternary, Homogeneous PuCl 3 /HCl/H 2 O Solutions

Nuclear material operations pose unique hazards that are not encountered in other chemical, energy, or manufacturing industries. One of these hazards is the potential for a nuclear criticality accident when handling fissile isotopes such as 235 U and 239 Pu. These hazards are particularly high when fissile material is dissolved in solution as the neutron behaviors of the system can change rapidly with the physical and chemical changes accessible in solution. Current estimates of solution density used for criticality safety are outdated and hinder fissile material handling. Developing new estimates for these safety calculations requires experimental characterization and the derivation of empirical density models. We have derived a density law describing PuCl 3 /HCl/H 2 O solutions from experimental data characterizing solution density. Density data was treated using a Pitzer-derived eight-parameter equation, defining density as a function of analyte concentrations, temperature, and interactions between these variables. The model is predictive across the concentration and temperature ranges from which it was derived. The potential effects of varying oxidation states of plutonium, which are easily accessible in aqueous media, on the bulk solution density of the ternary system were also investigated. The resulting Pitzer-derived density law was applied to a nuclear criticality safety model, and the impact of the experimental characterization of solution density relative to previous estimates was demonstrated to be significant and suggest that the current approach to estimating density in nuclear criticality safety calculations may lead to overly conservative controls.

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

Iron(III)–Oxo Cluster Chemistry with Dimethylarsinate Ligands: Structures, Magnetic Properties, and Computational Studies

A program has been initiated to develop Fe III /oxo cluster chemistry with the ‘pseudo-carboxylate’ ligand dimethylarsinate (Me 2 AsO 2 - ) for comparison with the well investigated Fe III /oxo/carboxylate cluster area. The synthesis and characterization of three polynuclear Fe III complexes are reported, [Fe 12 O 4 (O 2 C t Bu) 8 (O 2 AsMe 2 ) 17 (H 2 O) 3 ]Cl 3 (1), Na 2 [Fe 12 Na 2 O 4 (O 2 AsMe 2 ) 20 (NO 3 ) 6 (Me 2 AsO 2 H) 2 (H 2 O) 4 ](NO 3 ) 6 (2) and [Fe 3 (O 2 AsMe 2 ) 6 (Me 2 AsO 2 H) 2 (hqn) 2 ](NO 3 ) (3), where hqn is 8-hydroxyquinoline. The Fe 12 core of 1 is a type never previously encountered in Fe III carboxylate chemistry, consisting of two Fe 6 units each of which comprises two {Fe 3 (μ 3 -O 2- )} units bridged by three Me 2 AsO 2 - groups and linked into an Fe 12 loop structure by two anti-anti η 1 :η 1 :μ Me 2 AsO 2 - groups, a bridging mode extremely rare with carboxylates. 2 also consists of two Fe 6 units, differing in their ligation from those in 1, and this time linked together into a linear structure by a central {Na 2 (NO 3 ) 2 } bridging unit. 3 is a linear Fe 3 complex with no monoatomic bridges between Fe III ions, a very rare situation in Fe III chemistry with any ligands, and unprecedented in Fe carboxylate chemistry. The distinct differences observed in arsinate vs carboxylate ligation modes are rationalized largely based on the greater basicity of the former vs the latter. Variable-temperature dc and ac magnetic susceptibility data reveal all Fe 2 pairwise interactions to be antiferromagnetic. For 1 and 2, the different J ij couplings were estimated by use of a magnetostructural correlation for high nuclearity Fe III -oxo clusters and by density functional theory calculations using broken symmetry methods, allowing identification of their relative spin vector alignments and thus rationalization of their S = 0 ground states. The J ij values were then used as input values to give excellent fits of the experimental χM T vs T data. For 3, the fits of the experimental χM T vs T data to the Van Vleck equation or with PHI gave a very weak J 12 = -0.8(1) cm -1 (H = –2JŠ i ·Š j convention) between adjacent Fe III ions, and an S = 5/2 ground state. Furthermore, these initial Fe III arsinate complexes also provide structural parameters that help validate literature assignments of arsinate binding modes to iron oxide/hydroxide minerals as part of environmental concerns of using arsenic-containing herbicides in agriculture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Guide to Nonaqueous Electrochemistry of f-Element Complexes

Electrochemistry is a powerful tool for assessing and understanding the redox chemistry of molecular complexes. Cyclic voltammetry enables the f-element community to study molecules in unusually high or low oxidation states, which potentially pose important broad-scope questions of electronic structure. In the pursuit of boundary-pushing compounds, reactive air- and moisture-sensitive species are often encountered, which can be challenging to characterize, especially when they are chemically incompatible with certain solvents, electrolytes, or electrodes or when their potentials lie outside of common electrochemical windows. Nonaqueous solvents and pseudo reference electrodes complicate many of the standard practices in acquiring high-quality and reproducible electrochemical data. This guide presents a detailed discussion of selecting appropriate cell conditions and referencing and addresses metrics for evaluating electrochemical and chemical reversibility. These methodological approaches have been extended to best practices for the electrochemical analysis of radioactive transuranic complexes.

Electrodes↗