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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Particle acceleration during classical phase transitions on a spherical lattice

Abstract When compressed, certain lattices undergo phase transitions that may allow nuclei to gain significant kinetic energy. To explore the dynamics of this phenomenon, we develop a methodology to study Coulomb coupled N -body systems constrained to a sphere, as in the Thomson problem. We initialize N total Boron nuclei as point particles on the surface of the sphere, allowing them to equilibrate via Coulomb scattering with a viscous damping term. To simulate a phase transition, we remove N rm particles, forcing the system to rearrange into a new equilibrium. With this model, we consider the Thomson problem as a dynamical system, providing a framework to explore how non-zero temperature affects structural imperfections in Thomson minima. We develop a scaling relation for the average peak kinetic energy attained by a single particle as a function of N and N rm . For certain values of N , we find an order of magnitude energy gain when increasing N rm from 1 to 6. The model may help to design a lattice that maximizes the energy output.

Bachmann, Aidan M. (ORCID:0000000294706404)↗
DOE OSTI2024

Comparison of chamber beam geometry robustness to mispointing, imbalance and target offset for direct-drive laser fusion facilities

This study focuses on the optimization of beam chamber geometry designs for future direct-drive laser facilities. It provides a review of leading target chamber geometries, with a particular emphasis on random errors. Through comprehensive solid-sphere illuminations and analysis, we identify an optimized beam geometry design, highlighting its robustness and performance under realistic experimental conditions. Three major sources of random errors are evaluated, closely linked to experimental evaluations at OMEGA. The findings underscore the importance of optimizing the irradiation system alongside beam pattern considerations to enhance the efficiency and reliability of inertial confinement fusion experiments. We conclude that for a desired illumination uniformity of 1% in the presence of system errors, the split icosahedron design is the most robust. However, for a 0.3% uniformity goal, the charged-particle, icosahedron, and t-sphere methods exhibit similar performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

On-shell derivation of the soft effective action in Abelian gauge theories

We derive the soft effective action in (d+2)-dimensional Abelian gauge theories from the on-shell action obeying Neumann boundary conditions at timelike and null infinity and Dirichlet boundary conditions at spatial infinity. This allows us to identify the on-shell degrees of freedom on the boundary with the soft modes living on the celestial sphere. Following the work of Donnelly and Wall, this suggests that we can interpret soft modes as entanglement edge modes on the celestial sphere and study entanglement properties of soft modes in Abelian gauge theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Entanglement, trace anomaly, and confinement in QCD

We formulate confinement in quantum chromodynamics (QCD) as an entropic surface phenomenon. Quark and gluon quantum information is localized on a transverse, entangling two-sphere of radius 𝑅 𝐸⁢𝐸 ; at this radius the QCD vacuum—partitioned by a hadron into interior and exterior regions—reaches its maximal entanglement entropy. Lattice-QCD determinations of the scalar (trace) gravitational form factors fix both 𝑅 𝐸⁢𝐸 and the transverse trace-anomaly density 𝜌 ℎ ⁡(𝑅 𝐸⁢𝐸 ), yielding a parameter-free slope 𝑐 ℎ = 8⁢𝜋 2 ⁢𝑅𝑆$^2_{𝐸⁢𝐸}$𝜌 ℎ ⁡(𝑅 𝐸⁢𝐸 ) and a mechanical entropy 𝑆 𝐸⁢𝐸 ⁡(𝑦) = 𝑐 ℎ ⁢𝑦 that grows linearly with rapidity 𝑦. The entropy gradient ∂ 𝑅 𝑆 𝐸⁢𝐸 changes sign at 𝑅 𝐸⁢𝐸 : it pushes colored degrees of freedom outward for 𝑟 <𝑅 𝐸⁢𝐸 and pulls them inward for 𝑟 >𝑅 𝐸⁢𝐸 , thereby localizing them on the codimension-2 entangling two-sphere Σ ⊥ = 𝑆$^2_{𝑅_{𝐸⁢𝐸}}$ (which, in the infinite-momentum frame (IMF), projects onto the transverse plane)—the “information wall.” This provides a high-energy (large-𝑦) entropic confinement diagnostic that complements—rather than replaces—Wilson’s area-law criterion, which probes long-distance dynamics near the rest frame (𝑦 → 0). Imposing unitarity on an entropic ansatz for the amplitude yields 𝜎⁡(𝑠) ∝ 𝑦 𝛿 . World data favor 𝛿 = 2 for elastic 𝑝⁡𝑝⁡($𝑝\bar{⁡𝑝}$) scattering and heavy-quark photoproduction, whereas 𝜙 photoproduction favors a softer 𝛿 = 0.387. All extracted cross sections remain well below the Froissart-Martin bound. These results provide a confinement criterion quantified directly from nonperturbative QCD inputs, unifying the trace anomaly, entanglement entropy, and high-energy scattering within a single quantitative framework.

Color confinement↗
DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

SOC Microstructural Analyzer

This program was designed to analyze the 3-phase microstructure of the electrodes of a solid oxide fuel cell (SOFC) or electrolysis cell (SOEC), both referred to in combination as a solid oxide cell (SOC). It is agnostic to the exact system, so it could be repurposed to analyze any 3-phase microstructure. This tool directly analyzes segmented voxel-based data that has been segmented into phase IDs (1,2,3). The voxels will be analyzed directly for: - tortuosity factors - triple phase boundaries - 2-phase interfacial areas, using a meshed isosurface - mean diameters of each phase, using an inscribed sphere method - standard deviation of the diameters of each phase, from the same inscribed sphere data - connectivity information Comprehensive information is available in the readme file (within the zipped repository in Markdown language, and also available here as a rendered PDF). Please cite this page / DOI, as well as https://doi.org/10.1111/jace.14775, for usage.

3D microstructure↗
DOE OSTI2024

Matching Curved Lattices to Anisotropic Tangent Planes

Radial quantization would be the ideal formalism for studying strongly-coupled near-conformal quantum field theories but it requires the ability to perform lattice calculations on static, curved manifolds, specifically a very long cylinder whose cross section is a sphere. Smoothly discretizing the surface of a sphere requires a graph with unequal edge lengths. The geometry of such graphs is well understood since 1961 using Regge Calculus. But, lattice quantum field theories are defined in terms of couplings which appear in the action rather than edge lengths and so the relationship between couplings and lengths must be determined dynamically. A simple example is computing the ratio of spatial to temporal lattice spacings in anisotropic lattice QCD. I will discuss our conjecture that computing anisotropic lattice spacing ratios on affine transformations of regular flat lattices is sufficient to determine coupling assignments on curved lattices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

MFiX Development Updates

This presentation discusses recent developments of the Multiphase Flow with Interphase eXchanges (MFiX) software. A brief review of all modeling approaches along with their cost versus accuracy is provided to guide users when selecting a model for a given application. The main new features of the past five official releases of MFiX are described. Improvement in chemistry management allow for easier simulation setup, and faster simulation speed. Progress in the implementation of a thin-wall boundary condition is presented. The major new model development over the past year is the release of the Glued Sphere Particle model (GSP), where component spheres are combined together to represent non-spherical particles. The integration of Machine Learning (ML) workflow in the CFD process is discussed with two applications: a surrogate model for stiff chemistry and the development of a PIC stress model using ML.

Dietiker, Jeff↗
DOE OSTI2024

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗
DOE OSTI2024

Adaptive Methods for Radial Basis Functions

Radial basis functions (RBFs) are a powerful tool for constructing high-order accurate reduced representations of scattered data in arbitrary dimension and on manifolds. We present a method of constructing data approximations in which we utilize a functional tail to capture a global background profile and a RBF neural network (NN) to capture the smaller-scale features. In the RBF NN the RBF centers, matrix shape parameters were selected adaptively for each RBF. We also utilized a geodesic notion of distance on the manifold on which the data lies, e.g., the spherical geodesic for data on the sphere. Although each of these ideas have been been investigated separately in previous works, their combination into a single algorithm is novel. We defined a machine learning problem in which these properties are learned to minimize the data reduction error. We demonstrate the algorithm for applications of scattered data reduction in the plane and on the sphere.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

dynamics of organic-mineral interactions at the metal oxide-solution interface as studied via binding energetics (Final report)

This project focused on addressing longstanding fundamental and experimental uncertainties on how dissolved organic substances (DOS) interact with metal oxide surface under environmentally relevant conditions. By leveraging a custom-built real-time, in-tandem flow adsorption microcalorimetry-UV-Vis/fluorescence spectroscopy platform, we characterized the binding energetics, kinetics and mechanistic pathways driving DOS-metal oxide interactions at temporal resolution on the order of 1-5 seconds. We studied a diverse suite of model organic compounds/substances – including monocarboxylates (e.g. acetate and benzoate), di-carboxylates (oxalate and succinate), amino acids, amino-based nanparticles and natural organic matter – interacting at the mineral-water interface of structurally- and/or chemically distinct metal oxides (including SiO2, boehmite, ferrihydrite, and γ-Al2O3). Our results indicated that DOS-metal oxide interactions are governed by multi-step reaction pathways, often switching between distinct, resolvable enthalpy- and entropy-driven non-electrostatic or electrostatic configurations. To quantify these interactions, we developed and implemented an analytical workflow that integrates peak deconvolution and Monte-Carlo based error propagation to determine site-specific thermodynamic and kinetic parameters for individual binding/debinding events. In addition to resolving apparent first-order rate constants of each event, we were able to quantify associated apparent equilibrium constants as well as free energy, enthalpy and entropy contribution to the activation and subsequent progression of the binding/debinding process across compounds, compound class and metal oxide surfaces. The kinetic-thermodynamic data produced in this study captured how the interplay between oxide surface reactivity and DOS molecular structure jointly drives binding-debinding dynamics. Notably, that at pH below PZC of the oxide surface, neutral species were heavily involved in monocarboxylate binding, while anionic species drove dicarboxylate binding. Also, that among amino acids 1) positional isomers show distinctive binding characteristics to each other while enantiomers show no significant differences in binding characteristics, 2) molecules that bind via outer-sphere complexation show a larger entropic shift between binding and debinding with no impact on oxide surface while 3) inner-sphere interactions increased anion exchange capacity of the oxide surface. The new insights and data from this work has great potential for improving predictive modeling of carbon dynamics and specifically organic-mineral interactions in environmental and industrial systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

The Role of Cooperative Interactions Among Surfaces, Solvents, and Reactive Intermediates on Catalysis at Liquid–Solid Interfaces (Final Report DE-SC0020224)

This project established quantitative links between inner‑sphere chemistry (active metal identity, coordination, and zeolite topology) and outer‑sphere organization (solvent identity, hydrogen‑bond networks, and pore condensation) that govern rates, activation barriers, and selectivities for alkene epoxidation and epoxide ring‑opening at solid–liquid and quasi‑liquid–solid interfaces. We deconvoluted contributions from covalent interactions at active sites and noncovalent, solvent‑mediated interactions within pores by pairing well‑defined metal substituted zeolites with controlled solvent environments. We then mapped those contributions onto measurable kinetics (ΔH‡, ΔS‡), adsorption thermodynamics (ITC), and in situ spectroscopy. The transferrable outcomes include a set of design rules that include the following understandings. First, tune silanol ((SiOH)x) density and pore topology to organize solvent networks that selectively stabilize transition states. Second, exploit activity‑coefficient‑normalized rates and adsorption– barrier correlations to diagnose when solvent reorganization rather than surface chemistry limits performance. Third, use partial pore condensation (e.g., acetonitrile, water but also generalizable to other solvents) to elicit liquid‑like stabilization effects even in nominally vapor‑phase reactors. Collectively, these results provide strategies to increase epoxidation rates, improve oxidant utilization (i.e., selectivities), and steer regioselectivity in zeolite‑based catalytic processes relevant to sustainable oxidation chemistry. These outcomes should be transferable to other classes of reactions that proceed in microporous materials and under confinement provided by organized solvents (e.g., electrochemical double layers).

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

Hypersonic Wake Velocity Measurements Using Acetone Molecular Tagging Velocimetry

A non-intrusive laser diagnostic known as molecular tagging velocimetry was used to find quantitative off-body velocity measurements in the wake of a sphere in the Mach 7 Ludwieg Tube Wind Tunnel located at The University of Texas at San Antonio. Acetone gas seeded in the flow was excited using the 4th harmonic of a pulse-burst Nd:YAG laser. The experimental results were used to validate and compare to simulations using a continuous Galerkin flow solver. Both the experimental and simulated results agreed on negative velocities in the viscous shear layer. Near the centerline of the sphere, average velocities of -200 m/s were observed due to reverse flow in the recirculation region. Outside of the shear layer, velocities of 800 m/s were observed in both the experimental and simulated results. The overall average uncertainty for the strut-mounted and free-flight case was estimated to be ±27 m/s. The flow features of the wake were visualized using schlieren imaging, and the experimental results agreed well with the simulated results.

Shoemake, Lawton↗
DOE OSTI2024

Adsorption of neodymium, dysprosium, and ytterbium to goethite under varying aqueous chemistry conditions [dataset]

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (< 5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (> 5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. A SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. This predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗
DOE OSTI2024

Flattop-HEU Benchmark Reevaluation Summary

The Flattop critical assembly was first constructed in the 1950’s at Los Alamos National Laboratory as a follow-on to the Topsy experiment. Flattop is composed of a sphere of special nuclear material (SNM) surrounded by a thick spherical reflector made of natural uranium (NU). Two SNM cores currently exist: a highly-enriched-uranium (HEU) core and a plutonium core. The reflector is composed of three parts: a stationary hemisphere and two movable quarter spheres. For fine reactivity control, there are three control rods of NU that are inserted into the stationary hemisphere from underneath the assembly. The final components that allow for reactivity adjustment are the glory hole pieces, mass adjustment buttons, and hemispherical caps. These pieces can be loaded in various configurations to change the available reactivity loaded in the system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Chelator‐Assisted Precipitation‐Based Separation of the Rare Earth Elements Neodymium and Dysprosium from Aqueous Solutions

The rare earth elements (REEs) are critical resources for many clean energy technologies, but are difficult to obtain in their elementally pure forms because of their nearly identical chemical properties. Here, an analogue of macropa, G-macropa, was synthesized and employed for an aqueous precipitation-based separation of Nd 3+ and Dy 3+ . G-macropa maintains the same thermodynamic preference for the large REEs as macropa, but shows smaller thermodynamic stability constants. Molecular dynamics studies demonstrate that the binding affinity differences of these chelators for Nd 3+ and Dy 3+ is a consequence of the presence or absence of an inner-sphere water molecule, which alters the donor strength of the macrocyclic ethers. Leveraging the small REE affinity of G-macropa, we demonstrate that within aqueous solutions of Nd 3+ , Dy 3+ , and G-macropa, the addition of HCO 3 − selectively precipitates Dy 2 (CO 3 ) 3 , leaving the Nd 3+ −G-macropa complex in solution. With this method, remarkably high separation factors of 841 and 741 are achieved for 50 : 50 and 75 : 25 mixtures. Further studies involving Nd 3+ :Dy 3+ ratios of 95 : 5 in authentic magnet waste also afford an efficient separation as well. Finally, G-macropa is recovered via crystallization with HCl and used for subsequent extractions, demonstrating its good recyclability.

Gao, Yangyang↗
DOE OSTI2026

Redox‐Mediated Electrochemical Regeneration of Spent LiFePO 4 Battery Cathodes

Direct recycling of lithium-ion battery cathodes offers considerable appeal over metallurgical approaches. Here, we demonstrate a mediated electrochemical method for direct regeneration of degraded LiFePO 4 (LFP). The approach uses a redox mediator, iron propylenediamine tetraacetate, that undergoes electrochemical reduction and is circulated through an external reservoir, where it supplies the electrons needed to regenerate LFP in the presence of Li + ions derived from LiOH oxidation. Rapid outer-sphere electron transfer is observed from the mediator to the degraded LFP material. This feature, together with good aqueous solubility of the mediator (0.3 M), supports current densities up to 100 mA/cm 2 , and this electrochemical recycling process is demonstrated on 100 g scale. 57 Fe Mössbauer spectroscopy is used to monitor the correction of structural defects in the degraded LFP, providing the basis for regeneration of LFP that matches the electrochemical performance of pristine LFP.

Electrochemical Relithiation↗