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DOE OSTI2022

Supramolecular Control of Redox-Mediated Interactions for Ion-Selective Electroseparations

This report summarizes efforts from the Su Group at the University of Illinois at Urbana-Champaign in researching and developing materials and processes for the recovery of rare earth elements and other metal elements that are critical to the United States economy and national security, under DOE Award No. DE-SC0021409. This report highlights efforts in the recovery of: • Transition metal elements (including arsenic, chromium, molybdenum, rhenium, vanadium): Redox-active metallopolymers are able to capture these elements in their oxyanion form. Direct control of target ion capture/release through electrochemical-mediated switching of metallocene binding sites reduces chemical input and lowers generation of waste in element recovery processes. We study the effects of metallopolymer structure on targeted ion binding through a combination of experimental screening of ion selectivity from multi-component mixtures, computational efforts which elucidate the charge-transfer origins of metallocene binding and provide insight on how binding site structure influences selectivity, and state-of-the-art neutron reflectivity of metallocene polymer films to understand the interplay of polymer-ion (charge-transfer), polymer-solvent (polymer hydrophilicity/hydrophobicity), and ion-solvent (ion hydration) interactions with spatial resolution of polymer films. • Rare earth elements (including yttrium, neodymium, europium, gadolinium, dysprosium, cerium): Here we employ redox-copolymers for recovery of rare earth elements by electrochemically regenerated ion-exchange. Rare earth elements require an alternative route to capture/release than directly with metallopolymers since rare earth elements typically exist in cationic form in water. To address this, copolymerization of traditional ion-exchange moieties with metallocene moieties allowed for capture of rare earth elements with the ion-exchange moieties and electrochemical-mediated release of rare earth elements through oxidation of metallocene moieties.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Ultrafast pre-solvated dodecane hole capture and subsequent damage of used nuclear fuel extraction ligands DEHBA, DEH i BA, HONTA, CMPO, HEH[EHP] and TBP

Here, two classes of used nuclear fuel (UNF) extraction ligands, amide (DEHBA, DEH i BA, HONTA) and organophosphorus (CMPO, HEH[EHP], TBP), were selected to study radiation induced damage at picosecond to nanosecond timescale using electron pulse radiolysis in n-dodecane (DD) and supported by quantum chemical calculations. Spectra after radiolysis of 200 mM extraction ligands were recorded in DD/0.3 M DCM. Absorption peaks at 365, 365, 400 and 387 nm in case of DEHBA, DEH i BA, HONTA and CMPO respectively are assigned to triplet excited states. Additional absorption peaks at 420, 460 and 600 nm of DEHBA, DEH i BA and HONTA respectively were identified as due to ligand radical cations. A concentration dependent absorption peak at 600 nm in the case of CMPO was observed and assigned due to a combination of CMPO˙ + , (CMPO) 2 ˙ + and possibly a radical degradation product of CMPO. Weak absorption peaks at 650 and 550 nm in case of HEH[EHP] and TBP were observed and tentatively assigned to their radical cations. A two-component DD˙ + decay in the presence of ligands was observed due to different ligand oxidation mechanisms: ultrafast capture of pre-solvated DD holes and diffusive capture of solvated DD holes. At high extraction ligand concentrations (>100 mM), the majority of DD holes were captured via the ultrafast pre-solvated pathway in <10 ps with C 37 values of 389, 401, 270, 374, 458 and 340 mM for DEHBA, DEHiBA, HONTA, CMPO, HEH[EHP] and TBP respectively. Following ultrafast capture, the remainder of DD holes became solvated and were captured with k = (2.32 ± 0.13), (1.78 ± 0.12), (1.38 ± 0.2), (0.98 ± 0.081), (1.09 ± 0.08) and (1.77 ± 0.046) × 10 10 for DEHBA, DEH i BA, HONTA, CMPO, HEH[EHP] and TBP respectively. Subsequent hole transfer from the extraction ligands˙ + to the low IP solute tri-p-tolylamine (TTA) showed only 4–16% hole transfer, most likely indicating ligand˙ + degradation in 0.9–4.6 ns.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Systematic Improvement of Quantum Monte Carlo Calculations in Transition Metal Oxides: sCI-Driven Wavefunction Optimization for Reliable Band Gap Prediction

Accurate determination of the electronic properties of correlated oxides remains a significant challenge for computational theory. Traditional Hubbard-corrected density functional theory (DFT+U) frequently encounters limitations in precisely capturing electron correlation, particularly in predicting band gaps. We introduce a systematic methodology to enhance the accuracy of diffusion Monte Carlo (DMC) simulations for both ground and excited states, focusing on LiCoO 2 as a case study. By employing a selected configuration interaction (sCI) approach, we demonstrate the capability to optimize wavefunctions beyond the constraints of single-reference DFT+U trial wavefunctions. Here, we show that the sCI framework enables accurate prediction of band gaps in LiCoO 2 , closely aligning with experimental values and substantially improving traditional computational methods. The study uncovers a nuanced mixed state of t 2g and e g orbitals at the band edges that is not captured by conventional single-reference methods, further elucidating the limitations of PBE+U in describing d-d excitations. Our findings advocate for the adoption of beyond-DFT methodologies, such as sCI, to capture the essential physics of excited-state wavefunctions in strongly correlated materials. The improved accuracy in band gap predictions and the ability to generate more reliable trial wavefunctions for DMC calculations underscore the potential of this approach for broader applications in the study of correlated oxides. This work not only provides a pathway for more accurate simulations of electronic structures in complex materials but also suggests a framework for future investigations of the excited states of other challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Uncertainty-informed selection of CMIP6 Earth System Model subsets for use in multisectoral and impact models

Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.

Snyder, Abigail C.↗

NASA NTRS2002

Quantum Dynamics Study of the Isotopic Effect on Capture Reactions: HD, D2 + CH3

Time-dependent wave-packet-propagation calculations are reported for the isotopic reactions, HD + CH3 and D2 + CH3, in six degrees of freedom and for zero total angular momentum. Initial state selected reaction probabilities for different initial rotational-vibrational states are presented in this study. This study shows that excitations of the HD(D2) enhances the reactivities; whereas the excitations of the CH3 umbrella mode have the opposite effects. This is consistent with the reaction of H2 + CH3. The comparison of these three isotopic reactions also shows the isotopic effects in the initial-state-selected reaction probabilities. The cumulative reaction probabilities (CRP) are obtained by summing over initial-state-selected reaction probabilities. The energy-shift approximation to account for the contribution of degrees of freedom missing in the six dimensionality calculation is employed to obtain approximate full-dimensional CRPs. The rate constant comparison shows H2 + CH3 reaction has the biggest reactivity, then HD + CH3, and D2 + CH3 has the smallest.

Wang, Dunyou↗

DOE OSTI2025

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Contrast Matching Biopolymers: A SANS-Based Approach to Structural Characterization of Chitosan

Immobilizing enzymes in polysaccharide-based matrices has been shown to improve both their stability and their catalytic efficiency. Among available materials, chitosan was selected for its abundance, biocompatibility, and versatility in a range of applications. While the broader aim of this work is to study chitosan as a matrix for immobilizing carbonic anhydrase (CA) for CO₂ capture, this study focused on determining the contrast match point (CMP) of hydrogenated and deuterated chitosan in D₂O:H₂O mixtures to enable future structural investigations using small-angle neutron scattering (SANS). Previous work successfully synthesized deuterated chitosan from Rhizopus oryzae mycelia and assessed the degree of deuteration using Fourier-transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR). Building on this foundation, the current study determined the CMPs of both H-chitosan and D-chitosan by performing SANS measurements across a range of D₂O:H₂O solvent contrasts. The extracted CMPs for both forms correlated well with their respective calculated scattering length densities (SLDs), validating the experimental approach. These results establish a critical reference for selective contrast matching in future SANS studies of carbonic anhydrase immobilized in chitosan matrices, enabling detailed structural analysis of enzyme–matrix interactions.

Kosgallana, Chathurika J [ORNL] (ORCID:00000002851↗

DOE OSTI2021

Additively manufactured electrodes for plasma and power-flow studies in high-power transmission lines on the 1-MA MAIZE facility

Power-flow studies on the 30-MA, 100-ns Z facility at Sandia National Laboratories have shown that plasmas in the facility’s magnetically insulated transmission lines (MITLs) and double post-hole convolute can result in a loss of current delivered to the load. To study power-flow physics on the 1-MA, 100-ns MAIZE facility at the University of Michigan, planar MITL loads and planar post-hole convolute loads have been developed that extend into the lines of sight for various imaging diagnostics on MAIZE. These loads use 3D-printed dielectric support structures lined with thin foils of either aluminum or stainless steel. Here, the metal foils serve as the current-carrying power-flow surfaces, which generate plasma during the current pulse. The foil thickness (50 µm) and widths (11.5–16 mm) are selected to ensure a sufficient linear current density (0.5–0.7 MA/cm) for plasma formation. Laser backlighting (532 nm) and visible-light self-emission imaging capture the overall plasma evolution in the anode–cathode gaps, including the gap closure velocities (1–4 cm/μs).

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Developing new analysis tools for near surface radio-based neutrino detectors

The ARIANNA experiment is an Askaryan radio detector designed to measure high-energy neutrino induced cascades within the Antarctic ice. Ultra-high-energy neutrinos above 10 16 eV have an extremely low flux, so experimental data captured at trigger level need to be classified correctly to retain as much neutrino signal as possible. We first describe two new physics-based neutrino selection methods, or "cuts", (the updown and dipole cut) that extend the previously published analysis to a specialized ARIANNA station with 8 antenna channels, which is double the number used in the prior analysis. For a standard trigger with a threshold signal to noise ratio at 4.4, the new cuts produce a neutrino efficiency of > 95% per station-year of operation, while rejecting 99.93% of the background (corresponding to 53 remaining experimental background events). When the new cuts are combined with a previously developed cut using neutrino waveform templates, all background is removed at no change of efficiency. In addition, the neutrino efficiency is extrapolated to 1,000 station-years of operation, obtaining 91%. This work then introduces a new selection method (the deep learning cut) to augment the identification of neutrino events by using deep learning methods and compares the efficiency to the physics-based analysis. The deep learning cut gives 99% signal efficiency per station-year of operation while rejecting 99.997% of the background (corresponding to 2 remaining experimental background events), which are subsequently removed by the waveform template cut at no significant change in efficiency. Here the results of the deep learning cut were verified using measured cosmic rays which shows that the simulations do not introduce artifacts with respect to experimental data. The paper demonstrates that the background rejection and signal efficiency of near surface antennas meets the requirements of a large scale future array, as considered in baseline design of the radio component of IceCube-Gen2.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A Viable New Strategy for the Discovery of Peptide Proteolytic Cleavage Products in Plant-Microbe Interactions

Small peptides that are proteolytic cleavage products (PCPs) of less than 100 amino acids are emerging as key signaling molecules that mediate cell-to-cell communication and biological processes that occur between and within plants, fungi, and bacteria. Yet, the discovery and characterization of these molecules is largely overlooked. Today, selective enrichment and subsequent characterization by mass spectrometry–based sequencing offers the greatest potential for their comprehensive characterization, however qualitative and quantitative performance metrics are rarely captured. Herein, we addressed this need by benchmarking the performance of an enrichment strategy, optimized specifically for small PCPs, using state-of-the-art de novo–assisted peptide sequencing. As a case study, we implemented this approach to identify PCPs from different root and foliar tissues of the hybrid poplar Populus × canescens 717-1B4 in interaction with the ectomycorrhizal basidiomycete Laccaria bicolor . In total, we identified 1,660 and 2,870 Populus and L. bicolor unique PCPs, respectively. Qualitative results supported the identification of well-known PCPs, like the mature form of the photosystem II complex 5-kDa protein (approximately 3 kDa). A total of 157 PCPs were determined to be significantly more abundant in root tips with established ectomycorrhiza when compared with root tips without established ectomycorrhiza and extramatrical mycelium of L. bicolor . These PCPs mapped to 64 Populus proteins and 69 L. bicolor proteins in our database, with several of them previously implicated in biologically relevant associations between plant and fungus.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Aggregated DER_A Model Parameterization via Online Moving Horizon Estimation

Here, this paper introduces a methodology for parameterizing the DER_A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The methodology employs an online parameterization process that can operate in real-time. The model parameterization process is structured into five sequential steps, each targeting a specific aspect of the DER_A model through moving horizon estimation. This approach adapts to systems with varying voltage and frequency support requirements by selectively applying each step. Simulation results on systems with both known and unknown parameters validate the methodology’s effectiveness. The online moving horizon estimation technique accurately captures the dynamics of the overall system and ensures that the parameterized DER_A model closely mirrors the real system’s voltage, current, and power dynamics. The findings highlight the potential of this methodology to substantially improve and simplify the dynamic modeling of power systems, paving the way for more reliable and robust IBG and grid integration.

42 ENGINEERING↗

DOE OSTI2021

Uncertainty Visualization for Renewable Energy Potential

In this paper, we present the reV (Renewable Energy Potential) Dashboard, an interactive browser-based tool for uncertainty visualization and data exploration built using customized plotly dash components. With continuing development and utilization of computational models to study the power sector there is an increasing need for data-driven visualization tools which allow scientists, researchers, and engineers to interact with their data in real-time. Our principle motivation for developing this interactive uncertainty visualization was to provide domain scientists and modelers a platform which allows them to better understand and communicate scientific findings stemming from intricate information encoded in their data that is otherwise difficult to capture by conventional analysis. The development of customized dashboard components using the React programming paradigm, combined with fully pre-processed data, allows for users to select a variety of data options to update and manipulate the visualization in a straightforward computationally efficient manner.

dashboard↗

DOE OSTI2025

Development of Hydrogen Burner for FT4000® Aeroderivative Engine - Final Report

This report details an effort to develop a retrofittable fuel/air injector for the FT4000® aeroderivative gas turbine that enables use of hydrogen as a carbon-free fuel for efficient power generation. The FT4000 engine’s low-NOx combustor was developed by Pratt & Whitney and RTX Technology Research Center with core technology from the Pratt & Whitney PW4000 turbofan aircraft engine. The current FT4000 production engine operates on either natural gas or No. 2 fuel oil with water injection to achieve high thermal efficiency and low emissions. This engine is fielded by Mitsubishi Power Aero and delivers 70 MW of power with a simple-cycle efficiency of over 41% when operating with wet compression. The work reported here advances the technology readiness level of the FT4000 combustor for operation with hydrogen, starting with an experimental assessment of the current production hardware with increasing hydrogen content mixed with natural gas and ending with improved nozzle concepts for fully robust operation with 100% hydrogen. High-pressure single-sector combustor rig tests have been completed, demonstrating the ability for the dual fuel nozzle to operate an FT4000 combustor on 100% hydrogen with low nitrogen oxide (NOx) emissions. Metal temperature measurements and video images of the flame structure from zero to 100% hydrogen highlight opportunities to improve the fuel nozzle robustness for high hydrogen conditions. The design of new fuel/air mixer concepts to improve durability and operability with high hydrogen levels was also completed. A total of eleven new concepts were developed and analyzed, ranging from modifications to the bill-of-materials nozzle to fully clean sheet designs. The concepts were evaluated with non-reacting and reacting flow evaluations to assess the performance of the new hardware designs. Non-reacting tests included Phase Doppler Particle Analysis (PDPA) for droplet size and velocity, mechanical patternation for liquid water flux, and planar laser induced fluorescence (PLIF) with acetone-seeding for gaseous fuel/air mixing characterization. Five scaled candidate fuel nozzle designs, in addition to a scaled bill-of-materials nozzle, were then successfully evaluated in an atmospheric pressure burner rig. The nozzles were evaluated for performance with natural gas, hydrogen/natural gas blends, and pure hydrogen. For 100% hydrogen, the nozzles were evaluated with and without water injection. Optical and infrared imaging of the flame and fuel nozzle was captured. NOx emissions were sampled from fixed emissions probes. The results show measurable differences between the various designs, and the data was used to down-select the two most promising designs to advance to future full pressure rig testing. Results from this study have cleared the current production FT4000 engines with dual fuel nozzles to operate at baseload power on blends of hydrogen mixed with natural gas and water. Two promising nozzle designs have been developed to enable fully robust operation with up to 100% hydrogen. These nozzles require validation at full baseload operating conditions before they can be introduced to the field.

03 NATURAL GAS↗

DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

Lindsey, Jack W. (ORCID:0000000309307327)↗

DOE OSTI2022

Data Catalog Project - A Browsable, Searchable, Metadata System

Modern experiments are typically conducted by large, extended, where researchers rely on other team members to produce much of the data they use. The experiments record very large numbers of measurements which can be difficult for users to find, access and understand. We are developing a system for users to annotate their data products with structured metadata, providing data consumers with a discoverable, browsable data index. Machine understandable metadata captures the underlying semantics of the recorded data, which can then be consumed by both programs, and interactively by users. Collaborators can use these metadata to select and understand recorded measurements.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS1984

Origin of the Moon

The similarities in siderophile abundances strongly suggest that the Moon was derived from the Earth's mantle after the Earth's core had formed. The energy required to remove material from the Earth's mantle and place it into geocentric orbit can be supplied most readily by impact processes during accretion of the Earth. Impacts of late-accreting, high-velocity planetismals would evaporate many times their masses of mantle material. These gases would be accompanied by a massive spray of shock-melted silicate droplets. It is suggested that the gases produced from such near-equatorial impacts were rapidly spun out into equatorial geocentric orbit. The evaporated material was selectively recondensed, and, accompanied by the shock melted, devolatilized silicate droplets, accreted to form a sediment ring of Earth-orbiting planetismals. This sediment ring also captured a significant proportion of Earth-bound planetismals. The Moon was formed by accretion from planetismals comprising the sediment ring.

Ringwood, A. E.↗

NASA NTRS2003

Lunar and Planetary Surface Dynamics and Early History

This document, submitted as part of this proposal renewal represents the Final Report required by NASA for Grant NAGS-9442. It should be emphasized that, while this work statement in the original proposal outlined anticipated directions of our research, the specific activities we carried out during this period differed slightly from those proposed, capitalizing on new unexpected results and new advances in analytical capability. The thrust of all the work we completed were completely within the stated research goals of the proposal and significantly advanced our knowledge of planetary processes and our understanding of the early solar system. The following summary outlines our achievements in the different areas of research. These include: A) Early solar system processes and time scales using I-Xe chronometry; B) The Active Capture of Volatiles: A new mechanism for the capture of heavy noble gases, possible implications for phase Q and planetary heavy noble gases; C) Separation of Xe-L from Xe-H: Physically selective experiments; D) Abundances of Presolar grains; E) Studies of Neon and Helium from single interstellar SiC and graphite grains; F) Pre-compaction exposure of meteoritic grains and chondrules; G) Geochemically Measured Half-Lives: Double beta-decay of Te and Ba isotopes; H) Noble gases in stratospheric interplanetary dust particles; I) New Analytical Instrument.

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