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DOE OSTI2020

Failure investigation of nuclear grade POCO graphite target in high energy neutrino physics through numerical simulation

In many high energy physics neutrino beamlines, targets are made up of isotropic POCO graphite grade for production of neutrinos for high energy particle physics research and are bombarded with highly energetic pulsed proton beam. The pulsed proton beam with a small beam size creates thermal stress waves as well as radiation damage such as displacement damage, void formation, swelling, and gas formation amongst others. As a result, after a few years of operation one of the longest operated targets appears to have undergone bulk swelling and fractured along the beam centerline. A complex interaction of dynamic loading due to beam, material degradation due to irradiation are thought to have caused such a failure. Here, we present a numerical simulation to capture the combined effects of swelling and the dynamic effect of thermal stress waves due to beam heating, to explain the failure of target. An empirical formula has been developed to take into account swelling as a function of temperature and proton fluence and has been implemented in a commercial finite element code. Extensive X-ray diffraction (XRD) were performed on graphite samples from the failed target to understand the lattice parameter changes due to irradiation and build a valid empirical model. Simulation results show that swelling plays a major role in elevating the stress state in the material exceeding the failure strength while the pulsed beam heating also introduces fatigue loading that would explain brittle fracture emanating from inside of the material and propagating outward. Such empirical formulations will help in identifying the threshold values of critical parameters to extend the service life of future multi-megawatt neutrino targets and targets in other accelerator environments.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Seasonal Patterns in Mobile Colistin Resistance Gene Variants in Wastewater Bioaerosols and Liquid Sludge

To address the growing threat of global antimicrobial resistance, a one-health approach is needed to understand the complex socioecological cycling of antibiotic resistance genes. In this study, a metagenomics approach using DNA shotgun sequencing, metagenome assembly, and antibiotic resistance gene (ARG) annotation was used to examine seasonal patterns in the abundance of mobile colistin resistance (mcr) gene variants in bioaerosols and liquid sludge in three wastewater treatment plants (WWTPs). ARGs represented 0.2–0.8 and 0.1–0.2% of the bioaerosol and liquid sludge metagenomes, respectively, while mcr genes represented 0–0.3 and 0–0.5% of the identified ARGs in bioaerosol and liquid sludge metagenomes. Seven of the ten known mcr variants were detected in wastewater bioaerosol and liquid samples, with mcr-5 and mcr-8 being the most prevalent across all seasons and sites. Furthermore, additional functional and taxonomic annotation of mcr-containing metagenomic contigs showed that mcr genes were often located on contigs with other co-occurring ARGs and mobile genetic elements and may be harbored by opportunistic human pathogens and other bacterial taxa not previously associated with mcr genes. Atmospheric dispersion modeling showed that mcr-containing bioaerosols can be transported kilometers away from the WWTPs, resulting in the possible dissemination of these ARGs into surrounding environments and communities.

Antimicrobial agents↗

DOE OSTI2022

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗

DOE OSTI2023

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗

DOE OSTI2020

Estimation of Respirable Aerosol Release Fractions through Stress Corrosion Crack-Like Geometries

The formation of a stress corrosion crack (SCC) in the canister wall of a dry cask storage system (DCSS) has been identified as a potential issue for the long-term storage of spent nuclear fuel. The presence of an SCC in a storage system could represent a through-wall flow path from the canister interior to the environment. Modern, vertical DCSSs are of particular interest due to the significant backfill pressurization of the canister, up to approximately 800 kPa. This pressure differential offers a relatively high driving potential for blowdown of any particulates that might be present in the canister. In this study, the carrier gas flow rates and aerosol transmission properties were evaluated for an engineered microchannel with characteristic dimensions similar to those of an SCC. The microchannel was formed by mating two gage blocks with a slot orifice measuring 28.9 μm (0.0011 in.) tall by 12.7 mm (0.500 in.) wide by 8.86 mm (0.349 in.) long (flow length). Surrogate aerosols of cerium oxide, Ce0 2 , were seeded and mixed inside a pressurized tank. The aerosol characteristics were measured immediately upstream and downstream of the simulated SCC at elevated and ambient pressures, respectively. These data sets are intended to demonstrate a new capability to characterize SCCs under well-controlled boundary conditions. Separate modeling efforts are also underway that will be validated using these data. The test apparatus and procedures developed in this study can be easily modified for the evaluation of more complex SCC-like geometries including laboratory-grown SCC samples.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Leveraging design of experiments to build chemometric models for the quantification of uranium (VI) and HNO3 by Raman spectroscopy

Partial least squares regression (PLSR) and support vector regression (SVR) models were optimized for the quantification of U(VI) (10–320 g L −1 ) and HNO 3 (0.6–6 M) by Raman spectroscopy with optimized calibration sets chosen by optimal design of experiments. The designed approach effectively minimized the number of samples in the calibration set for PLSR and SVR by selecting sample concentrations with a quadratic process model, despite complex confounding and covarying spectral features in the spectra. The top PLS2 model resulted in percent root mean square errors of prediction for U(VI), HNO 3 , and NO 3 − of 3.7%, 3.6%, and 2.9%, respectively. PLS1 models performed similarly despite modeling an analyte with a majority linear response (i.e., uranyl symmetric stretch) and another with more covarying vibrational modes (i.e., HNO 3 ). Partial least squares (PLS) model loadings and regression coefficients were evaluated to better understand the relationship between weaker Raman bands and covarying spectral features. Support vector machine models outperformed PLS1 models, resulting in percent root mean square error of prediction values for U(VI) and HNO 3 of 1.5% and 3.1%, respectively. The optimal nonlinear SVR model was trained using a similar number of samples (11) compared with the PLSR model, even though PLS is a linear modeling approach. The generic D-optimal design presented in this work provides a robust statistical framework for selecting training set samples in disparate two-factor systems. This approach reinforces Raman spectroscopy for the quantification of species relevant to the nuclear fuel cycle and provides a robust chemometric modeling approach to bolster online monitoring in challenging process environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Geochemistry and Microbiology Predict Environmental Niches with Conditions Favoring Potential Microbial Activity in the Bakken Shale

The Bakken Shale and underlying Three Forks Formation is an important oil and gas reservoir in the United States. The hydrocarbon resources in this region are accessible using unconventional oil and gas extraction methods, including horizontal drilling and hydraulic fracturing. However, the geochemistry and microbiology of this region are not well understood, although they are known to have major implications for productivity and water management. In this study, we analyzed the produced water from 14 unconventional wells in the Bakken Shale using geochemical measurements, quantitative PCR (qPCR), and 16S rRNA gene sequencing with the overall goal of understanding the complex dynamics present in hydraulically fractured wells. Bakken Shale produced waters from this study exhibit high measurements of total dissolved solids (TDS). These conditions inhibit microbial growth, such that all samples had low microbial loads except for one sample (well 11), which had higher 16S rRNA gene copies. Our produced water samples had elevated chloride concentrations typical of other Bakken waters. However, they also contained a sulfate concentration trend that suggested higher occurrence of sulfate reduction, especially in wells 11 and 18. The unique geochemistry and microbial loads recorded for wells 11 and 18 suggest that the heterogeneous nature of the producing formation can provide environmental niches with conditions conducive for microbial growth. This was supported by strong correlations between the produced water microbial community and the associated geochemical parameters including sodium, chloride, and sulfate concentrations. The produced water microbial community was dominated by 19 bacterial families, all of which have previously been associated with hydrocarbon-reservoirs. These families include Halanaerobiaceae, Pseudomonadaceae, and Desulfohalobiaceae which are often associated with thiosulfate reduction, biofilm production, and sulfate reduction, respectively. Notably, well 11 was dominated by sulfate reducers. Our findings expand the current understanding of microbial life in oil and gas related environments, provide new insights into how the unique produced water conditions shape microbial communities, and demonstrate thatproduced water chemistry is tightly linked with microbiota in the Bakken Shale. Finally, our study shows that additional research efforts are necessary to understand this ecosystem and highlights the need for work in other unconventional reservoirs.

Tinker, Kara↗

DOE OSTI2024

The Scientific Case for Concurrent Neutron and X-ray Scattering and Spectroscopy

The interrogation of materials with X-rays or neutrons to determine the structure, energetics, and dynamics of materials is fundamental to advancing materials' physical and chemical science and developing innovative material technologies. A transcending challenge in developing novel materials is that progress hinges on understanding the structure and dynamics across multiple time and length scales in complex materials that feature multiple components, interfaces, and compositions. Despite the ever-growing demands on materials’ characterization, existing approaches are almost exclusively based on isolated X-ray or neutron scattering, i.e., an approach commensurate with the more narrowly defined needs of fifty years ago. A three-day workshop sponsored by the U.S. National Science Foundation (NSF) analyzed the demand for concurrent neutron and X-ray (NeX) experiments. It was held at the Spring Hill Suites, San Jose, California, from June 2 to 4, 2022. In this workshop, 70 national and international experts ascertained the crucial need to establish NeX capabilities to advance the science of complex materials and systems in the US. Here, we illustrate the need for NeX scattering and spectroscopy experiments by showcasing examples that span areas as diverse as biomaterials, energy science, soft matter, and nanomaterials. To provide NeX capability will require new instrumentation that enables concurrent experiments. Affected areas include chemistry, soft matter, quantum materials, pure and applied chemistry, bioscience, geoscience, and applied materials. NeX benefits research outcomes due to the complementarity of the two techniques, which is essential for better model refinement. While joint refinement of data from separate neutron and X-ray experiments is critical to avoid ambiguities, especially in multiphase-multicomponent materials, concurrent experiments overcome scientific and technical barriers associated with single measurements, separated by location and, thus, time. Among all the examples, these factors introduce uncertainties in the results that complicate data analysis. [1,2] [3] While models are strongly sample-dependent, the principles of joint refinement are generally applicable to these disciplines, including the development of advanced parameterization, modeling, and analysis techniques that also consider the temporal and spatial resolutions of the two methods, leading to unambiguous data interpretation. Solutions for technical barriers must be found to realize NeX experiments, including developing robust sample environments that meet the optical requirements of neutrons and X-rays.

36 MATERIALS SCIENCE↗

DOE OSTI2025

SAGAbg. III. Environmental Stellar Mass Functions, Self-quenching, and the Stellar-to-halo Mass Relation in the Dwarf Galaxy Regime

Recent efforts have extended our view of the number and properties of satellite galaxies beyond the Local Group firmly down to M ⋆ ∼ 10 6 M ⊙ . A similarly complete view of the field dwarf population has lagged behind. Using the background galaxy sample from the Satellites Around Galactic Analogs (SAGA) survey at z < 0.05, we take inventory of the dwarf population down to M ⋆ ∼ 5 × 10 6 M ⊙ using three metrics: the stellar mass function (SMF) as a function of environment, the stellar-to-halo mass relation (SHMR) of dwarf galaxies inferred via abundance matching, and the quenched fraction of highly isolated dwarfs. We find that the low-mass SMF shape shows minimal environmental dependence, with the field dwarf SMF described by a low-mass power-law index of α 1 = −1.44 ± 0.09 down to M ⋆ ∼ 5 × 10 6 M ⊙ , and that the quenched fraction of isolated dwarfs drops monotonically to f q ∼ 10 −3 at M ⋆ ∼ 10 8.5 M ⊙ . Though slightly steeper than estimates from H I kinematic measures, our inferred SHMR agrees with literature measurements of satellite systems, consistent with minimal environmental dependence of the SHMR in the probed mass range. Finally, although most contemporary cosmological simulations against which we compare accurately predict the SAGAbg-SMF SHMR, we find that big-box cosmological simulations largely overpredict isolated galaxy quenched fractions via a turnaround in f q (M ⋆ ) at 10 8 ≲ M ⋆ /M ⊙ ≲ 10 9 , underscoring the complexities in disentangling the drivers of galaxy formation and the need for systematic multidimensional observations of the dwarf population across environments.

Kado-Fong, Erin [Yale Univ., New Haven, CT (United↗

DOE OSTI2025

Ultra-high Information-content Chemical Imaging with Broadband Coherent Anti-Stokes Raman and Two-photon Fluorescence Lifetime Microscopy

Raman fingerprint spectroscopy and fluorescence lifetime imaging are emerging tools for studying metabolic profiles of biological specimens. While Raman fingerprint spectroscopy detects intrinsic molecular vibrations that reflect the molecular composition and chemical environment of a sample, fluorescence lifetime imaging measures changes in the excited-state lifetime of fluorophores that are sensitive to their microenvironments. Here, we present a multimodal imaging platform combining broadband coherent anti-Stokes Raman scattering (BCARS) and two-photon fluorescence lifetime imaging (2p-FLIM) microscopy that can acquire biologically relevant Raman fingerprint spectra and fluorescence lifetime signals in vivo and simultaneously. The tremendous chemical information obtained from spatially co-registered BCARS and 2p-FLIM images allows us to characterize the subtle differences between sub-cellular compartments and verify the potential false-positive results generated by fluorescence imaging alone. This is demonstrated by directly comparing the BCARS, 2p-FLIM, and two-photon excitation fluorescence(TPEF) signals simultaneously obtained from the same dye-stained organelle in the live, intact C. elegans expressing a green fluorescent protein (GFP) marker. In this work, we introduce the BCARS/2p-FLIM/TPEF setup scheme, the image acquisition steps, data processing, and representative results showing that the cross-modality imaging method enables rigorous characterization and in vivo detection at sub-cellular resolution. Furthermore, this protocol provides a framework for simultaneous chemical and fluorescence lifetime imaging to improve the accuracy of biological interpretation in complex living systems.

Xu, Haoyu [Georgia Institute of Technology, Atlant↗

DOE OSTI2020

Characteristics of the Diffuse Astrophysical Electron and Tau Neutrino Flux with Six Years of IceCube High Energy Cascade Data

In this work, we report on the first measurement of the astrophysical neutrino flux using particle showers (cascades) in IceCube data from 2010-2015. Assuming standard oscillations, the astrophysical neutrinos in this dedicated cascade sample are dominated (~90%) by electron and tau flavors. The flux, observed in the sensitive energy range from 16 TeV to 2.6 PeV, is consistent with a single power-law model as expected from Fermi-type acceleration of high energy particles at astrophysical sources. We find the flux spectral index to be γ=2.53±0.07 and a flux normalization for each neutrino flavor of $\phi$ astro =1.66$_{-0.27}^{+0.25}$ at E 0 =100 TeV, in agreement with IceCube's complementary muon neutrino results and with all-neutrino flavor fit results. In the measured energy range we reject spectral indices γ≤2.28 at ≥3σ significance level. Because of high neutrino energy resolution and low atmospheric neutrino backgrounds, this analysis provides the most detailed characterization of the neutrino flux at energies below ~100 TeV compared to previous IceCube results. Results from fits assuming more complex neutrino flux models suggest a flux softening at high energies and a flux hardening at low energies (p value ≥0.06). The sizable and smooth flux measured below ~100 TeV remains a puzzle. In order to not violate the isotropic diffuse gamma-ray background as measured by the Fermi Large Area Telescope, it suggests the existence of astrophysical neutrino sources characterized by dense environments which are opaque to gamma rays.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

SIT 45: An interacting, compact, and star-forming isolated galaxy triplet

The underlying scenario of the formation and evolution of galaxy triplets is still uncertain. Mergers of galaxies in isolated triplets give us the opportunity to study the already complex merging process, with minimal contamination of other environmental effects that potentially allow and accelerate galaxy transitions from active star-forming to passive galaxies. The merging system SIT 45 (UGC 12589) is one of 315 systems in the SDSS-based catalogue of Isolated Triplets (SIT); it is an unusual isolated galaxy triplet, consisting of three merging late-type galaxies. The main aims of this work are to study the dynamical evolution and star formation history (SFH) of SIT 45, as well as its dependence on its local and large-scale environment. Methods. To study its dynamics, parameters such as the velocity dispersion (σ v ), the harmonic radius (R H ), the crossing time (H 0 t c ), and the virial mass (M vir ), along with the compactness of the triplet (S) were considered. To investigate the possible dependence of these dynamical parameters on the environment, the tidal force Q parameters (both local and large-scale) and the projected local density (η k ) were used. To constrain the SFH, we used CIGALE to fit its observed spectral energy distribution using multiwavelength data from the ultraviolet to the infrared. SIT 45 is one of the most compact triplets in the SIT, and it is also more compact than triplets in other samples. According to its SFH, SIT 45 presents star formation, where the galaxies also present recent (~200 Myr) star formation increase, indicating that this activity may have been triggered by the interaction. Its dynamical configuration suggests that the system is highly evolved in comparison to the SIT. However, this is not expected for systems composed of star-forming late-type galaxies, based on observations in compact groups. We conclude that SIT 45 is a system of three interacting galaxies that are evolving within the same dark matter halo; its compact configuration is a consequence of the ongoing interaction rather than being due to a long-term evolution (as suggested from its H 0 t c value). We consider two scenarios for the present configuration of the triplet, one where one of the members is a tidal galaxy, and another where this galaxy arrives to the system after the interaction. Both scenarios need further exploration. The isolated triplet SIT 45 is therefore an ideal system to study short timescale mechanisms (~10 8 yr), such as starbursts triggered by interactions which are more frequent at higher redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

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 OSTI2026

Simultaneous Determination of Halogens and Metals in Waste Plastic Pyrolysis Oil by Inductively Coupled Plasma Mass Spectrometry

A major barrier to integrating pyrolysis-derived oil into conventional refinery technology is the presence of impurities, particularly halogens and metals, that can deactivate catalysts. This study presents a novel, cost-effective approach for the simultaneous analysis of a subset of halogens, metals, nonmetals, and metalloids in complex, industrially relevant distilled pyrolysis oil samples, this was previously achievable only through multiple techniques. Excellent results were obtained using a widely accessible inductively coupled plasma mass spectrometry (ICP-MS) method with helium gas mode and standard laboratory consumables, enabling high-throughput analysis and efficient evaluation of adsorbent performance. Sample preparation is straightforward, requiring only dilution in a compatible matrix, and provides accurate and precise quantification, with 75%–137% spike recovery for Be, Ti, V, Cr, Fe, Ni, Co, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, and 62%–65% spike recovery for Cl and 109%–133% spike recovery for Br. Additionally, an enhanced version of the method using ICP-MS/MS and hydrogen gas is described, which has higher accuracy with 69%–112% spike recovery for Be, B, Ti, V, Fe, Co, Ni, Cu, As, Se, Mo, Cd, Sb, Tl, and Pb, with 85%–102% spike recovery for Cl and 63%–93% spike recovery for Br. Helium mode detection limits for industrially relevant elements (V, Fe, Ni, Cu, As, and Pb) are less than 1.7 µg/kg, and less than 0.2 mg/kg for Br and Cl. Furthermore, this methodology facilitates rapid systematic evaluation of adsorption capacities of materials under time-on-stream conditions and supports robust comparisons across diverse operating environments.

Lazarcik, James [University of Wisconsin-Madison, ↗

DOE OSTI2020

Iron Speciation in PM 2.5 From Urban, Agriculture, and Mixed Environments in Colorado, USA

Atmospheric iron solubility varies depending on whether the particles are collected in rural or urban areas, with urban areas showing increased iron solubility. In this study, we investigate if the iron species present in different environments affects its ultimate solubility. Field data are presented from the Platte River Air Pollution and Photochemistry Experiment (PRAPPE), aimed at understanding the interactions between organic carbon and trace elements in atmospheric particulate matter (PM). 24-hr PM 2.5 samples were collected during the summer and winter (2016–2017), at three different sites on the Eastern Colorado plains: an urban, agricultural, and a mixed site. Downtown Denver had an average total and water-soluble iron air concentration of 181.2 and 7.7 ng m -3 , respectively. Platteville, the mixed site, had an average of total iron of 76.1 ng m -3 , with average water-soluble iron concentration of 9.1 ng m -3 . Jackson State Park (rural/agricultural) had the lowest total iron average of 31.5 ng m -3 and the lowest water-soluble iron average, 1.3 ng m -3 . The iron oxidation state and chemical speciation of 97 samples across all sites and seasons was probed by X-ray absorption near edge structure (XANES) spectroscopy. The most common iron phases observed were almandine (Fe 3 Al 2 Si 3 O 12 ) (Denver 21%, Platteville 16%, Jackson 24%), magnetite (Fe 3 O 4 ) (Denver 9%, Platteville 4%, Jackson 5%) and Fe (III)dextran (Denver 5%, Platteville 13%, Jackson 5%), a surrogate for Fe-organic complexes. Additionally, native iron [Fe(0)] was found in significant amounts at all sites. No correlation was observed between iron solubility and iron oxidation state or chemical speciation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Determining the Solubility Behavior of Kogarkoite in Simulated Nuclear Waste

Kogarkoite (Na 3 FSO 4 ) is a sparingly soluble fluoride–sulfate double salt that has been identified in high level nuclear waste sludge at the Hanford Site and, more recently, in sludge batch compilation samples at the Savannah River Site (SRS). Due to its complex dissolution behavior, which exhibits an inverse dependence on sodium ion activity, the presence of this mineral poses significant challenges to waste retrieval and processing. Incomplete dissolution during sludge washing can lead to the retention of fluoride and sulfate in the high-level waste feed, potentially causing the formation of corrosive, immiscible molten salt layers, known as "glass gall,” in vitrification melters. Current efforts to optimize flowsheet parameters and wash-water volumes are hindered by the absence of a commercially available, certified reference material, which prevents the accurate calibration of analytical methods and the verification of dissolution kinetics. To address this critical gap, this research focuses on the laboratory synthesis of pure Kogarkoite to serve as a standard for comprehensive solubility and washing performance testing. A coupled synthesis and simulant campaign was executed using an evaporative crystallization protocol designed to replicate the dynamic concentration effects observed in tank farm operations. Thirteen simulant matrices were prepared by dissolving systematically varied ratios of sodium fluoride (NaF) and sodium sulfate (Na 2 SO 4 ) in deionized water under three distinct caustic regimes: 0.0 g (control), 4.0 g (~1 M), and 12.0 g (~3 M) sodium hydroxide (NaOH). While thermodynamic equilibrium models suggest that high-caustic environments should favor the stability of the double salt7, results from this evaporative study at 25 0 C revealed a distinct kinetic divergence. Simulants with high hydroxide loading predominantly yielded large, blocky crystals of sodium sulfate decahydrate (Na 2 SO 4 .10H 2 O). Successful synthesis of pure Kogarkoite was achieved exclusively in specific NaOH-free compositional windows, where the precipitate manifested as fine, opaque granular aggregates. Ion chromatography (IC) analysis confirmed phase purity through the simultaneous stoichiometric depletion of both fluoride and sulfate from the supernatant. This successful synthesis establishes a reproducible route to generate bulk Kogarkoite, enabling the subsequent phase of quantitative dissolution testing using inhibited water to optimize sludge-batch assembly.

Sarker, Md Sharif [Florida International Univ. (FI↗

DOE OSTI2022

Alternating chempolishing and electropolishing for interior and exterior surface finishing of additively manufactured (AM) metal components

Additively manufactured (AM) components’ surface finishing is crucial in adopting them for intended applications in challenging environments involving fatigue, corrosion, high temperature, and nuclear radiation. In our prior research, chempolishing (C) was utilized as an electroless etching process that uniformly smoothens complex AM components’ accessible interior and exterior surfaces (Tyagi et al. Additive Manufacturing, 25:32–38, 22). A wide range of electropolishing (E) has been demonstrated for AM surface finishing. However, electropolishing can impact a surface that can be juxtaposed to counter electrode and can yield a very smooth surface to sub-micrometer level roughness. However, a knowledge gap exists about the impact of applying both approaches on the same surface one after another and what new advantages may arise because of combining two methods. This paper uses dual-stage liquid-based surface finishing strategies produced by alternating the chempolishing (C) and electropolishing (E) steps. Two dual-stage surface finishing approaches, i.e., chempolishing followed by electropolishing (CE) and electropolishing followed by chempolishing (EC), were performed on the 316 stainless AM steel component. Impacts of EC and CE approaches were compared with single-stage C and E surface finishing approaches. An optical microscope and mechanical profilometer were utilized to investigate the wide range of surface roughness parameters. CE and EC produced Ra ~ 1.4 µm and ~ 1.6 µm, respectively. Surface roughness on CE- and EC-treated AM samples was lower than those individually treated by C and E approaches. Scanning electron microscopy provided further insights into the microstructural difference between CE- and EC-treated AM samples. This paper reports a liquid contact angle study on CE- and EC-treated AM samples to provide insights into the relative difference in surface energy that is crucial for making coatings on AM parts. A spectroscopic reflectance study was also employed to register the difference in physical properties of AM components treated with CE and EC approaches. Further, this study reveals industrially practicable interior and exterior surface finishing approaches for complex AM metal components that require minimum tooling and real-time process monitoring.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Root Pulling Force Across Drought in Maize Reveals Genotype by Environment Interactions and Candidate Genes

High-throughput, field-based characterization of root systems for hundreds of genotypes in thousands of plots is necessary for breeding and identifying loci underlying variation in root traits and their plasticity. We designed a large-scale sampling of root pulling force, the vertical force required to extract the root system from the soil, in a maize diversity panel under differing irrigation levels for two growing seasons. We then characterized the root system architecture of the extracted root crowns. We found consistent patterns of phenotypic plasticity for root pulling force for a subset of genotypes under differential irrigation, suggesting that root plasticity is predictable. Using genome-wide association analysis, we identified 54 SNPs as statistically significant for six independent root pulling force measurements across two irrigation levels and four developmental timepoints. For every significant GWAS SNP for any trait in any treatment and timepoint we conducted post hoc tests for genotype-by-environment interaction, using a mixed model ANOVA. We found that 8 of the 54 SNPs showed significant GxE. Candidate genes underlying variation in root pulling force included those involved in nutrient transport. Although they are often treated separately, variation in the ability of plant roots to sense and respond to variation in environmental resources including water and nutrients may be linked by the genes and pathways underlying this variation. While functional validation of the identified genes is needed, our results expand the current knowledge of root phenotypic plasticity at the whole plant and gene levels, and further elucidate the complex genetic architecture of maize root systems.

Woods, Patrick↗