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DOE OSTI2022

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

58 GEOSCIENCES↗

DOE OSTI2024

Reaction Pathways and Energy Consumption in NH 3 Decomposition for H 2 Production by Low Temperature, Atmospheric Pressure Plasma

Pathways for NH 3 decomposition to N 2 and N 2 H 4 by atmospheric pressure nonthermal plasma are analyzed using a combination of molecular beam mass spectrometry measurements and zero-dimensional kinetic modeling. Experimental measurements show that NH 3 conversion and selectivity towards N 2 formation scale monotonically with the specific energy input into the plasma with ~ 100% selectivity to N 2 formation achieved at specific energy inputs above 0.12 J cm −3 (3.1 eV (molecule NH 3 ) −1 ). The kinetic model recovers these trends, although it underpredicts N 2 selectivity at low specific energy input. These discrepancies can be explained by the underestimation of reaction rate coefficients for reactions that consume N 2 H x species in collisions with H radicals and/or radial nonuniformities in power deposition, gas temperature, and species concentrations that are not represented by the plug flow approximation used in the model. The kinetic model shows that N 2 formation proceeds through N 2 H x decomposition pathways rather than NH x decomposition pathways in low temperature, atmospheric pressure plasma. Higher selectivity toward N 2 production can be achieved by operating at higher NH 3 conversion and with a higher gas temperature. Furthermore, the high energy cost of NH 3 decomposition by atmospheric pressure nonthermal plasma found in this work (25–50 eV (molecule NH 3 converted) −1 ; 17–33 eV (molecule H 2 formed) −1 ) is a result of the energy requirement for electron-impact dissociation of NH 3 and the significant re-formation of NH 3 by three-body recombination reactions between NH 2 and H.

Nonthermal plasma↗

DOE OSTI2022

Electro-Optical Characterization of Arsenic-Doped CdSeTe and CdTe Solar Cell Absorbers Doped in-situ During Close Space Sublimation

Most contemporary device models predict that an acceptor concentration of at least 10^16 cm^-3 is required to reach an open circuit voltage of 1 V in polycrystalline CdTe-based solar cells. While copper has traditionally been used as the de facto p-type dopant in polycrystalline cadmium telluride (CdTe) and cadmium selenide telluride (CdSeTe), reaching high acceptor concentrations has proved to be challenging in such devices due to significant dopant compensation. The acceptor concentration in copper-doped CdTe and CdSeTe typically ranges from 10^13 to 10^15 cm^-3 and routinely exhibit low external radiative efficiencies below 0.01%, limiting their implied voltage (i.e., quasi-Fermi level splitting) to approximately 900 mV. As an alternative to copper, this work explores the use of arsenic as a p-type dopant for CdTe and CdSeTe. Using a novel technique in which a thin layer of arsenic-containing material is deposited and used as a reservoir for arsenic to diffuse into a front layer of previously undoped material, this contribution demonstrates that high external radiative efficiencies are achievable, a direct result of combined high acceptor concentrations and long minority-carrier lifetimes in the absorber. This leads to improved implied voltages, and indicates that As-doping represents a promising pathway towards improving the external voltage of CdSeTe/CdTe solar cells.

cadmium telluride↗

DOE OSTI2026

Pathways to cost competitive and viable lithium production from Salton Sea geothermal brines

Lithium supply chains remain heavily concentrated in hard rock and brine resources, creating significant supply risks. Geothermal brines represent an underutilized alternative, yet commercial progress is hindered by the absence of facility-scale cost assessments. Here, we present a techno-economic analysis of large-scale lithium extraction from Salton Sea geothermal brines, drawing on primary company disclosures, process patents, and brine resource modeling. Caused by varying lithium and impurity concentrations, brine dilution over time, and process configurations (e.g., production via carbonation and conversion vs. electrolysis), we find that large-scale production costs may reach ~10,000 United States dollars per ton, but increase up to 22,000 United States dollars per ton with higher certainty of brine modeling, raising concerns about economic competitiveness to conventional low-cost sources. Finally, a project feasibility-focused scenario analyses shows that leveraging brine pre-treatment by-product sales could lower long-term lithium break-even prices by ~5,000 United States dollars per ton, whereas capital cost optimization of 20% could further reduce lithium break-even prices by 10%.

Wesselkaemper, Jannis↗

DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Iodine Air Sampling: Installation and Preliminary Results

The F-Area wetlands are a known sink for radioiodine generated at the Savannah River Site (SRS). Wastewater containing iodine-129 ( 129 I) was discharged into the F-Area Seepage Basins for disposal, but the acidity of the wastewater mobilized some of the contaminants from the basin soil through the vadose zone and into the groundwater; ultimately creating a groundwater plume that extends towards Fourmile Branch and its associated wetland areas. Dissolved radioiodine specifically has migrated to the nearby F-Area wetlands, where it persists as a contaminant of concern. Accumulation and resurfacing of 129 I in the wetlands and nearby areas creates a potential secondary source zone where changes in biogeochemical conditions could result in the release of this sequestered 129 I to the air. Monitoring data has indicated that 129 I has a seasonal behavior at several surface water stations, with high concentrations during summertime and low concentrations during wintertime. Still, it is not known which factors control the seasonal behavior of 129 I. Further, it has been reported that 129 I contributed approximately 23% to the 2019 SRS offsite air pathway dose to the representative person for that year (SRNS, 2020), but air measurements of 129 I have never been taken in the F-Area wetlands. Because air emissions of 129 I from the wetlands have never been investigated, it is not known if this could be a potential release pathway that needs to be included in the site conceptual model. To address these unknowns, the Savannah River National Laboratory (SRNL) has an applied research task to investigate whether 129 I in the wetlands is emitted to the air and, if so, whether air concentrations exhibit seasonal variation. This report presents information about the system recently installed in the F-Area wetlands for measuring 129 I, as well as analysis results for samples collected June through August 2023. Quantification of this constituent will provide a better understanding of the contribution of airborne 129 I from the F-Area wetlands to the offsite dose and better inform ongoing and future remedial actions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Analysis of Brackish Water Desalination for Municipal Uses: Case Studies on Challenges and Opportunities

Brackish water is a widely available, nontraditional water resource that can augment limited freshwater supplies. Although brackish water desalination has been continuously implemented in the United States and worldwide, it is necessary to reduce further its energy consumption, costs, and environmental impacts. This study conducted technoeconomic analyses to evaluate the current desalination and brine management technologies, focusing on the key factors and opportunities for sustainable brackish water desalination for municipal uses. Three case studies were selected as baseline representative of different geographic and operational conditions, including water quality, plant size, pretreatment, desalination, and concentrate management. Here, the technoeconomic analyses and model simulations identified challenges, opportunities, and research priorities to achieve specific pathways for enhanced brackish water desalination regarding levelized costs of water, electricity intensity, water recovery, zero liquid discharge, and brine valorization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Natural and Anthropogenically Influenced Isoprene Oxidation in Southeastern United States and Central Amazon

Anthropogenic emissions alter secondary organic aerosol (SOA) formation chemistry from naturally emitted isoprene. Here, we use correlations of tracers and tracer ratios to provide new perspectives on sulfate, NO x , and particle acidity influencing isoprene-derived SOA in two isoprene-rich forested environments representing clean to polluted conditions-wet and dry seasons in central Amazonia and Southeastern U.S. summer. We used a semivolatile thermal desorption aerosol gas chromatograph (SV-TAG) and filter samplers to measure SOA tracers indicative of isoprene/HO 2 (2-methyltetrols, C5-alkene triols, 2-methyltetrol organosulfates) and isoprene/NO x (2-methylglyceric acid, 2-methylglyceric acid organosulfate) pathways. Summed concentrations of these tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 μg m -3 reduction in sulfate corresponds with at least ~0.5 μg m -3 reduction in isoprene-derived SOA. We also find that isoprene/NO x pathway SOA mass primarily comprises organosulfates, ~97% in the Amazon and ~55% in Southeastern United States. We infer under natural conditions in high isoprene emission regions that preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought of as representative of an anthropogenic influence. We further report the first field observations showing that particle acidity correlates positively with 2-methylglyceric acid partitioning to the gas phase and negatively with the ratio of 2-methyltetrols to C 5 -alkene triols.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. A total of 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO 2 -concentrating mechanism and ciliogenesis. We illustrate the value of this resource by validating phenotypes and gene functions, including three new components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants; mutants in Arabidopsis thaliana genes exhibit phenotypes similar to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

MACCS Theory Manual

This report describes the models of the MACCS computer code as presented in MACCS Version 3.10.0. The purpose of MACCS is to simulate the impact of severe accidents at nuclear power plants on the surrounding environment. MACCS has been developed by Sandia National Laboratories for the U.S. Nuclear Regulatory Commission. From a given release of radioactive material into the atmosphere, MACCS estimates the extent and magnitude of radiological contamination, offsite doses, protective actions, socioeconomic impacts and costs, and health effects. Since the weather at the time of an accident is not predictable, MACCS supports various sampling options to run a representative set of simulations to evaluate weather variability. MACCS simulates atmospheric transport with a straight-line Gaussian plume segment model. From the estimated air and ground concentrations, MACCS models dose projections through several dose exposure pathways. These exposures can be offset by protective actions during the emergency response and long-term recovery of the accident. MACCS users directly specify the evacuation and sheltering area, while other protective actions (e.g., relocation, farmland restrictions, decontamination) are based on user-specified dose or concentration limits. While protective actions help reduce dose accumulation, they also cause social and economic impacts. MACCS models the extent of displaced individuals and land contamination, and the cost of offsite property damage, economic disruptions, and various accident expenditures caused by protective actions. Finally, from the dose accumulation, MACCS estimates early and stochastic health effects according to dose-response models. The purpose of consequence analyses is to be able to understand and estimate the impact of nuclear accidents. Consequence analysis is an essential tool to inform determinations of adequate protection of the public, to understand nuclear power hazards, to measure the value of regulations, and to help us appreciate the importance of nuclear safety. As such, MACCS has a variety of regulatory uses including environmental analyses (10 CFR 51.53, 52.47), regulatory cost-benefit analyses, backfit analyses (10 CFR 50.109), consequence analysis studies such as SOARCA (NUREG-1935), Level 3 PRA studies, and risk-informing of emergency planning (10 CFR 50 App. E and 50.47). This report updates the previous MACCS theory manual (NUREG/CR-4691 Vol. 2; Chanin, Sprung, Ritchie, & Jow, 1990) and accompanies the MACCS User's Guide (SAND-2021-1588) that describes the use and input requirements of the graphical user interface of MACCS known as WinMACCS. The MACCS User's Guide is also a reference guide that describes data input file formats, describes various software components in the MACCS code suite, and provides a set of example tutorials for running WinMACCS. Also, soon to be published is a MACCS input parameter guidance report (NUREG/CR-7270) that provides technical bases for commonly used MACCS input values. This page left blank

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Enhancing CO 2 Mineralization Rate and Extent of Iron and Steel Slag via Grinding

Roughly 10% of the CO 2 emissions from iron and steel making are attributable to the direct release of CO 2 from the thermal decomposition of carbonates to produce flux, mainly CaO, used for impurity removal. Notably, these direct emissions remain even if carbon-based steelmaking is replaced by hydrogen-based steelmaking. After removing impurities from the molten metal, this flux becomes the solid waste product called ‘slag’, a primarily Ca-silicate material. The transformation of slag back into carbonates is thermodynamically spontaneous with negative ΔG in the ambient environment, meaning that ~10% of the CO 2 emissions from iron and steel making could be negated if equipment and methods were developed to support CO 2 mineralization. However, the rate of CO 2 mineralization using slag is slowed by several environmental, geometric, and processing factors. We leverage an experimentally verified model of CO 2 mineralization to determine how to efficiently accelerate the process. Increasing the crystallinity of slag, increasing the relative humidity, and reducing the grain size of slag particles provide the greatest increase in CO 2 mineralization rate at the lowest energy penalty. Increasing the concentration of CO 2 and the temperature provide only modest increases in the CO 2 mineralization rate while incurring a substantial energy penalty. For steelmaking slags, CO 2 mineralization represents low-hanging fruit as the current reuse pathways are low value. For ironmaking slag, replacing the production of amorphous slag for the cement industry with the production of crystalline slag for CO 2 mineralization becomes financially preferable when a carbon price/tax exceeds 67.40 USD/t-CO 2 .

42 ENGINEERING↗

DOE OSTI2026

Breakthrough Zn(II) Catalyst for Direct Air Capture Employing CO 2 Hydration

Direct air capture (DAC) represents a vital technology for atmospheric CO₂ remediation, but few studies have tested catalysts at dilute atmospheric CO₂ concentrations. Inspired by the carbonic anhydrase metalloenzyme, we report a catalytic DAC strategy employing robust zinc(II) enzyme mimics that enable efficient CO₂ sequestration pathways. A catalyst-mediated CO₂ hydration cycle in aqueous sorbents facilitates accelerated capture from dilute atmospheric air, thereby addressing the kinetic limitations observed in carbonate-based systems. Our developed complexes [ZnC1] and [ZnC2] enhance capture rates up to two-fold at millimolar concentrations and improve CO₂ mass transfer by 40-60% in 1 M K₂CO₃ sorbent under ambient conditions. These bench-stable, earth-abundant zinc catalysts operate effectively under dilute CO₂ concentrations, overcoming the kinetic limitations of conventional carbonate-based sorbents. As a result, mechanistic studies support a biomimetic catalytic cycle that facilitates rapid CO₂ conversion, demonstrating that catalyst-assisted DAC can enable energy-efficient, scalable carbon capture technologies.

Atmospheric chemistry↗

DOE OSTI2020

Conceptual Model Update of Mercury Sources and Flux at Y-12 and Upper East Fork Poplar Creek, Oak Ridge,Tennessee

The interactions between the key processes that control the fate and transport of mercury (Hg) in the sediments, groundwater, and stream water within the Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee are complex, and many aspects are not well understood. In contaminated environments such as Y-12, conceptual models are frequently developed to aid in visualizing and understanding the dynamic nature of the hydrologic, geochemical, and physical environment. These conceptual models integrate data in an internally consistent manner to understand processes that control the fate and transport of contaminants. Over the past few decades of environmental investigation at Y-12, a number of conceptual models have been developed to identify and define various technical processes at various scales. The main purpose of the activities described in this report is to update the 2011 conceptual model for Upper East Fork Poplar Creek using the most recent Hg concentration and flux data and informed scientific interpretation. Emphasis was placed on improving the previous model by implementing a more detailed spatial and temporal approach to visualize transport pathways in the watershed and trends in flux and concentration over time, and to compare baseflow and stormflow system dynamics. Detailed descriptions of historical and current Hg sources and transport pathways are also provided for the east and west ends of the facility. This conceptual model will allow the US Department of Energy to evaluate past and present remedial activities and provide a strong technical basis for prioritizing and optimizing remedial responses in a cost-effective and efficient manner. Twenty years ago, Hg flux from Outfall (OF) 200 at the headwaters of East Fork Poplar Creek represented approximately 20% of the overall flux leaving Y-12. By the time of the 2011 conceptual model report, that percentage had increased to 70%–80%. Flux estimates compiled for this report using data from 2009 to 2018 show that OF200 accounted for roughly 60% of the flux leaving Y-12. The relative role of the four storm drain conduits to OF200 appeared similar to 2011, with OF163 being the greatest contributor to downstream flux. An increase in Hg concentrations and flux occurred throughout and downstream of west end storm drains in 2011 in response to a storm drain cleanout. Leading up to the 2011 storm drain cleanout, annual baseflow flux was higher at OF200A6 than at Station 17. From 2011 to 2018, the trend reversed with concentrations and flux being higher at Station 17 than at OF200A6. A spike in concentrations occurred in July 2018, potentially due to a one-time influx of Hg that occurred during COLEX decontamination and decommissioning activities at Y-12. This report includes recommendations for improving our conceptual understanding of Hg sources, transport pathways, and flux at Y-12. Important recommendations include further evaluation of transport pathways, concurrent measurement of Hg concentration and flux under baseflow and stormflow conditions at multiple sites, and research to understand the connections among periphyton and methylmercury concentration, bioavailability, and bioaccumulation. Ongoing facility decontamination and decommissioning efforts, site characterization, remedial actions, and research are facilitating the collection of new Hg data at Y-12. The conceptual model update provided herein takes advantage of the extensive recent Hg sampling to provide an updated assessment of Hg mass balance and support a refined understanding of Hg behavior at or near Y-12. This assessment should assist in future environmental management decisions and in mitigating the impacts of Hg on the surrounding environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Energy, greenhouse gas, and water life cycle analysis of lithium carbonate and lithium hydroxide monohydrate from brine and ore resources and their use in lithium ion battery cathodes and lithium ion batteries

Life cycle analyses (LCAs) were conducted for battery-grade lithium carbonate (Li 2 CO 3 ) and lithium hydroxide monohydrate (LiOH·H 2 O) produced from Chilean brines (Salar de Atacama) and Australian spodumene ores. The LCA was also extended beyond the production of Li 2 CO 3 and LiOH·H 2 O to include battery cathode materials as well as full automotive traction batteries to observe the effect that the lithium production pathways had on these end products. The LCA here covers material, water, and energy flows associated with lithium acquisition; lithium concentration; production of lithium chemicals, battery cathode powders, and batteries; and associated transportation activities along the supply chain. Based on battery cathode material, the difference in lithium source represents a difference of up to 20% for NMC811 cathode greenhouse gases (GHGs) and up to 45% for NMC622 cathode GHGs. For full batteries, this represents a difference of up to 9% for NMC811 batteries and 20% for NMC622 batteries. Production of Li 2 CO 3 from brine-based resources had less life cycle GHG emissions and freshwater consumption per tonne of Li 2 CO 3 than Li 2 CO 3 from ore-based resources. And LiOH·H 2 O produced from brine-based lithium also had less life cycle GHG emissions and freshwater consumption per tonne of LiOH·H 2 O than LiOH·H 2 O from ore-based resources.

25 ENERGY STORAGE↗

DOE OSTI2020

Enzyme activities predicted by metabolite concentrations and solvent capacity in the cell

Experimental measurements or computational model predictions of the post-translational regulation of enzymes needed in a metabolic pathway is a difficult problem. Consequently, regulation is mostly known only for well-studied reactions of central metabolism in various model organisms. In this study, we use two approaches to predict enzyme regulation policies and investigate the hypothesis that regulation is driven by the need to maintain the solvent capacity in the cell. The first predictive method uses a statistical thermodynamics and metabolic control theory framework while the second method is performed using a hybrid optimization–reinforcement learning approach. Efficient regulation schemes were learned from experimental data that either agree with theoretical calculations or result in a higher cell fitness using maximum useful work as a metric. As previously hypothesized, regulation is herein shown to control the concentrations of both immediate and downstream product concentrations at physiological levels. Model predictions provide the following two novel general principles: (1) the regulation itself causes the reactions to be much further from equilibrium instead of the common assumption that highly non-equilibrium reactions are the targets for regulation; and (2) the minimal regulation needed to maintain metabolite levels at physiological concentrations maximizes the free energy dissipation rate instead of preserving a specific energy charge. The resulting energy dissipation rate is an emergent property of regulation which may be represented by a high value of the adenylate energy charge. In addition, the predictions demonstrate that the amount of regulation needed can be minimized if it is applied at the beginning or branch point of a pathway, in agreement with common notions. The approach is demonstrated for three pathways in the central metabolism of E. coli (gluconeogenesis, glycolysis-tricarboxylic acid (TCA) and pentose phosphate-TCA) that each require different regulation schemes. It is shown quantitatively that hexokinase, glucose 6-phosphate dehydrogenase and glyceraldehyde phosphate dehydrogenase, all branch points of pathways, play the largest roles in regulating central metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Global Impacts of Marine Methanethiol Emissions and Chemistry in the Atmosphere

Oceanic emissions of dimethyl sulfide (DMS) have long been known to influence aerosol particle composition, cloud condensation nuclei (CCN) concentration, and Earth’s radiative budget. However, the impact of oceanic emissions of methanethiol (MeSH), a sulfur compound produced by the same oceanic precursor as DMS, has been relatively less explored. The gas-phase oxidation of MeSH has a higher effective yield of SO 2 and a shorter oxidative lifetime compared to DMS, highlighting the relevance of this pathway for the modeled representation of particle formation, growth, and CCN abundance in the marine atmosphere. Here, we use the global chemical transport model GEOS-Chem to explore possible scenarios representative of specific environmental conditions and MeSH emission schemes based on previous experimental studies. We further implement and test previously reported chemical mechanisms for MeSH oxidation, along with additional improvements, highlighting key uncertainties and sensitivities for regional and global sulfur budgets. We place our results in the context of recent modeling updates to DMS chemistry and cloud processing, which further impact SO 2 production in the marine atmosphere in parallel with MeSH oxidation. Within the overall marine sulfur budget, our findings highlight that MeSH plays a significant role in SO 2 production in the marine atmosphere, contributing to regional surface layer concentration increases of up to 40–60%. These results point to the importance of MeSH for efforts aimed at improving the modeled representation of sulfur spatiotemporal patterns relevant to air quality predictions and climate impact assessments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

FY24 Task 5: Leachate Disposition

Directly feeding sludge solids to the high-level waste (HLW) Waste Treatment Plant represents an alternative flowsheet seeking to initiate sludge processing as soon as possible. Key processing functions previously captured during baseline pretreatment operations include leaching and washing prior to solids concentration. These operations should be considered in the potential direct feed flowsheets to maximize waste feed loading, minimize HLW volume, and mitigate corrosion challenges associated with vitrification of high phosphate and fluoride concentrations. Additionally, single-shell tank (SST) retrievals and waste transfers to double-shell tanks (DSTs) in a direct feed flowsheet would likely also benefit from some level of leaching, washing, and solids concentration in order to reduce DST space and mission duration. These operations could occur in a new facility or potentially in available DSTs. If washing and leaching are utilized, an effective disposition pathway for the wash water and leachate solutions are needed. Three target species that benefit significantly from leaching and washing are phosphate, fluoride and aluminum. Phosphate (PO 4 3- ) and fluoride (F - ) can contribute substantially to the amount of carrier fluid needed for dissolution, and the resulting volume of liquid generated. Disposition of this retrieval solution should be evaluated in order to prevent crystallization of these anions throughout system processing. Since there is a high probability that any retrieval solutions will be at or near their PO 4 3- and F - solubility limits, evaporation or blending with a high Na supernate (>3.5 M) is not recommended for the wash water streams without a method to remove precipitants prior to solution disposal. Additionally, aluminum present in the southeast quadrant of the Hanford site represents roughly 60% of the waste solids in the initial processing tanks. These aluminum solids are in the form of gibbsite (Al(OH) 3 ) and can pose significant challenges for processing due to the fast-settling times and high solids loading associated with these materials. Easily remediated by caustic addition to the solids, these wash solutions could be processed through crystalline silicotitanate (CST) ion exchange columns to prepare the supernate solutions for disposition. The current target for feed conditions to the Low Activity Waste (LAW) melter are waste streams that contain nominally 5-6 M Na. Fractions within the tanks contain upwards of 0.2 M phosphate and fluoride in solution at 3.5 M Na. Concentrating these solutions above 5 M Na would result in an exceedance of the solubility limits, and potential for uncontrolled precipitation of the phosphate and fluoride crystal material. The resulting crystalline salt material is typically sodium fluoride phosphate, also referred to as natrophosphate (Na 7 FPO 4 ·19H 2 O). Salt phases are of importance in tank waste due to their chemical reactivity, which can result in precipitation, dissolution, or transformation, impacting any downstream processes (Bolling et al. 2020, Russell, Snow, and Peterson 2010). Salt generation and precipitation could pose challenges by causing system plugging and melter corrosion if left in the supernate stream, or limit sodium molarity of the supernate that would be accepted without incident in waste operations. To understand the impact of this salt generation, the crystallization of natrophosphate in multiple simulant feed matrices was studied to understand the implications of various tank waste supernate chemistries. Three matrices were examined: high PO 4 3- /low F - , low PO 4 3- /high F - , and an average matrix. Subsequent testing was performed with the average matrix with the inclusion of CsNO 3 , and a final run with the average matrix including CsNO 3 and a 137 Cs spike for tracer purposes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗