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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2026

Modeling the Cosmological Lyman-𝛼 Forest at the Field Level

The distribution of absorption lines in the spectra of distant quasars, called the Lyman-𝛼 (Ly-𝛼) forest, is a unique probe of cosmology and the intergalactic medium at high redshifts and small scales. The statistical power of ongoing redshift surveys demands precise theoretical tools to model the Ly-𝛼 forest. We address this challenge by developing an analytic, perturbative forward model to predict the Ly-𝛼 forest at the field level for a given set of cosmological initial conditions. Our model shows a remarkable performance when compared with the Sherwood hydrodynamic simulations: it reproduces the Ly-𝛼 forest flux power spectrum, its cross-correlation with dark matter halos, and the one-point probability distribution function of both fields at the percent level down to scales of a few Mpc. Our work provides crucial tools that bridge analytic modeling on large scales with simulations on small scales, enabling field-level inference from Ly-𝛼 forest data and simulation-based priors for cosmological analyses. Furthermore, this is especially timely for realizing the full scientific potential of the Ly-𝛼 forest measurements by the dark energy spectroscopic instrument.

Cosmological parameters↗
DOE OSTI2025

The evidence of N = 16 shell closure and β -delayed neutron emission from 25 F

We measured the β -delayed neutron emission from 25 F for the first time at the Facility for Rare Isotope Beams (FRIB). Using combined neutron and γ -ray detector systems of the FRIB Decay Station Initiator (FDSi), we observed β -decay transitions populating neutron unbound states between 4.2 and 8 MeV in 25 Ne. The experimental results led to the revision of the β -decay half-life and β -delayed neutron-emission probability of 25 F. The β -decay strength distribution of 25 F extracted from the data agrees with the shell-model predictions using the USDB and SDPF-M effective interactions. This result indicates that the spherical neutron shell gap persists in 25 F and 25 Ne.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Hydrated doped-BaZrO 3 proton conductors studied by positron annihilation lifetime spectroscopy

The study of defect chemistry for doped BaZrO 3 proton conductors is of particular interest because of defect interactions that can affect the proton conductivity of the material. Protons incorporated due to the material's hydration can be trapped by negatively charged immobile dopants, reducing proton mobility. The reduction of the proton conduction impedes using BaZrO 3 materials in energy conversion applications at intermediate temperatures (300°C – 600°C). The probing of proton trapping in doped BaZrO 3 is hindered by the limited availability of techniques sensitive to defect chemistries. In this work, we used positron annihilation lifetime spectroscopy (PALS) to study the defect chemistry of Y-doped and Sc-doped BaZrO 3 . Using a two-state positron trapping model we showed that PALS can be used to study the defect chemistry of hydrated dense proton conductors. Positron trapping rates and lifetimes were correlated with doping levels of the materials. Probability significance t-tests were carried out for PALS parameters to verify whether there are differences/similarities for various populations: non-doped/doped, level and type of doping, high temperature, and surface effects. Further, the results revealed that the initial doping generates a significant number of traps available for positrons. Doping in yttrium increased the positron trapping rate, while this effect was not observed with scandium. Low-temperature hydration affects specimens significantly inhibiting positron trapping at undoped BaZrO 3 material and highly doped specimens. Positronium formation in rough surface layers, and highly doped specimens was detected but does not exceed 1%.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transient anisotropic kernel for probabilistic learning on manifolds

PLoM (Probabilistic Learning on Manifolds) is a method introduced in 2016 for handling small training datasets by projecting an Itô equation from a stochastic dissipative Hamiltonian dynamical system, acting as the MCMC generator, for which the KDE-estimated probability measure with the training dataset is the invariant measure. PLoM performs a projection on a reduced-order vector basis related to the training dataset, using the diffusion maps (DMAPS) basis constructed with a time-independent isotropic kernel. In this paper, we propose a new ISDE projection vector basis built from a transient anisotropic kernel, providing an alternative to the DMAPS basis to improve statistical surrogates for stochastic manifolds with heterogeneous data. The construction ensures that for times near the initial time, the DMAPS basis coincides with the transient basis. For larger times, the differences between the two bases are characterized by the angle of their spanned vector subspaces. The optimal instant yielding the optimal transient basis is determined using an estimation of mutual information from Information Theory, which is normalized by the entropy estimation to account for the effects of the number of realizations used in the estimations. Consequently, this new vector basis better represents statistical dependencies in the learned probability measure for any dimension. Three applications with varying levels of statistical complexity and data heterogeneity validate the proposed theory, showing that the transient anisotropic kernel improves the learned probability measure.

Diffusion maps↗
DOE OSTI2023

Series FACTS Devices for Increasing Resiliency in Severe Weather Conditions

Severe weather conditions are low-probability, high-impact events that affect grid operations. The majority of power outages are caused by severe weather conditions. Grid resiliency to weather events can be enhanced by decreasing the reliance on its affected sections. One way to do this is to reduce the power flow through lines vulnerable to severe weather. If a line is disconnected, its initial power flow is distributed through the neighbor lines, which may cause congestion in the grid. FACTS devices can be used to control the power flow of lines that have a higher chance of power outages. Most previous works do not consider weather events in power flow control. In this work, a linearized optimal power flow (OPF)–based algorithm is developed to minimize the real power flow of vulnerable lines considering the thermal limits of lines to prevent infeasible solutions; the simulation is fast, making it suitable for large-scale systems. The proposed optimization problem is presented as a mixed-integer linear program (MILP), making it capable of using short-term load forecasting due to its high solution speed. The proposed optimization problem considers multiple lines with different outage probabilities and the uncertainties of the weather forecast. Moreover, it estimates the power reduction in vulnerable lines due to changes in the series FACTS devices. The performance of the proposed optimization problem is tested on IEEE 14-, 30-, and 118-bus systems for several scenarios. The results are validated with the AC power flow results from MATPOWER.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

GeoMicro3D: A novel numerical model for simulating the reaction process and microstructure formation of alkali-activated slag

Highlights: • The GeoMicro3D model was innovatively developed for simulating the reaction process and microstructure formation of AAS. • In GeoMicro3D, the dissolution of slag and reactions of aqueous ions are fundamentally described in the local lattice cell. • A novel approach is proposed to speed up the nucleation simulations. • GeoMicro3D was implemented and verified with the relevant experimental data and thermodynamic calculation results. For the first time, this study developed a novel model, named GeoMicro3D, to simulate the reaction process and microstructure formation of alkali-activated slag. The GeoMicro3D model consists of four modules that are designed to simulate, respectively: (i) the initial spatial distribution of real-shape slag particles in alkaline activator, (ii) the dissolution of slag and diffusion of ions via the transition state theory and lattice Boltzmann method, respectively, (iii) the spatial distribution of reaction products using a nucleation probability theory, and (iv) the chemical reactions with thermodynamic modelling. Afterwards the GeoMicro3D model was implemented and verified. The simulation results were discussed and compared with the relevant experimental data and thermodynamic calculation results using GEMS. A good agreement was found in the comparisons, showing the strong simulation capability of GeoMicro3D.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity

We present a stochastic mathematical model of the intracellular infection dynamics of Bacillus anthracis in macrophages. Following inhalation of B. anthracis spores, these are ingested by alveolar phagocytes. Ingested spores then begin to germinate and divide intracellularly. This can lead to the eventual death of the host cell and the extracellular release of bacterial progeny. Some macrophages successfully eliminate the intracellular bacteria and will recover. Here, a stochastic birth-and-death process with catastrophe is proposed, which includes the mechanism of spore germination and maturation of B. anthracis . The resulting model is used to explore the potential for heterogeneity in the spore germination rate, with the consideration of two extreme cases for the rate distribution: continuous Gaussian and discrete Bernoulli. We make use of approximate Bayesian computation to calibrate our model using experimental measurements from in vitro infection of murine peritoneal macrophages with spores of the Sterne 34F2 strain of B. anthracis . The calibrated stochastic model allows us to compute the probability of rupture, mean time to rupture, and rupture size distribution, of a macrophage that has been infected with one spore. We also obtain the mean spore and bacterial loads over time for a population of cells, each assumed to be initially infected with a single spore. Our results support the existence of significant heterogeneity in the germination rate, with a subset of spores expected to germinate much later than the majority. Furthermore, in agreement with experimental evidence, our results suggest that most of the spores taken up by macrophages are likely to be eliminated by the host cell, but a few germinated spores may survive phagocytosis and lead to the death of the infected cell. Finally, we discuss how this stochastic modelling approach, together with dose-response data, allows us to quantify and predict individual infection risk following exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Scrambling Dynamics with Imperfections in a Solvable Model

We study how probes of quantum scrambling dynamics respond to two kinds of imperfections -- unequal forward and backward evolutions and decoherence -- in a solvable Brownian circuit model. We calculate a ``renormalized'' out-of-time-order correlator (ROTOC) in the model with $N$ qubits, and we show that the circuit-averaged ROTOC is controlled by an effective probability distribution in operator weight space which obeys a system of $N$ non-linear equations of motion. These equations can be easily solved numerically for large system sizes which are beyond the reach of exact methods. Moreover, for an operator initially concentrated on weight one $w_0=1$, we provide an exact solution to the equations in the thermodynamic limit of many qubits that is valid for all times, all non-vanishing perturbation strengths $p\gtrsim 1/\sqrt{N}$, and all decoherence strengths. We also show that a generic initial condition $w_0 >1$ leads to a metastable state that eventually collapses to the $w_0=1$ case after a lifetime $\sim \log(N/w_0)$. Our results highlight situations where it is still possible to extract the unperturbed chaos exponent even in the presence of imperfections, and we comment on the applications of our results to existing experiments with nuclear spins and to future scrambling experiments.

FOS: Physical sciences↗
DOE OSTI2021

Industry-Average Performance for Components and Initiating Events at U.S. Commercial Nuclear Power Plants: 2020 Update

This report documents the quantitative results of the current industry-average performance for components and initiating events (IEs) at U.S. commercial nuclear power plants (NPPs). It represents the third update of the original analysis in NUREG/CR-6928 with data through 2020. Continuous characterization and updating of current industry-average performance with the latest industry data available are important steps in maintaining up-to-date risk models. Typically, data from 1998–2002 were used in NUREG/CR-6928, data from 1998–2010 in the first update, data from 1998–2015 in the second update, and data from 2006–2020 in this update, although many IEs required longer periods for adequate characterization of frequencies in all these analyses. As with NUREG/CR-6928 and previous updates, four types of events are covered in this report: component unreliability (e.g., a pump that fails to start or fails to run), component or train unavailability resulting from test or maintenance outages, special event probabilities covering operational issues (e.g., pump restarts and injection valve re-openings during unplanned demands), and IE frequencies. Results (in the form of beta distributions for failure probabilities upon demand and gamma distributions for rates) are used as inputs to the U.S. Nuclear Regulatory Commission standardized plant analysis risk models covering U.S. commercial NPPs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Uncertainty Quantification Enabled by Automatic Differentiation for Hydrodynamic Simulation of Shock‐to‐Detonation Transition in High Explosives

Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Survey of gravitationally lensed objects in HSC imaging (SuGOHI) – X. Strong lens finding in the HSC-SSP using convolutional neural networks

ABSTRACT We apply a novel model based on convolutional neural networks (CNN) to identify gravitationally lensed galaxies in multiband imaging of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. The galaxies in HSC Wide are selected based on stringent pre-selection criteria, such as multiband magnitudes, stellar mass, star formation rate, extendedness limit, photometric redshift range, etc. The trained CNN assigns a score from 0 to 1, with 1 representing lenses and 0 representing non-lenses. Initially, the CNN selects a total of 20 241 cutouts with a score greater than 0.9, but this number is subsequently reduced to 1522 cutouts after removing definite non-lenses for further visual inspection. We discover 43 grade A (definite) and 269 grade B (probable) strong lens candidates, of which 97 are completely new. In addition, we also discover 880 grade C (possible) lens candidates, 289 of which are known systems in the literature. We identify 143 candidates from the known systems of grade C that had higher confidence in previous searches. Our model can also recover 285 candidate galaxy-scale lenses from the Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI), where a single foreground galaxy acts as the deflector. Even though group-scale and cluster-scale lens systems are not included in the training, a sample of 32 SuGOHI-c (i.e. group/cluster-scale systems) lens candidates is retrieved. Our discoveries will be useful for ongoing and planned spectroscopic surveys, such as the Subaru Prime Focus Spectrograph project, to measure lens and source redshifts in order to enable detailed lens modelling.

Jaelani, Anton T. (ORCID:0000000162825778)↗
DOE OSTI2023

Li iontronics in single-crystalline T-Nb2O5 thin films with vertical ionic transport channels

Abstract The niobium oxide polymorph T -Nb 2 O 5 has been extensively investigated in its bulk form especially for applications in fast-charging batteries and electrochemical (pseudo)capacitors. Its crystal structure, which has two-dimensional (2D) layers with very low steric hindrance, allows for fast Li-ion migration. However, since its discovery in 1941, the growth of single-crystalline thin films and its electronic applications have not yet been realized, probably due to its large orthorhombic unit cell along with the existence of many polymorphs. Here we demonstrate the epitaxial growth of single-crystalline T -Nb 2 O 5 thin films, critically with the ionic transport channels oriented perpendicular to the film’s surface. These vertical 2D channels enable fast Li-ion migration, which we show gives rise to a colossal insulator–metal transition, where the resistivity drops by 11 orders of magnitude due to the population of the initially empty Nb 4 d 0 states by electrons. Moreover, we reveal multiple unexplored phase transitions with distinct crystal and electronic structures over a wide range of Li-ion concentrations by comprehensive in situ experiments and theoretical calculations, which allow for the reversible and repeatable manipulation of these phases and their distinct electronic properties. This work paves the way for the exploration of novel thin films with ionic channels and their potential applications.

Chemistry↗
DOE OSTI2022

Search for Supernova Neutrinos and Constraint on the Galactic Star Formation Rate with the KamLAND Data

We present the results of a search for core-collapse supernova neutrinos, using long-term KamLAND data from 2002 March 9 to 2020 April 25. We focus on the electron antineutrinos emitted from supernovae in the energy range of 1.8–111 MeV. Supernovae will make a neutrino event cluster with the duration of ~10 s in the KamLAND data. We find no neutrino clusters and give the upper limit on the supernova rate to be 0.15 yr –1 with a 90% confidence level. The detectable range, which corresponds to a >95% detection probability, is 40–59 kpc and 65–81 kpc for core-collapse supernovae and failed core-collapse supernovae, respectively. This paper proposes to convert the supernova rate obtained by the neutrino observation to the Galactic star formation rate. Assuming a modified Salpeter-type initial mass function, the upper limit on the Galactic star formation rate is <(17.5–22.7) M ⊙ yr –1 with a 90% confidence level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Preliminary Radiological Risk Assessment Model for Disposition of Remote-Handled Transuranic Wastes at Los Alamos National Laboratory Area G - 20116

The U.S. Department of Energy (DOE) operates a low-level radioactive waste (LLW) disposal site at Material Disposal Area G, in Los Alamos, New Mexico, USA. Area G has been the primary LLW disposal site for Los Alamos National Laboratory (LANL) since the 1960's. In addition to LLW, Area G is host to a variety of other wastes, the disposition of which must be determined before closure of the site. A probabilistic Radiological Risk Assessment (RRA) for Area G is used in order to support decision making regarding some wastes that are not addressed in the extant Area G Performance Assessment (PA) and Composite Analysis (CA). Between 1979 and 1987, 33 special shafts were augered into the Bandelier Tuff at Area G. This volcanic tuff is present across Pajarito Plateau on the eastern slopes of the Jemez Mountains, and varies widely in its consistency, from weakly indurated non-welded layers to welded layers that uphold the mesa cliffs of the Plateau. These mesas are home to LANL, Area G, and the townsites of Los Alamos and White Rock, with residences about 1400 m from Area G. The 33 Shafts were lined with steel casing, and contain remote-handled (RH) transuranic wastes (TRU) resulting from experiments and analysis performed in special glove boxes at the Chemistry and Metallurgy Research (CMR) facility at LANL. Some of these wastes originated as used nuclear fuel. The purpose of the Area G RRA is to evaluate the potential future risk to humans and the environment from the RH TRU in the 33 Shafts in the context of the risk associated with the surrounding wastes at Area G. The analysis is responsive to expectations outlined in DOE Order 458.1, Radiation Protection of the Public and the Environment, and is informed by the Manual and Guidance accompanying DOE O 435.1, Radioactive Waste Management. Because the waste meets the definition of TRU, the regulatory context necessarily takes into consideration the regulation governing the disposal of TRU from the U.S. Environmental Protection Agency (EPA): 40 CFR 191, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes. Given the broader regulatory context for the RRA, the analysis is subject to different assumptions from those made in the existing DOE O 435.1 PA and CA, such as allowing for future occupation of the site. The analysis begins with a comprehensive evaluation of features, events, processes, and exposure scenarios (FEPS) for Area G and the wastes it contains. These FEPSs are screened to eliminate from further consideration those of extremely low probability and/or consequence, and a conceptual site model (CSM) is subsequently developed. The scope and structure of the Area G RRA Model is informed by this CSM, and the Area G RRA Model is developed using the GoldSim systems analysis modeling platform. This paper presents the initial version of a defensible, transparent, and reasonably realistic model, which is based on the state of knowledge of the wastes, the site, and the FEPSs that govern contaminant transport from wastes into the environment and subsequent exposures to humans and other biota. Probabilistic model input distributions represent uncertainties inherent in the real and modeled systems. The results of the Area G RRA Model inform decisions regarding the disposition of the RH TRU in the 33 Shafts. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Decoding ionic conductivity and reordering in cation-disordered pyrochlores

The ordered structure A 2 B 2 O 6 O’ in pyrochlores engenders twin rows of inequivalent anion sublattices each centred on alternating cations. While it is known that cation antisite disorder augments the ionic conductivity by several orders of magnitude, the local cation environment around the anions and the dynamic anion reordering during the cation disordering are not well-elucidated. Using atomistic simulations on Gd 2 Zr 2 O 7 , we first show that the anions engage in concerted hops to the neighbouring tetrahedral sites mostly along with the $\langle$1 0 0$\rangle$ direction while completely avoiding the octahedral sites. While the initially vacant 8 a sites start accommodating oxygen ions with increasing cation disorder, they show noticeable reluctance even at significant levels of disorder. We have also tracked both the distribution of available oxygen sites following random cation disorder, which is dependent only on cation disordering, and the probability of occupation of these sites. Interestingly, the available oxygen sites show a non-monotonic dependence on the number of B ions in the nearest neighbouring shell while the occupation probability of all the available oxygen sites increases monotonically. A tetrahedral oxygen site thus has a better probability of being occupied when it has a greater number of second neighbour B ions. This article is part of the Theo Murphy meeting issue 'Understanding fast-ion conduction in solid electrolytes'.

Science & Technology - Other Topics↗
DOE OSTI2025

Mechanistic within-host mathematical model of inhalational anthrax

We present a mathematical model of the dynamics of Bacillus anthracis bacteria within the lymph nodes and blood of a host, following inhalation of an initial dose of spores. We also incorporate the dynamics of protective antigen, which is the binding component of the anthrax toxin produced by the bacteria. The model offers a mechanistic description of the early infection dynamics of inhalational anthrax, while its stochastic nature allows us to study the probabilities of different outcomes (for example, how likely it is that the infection will be cleared for a given inhaled dose of spores) in order to explain dose-response data for inhalational anthrax. The model is calibrated via a Bayesian approach, using in vivo data from New Zealand white rabbit and guinea pig infection studies, enabling within-host parameters to be estimated. We also leverage incubation-period data from the Sverdlovsk 1979 anthrax outbreak to show that the model can accurately describe human time-to-symptoms data under reasonable parameter regimes. Finally, we derive a simple approximate formula for the probability of symptom onset before time t, assuming that the number of inhaled spores has a Poisson distribution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗
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↗