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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Estimating source-sink distributions and fluxes of reactive nitrogen and sulfur within a mixed forest canopy

The vertical source-sink distribution of air pollutants within and above forested canopies is necessary for describing the biological, physical, and chemical processes influencing the soil-vegetation-atmosphere exchange. Here, this study implemented inverse modeling methods to estimate the source-sink and flux profiles of reactive nitrogen (N) and sulfur (S) compounds from measurements of the mean concentration profiles of ammonia (NH 3 ), nitric acid (HNO 3 ), sulfur dioxide (SO 2 ), and particulate ammonium (NH 4 + ), nitrate (NO 3 − ), and sulfate (SO 4 2− ) at a forest site in the southern Appalachian Mountains. Three inverse approaches utilizing different approximations to scalar transport within the canopy were developed and evaluated against sensible heat flux measurements. The Eulerian model (EUL), which incorporates vertical velocity skewness, performed well in reproducing the turbulent heat fluxes and was subsequently used to calculate the chemical source-sink and flux profiles. Above-canopy fluxes of NH 3 were downward, indicating that the forest was a net sink of NH 3 . The soil/litter layer was both a source and a sink for NH 3 but the exchange rate at the forest floor was small. Fluxes of HNO 3 , SO 2 , NO 3 − , NH 4 + , and SO 4 2- were uni-directional (deposition only) between the air and the canopy/ground and increased monotonically from the forest floor to the canopy top. Crown foliage dominated the uptake of reactive N and S during the growing season, accounting for 80–90% of the total canopy-scale flux. Fluxes and canopy-ground partitioning estimated using the resistance-based Surface Tiled Aerosol and Gas Exchange (STAGE) model were generally comparable to EUL. The comparison highlights the need for improved parameterizations of litter exchange and NH 3 compensation points in resistance models for forest ecosystems. The findings here benefit the application of critical loads in forest ecosystems and guide further development of resistance-based exchange models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Solvent Induced Proton Polarization within the Nuclear–Electronic Orbital Framework

To explicitly account for nuclear quantum effects and solvent environments in simulations of chemical processes, the nuclear-electronic orbital approach is coupled with a polarizable continuum model (PCM). This NEO–PCM approach is used to explore the influence of solvation on nuclear polarization through applications to a water dimer and a set of protonated water tetramers. Nuclear polarization in these species is analyzed in terms of changes in proton density and oxygen–hydrogen bond length. Solvation is shown to enhance nuclear polarization with increasing dielectric constant. For the water dimer, the internal, hydrogen-bonded proton is shown to polarize more than the external, free proton. Moreover, proton quantization leads to greater solvent polarization through their mutual polarization. Furthermore, these calculations highlight the complex interplay among electronic, nuclear, and solvent polarization in chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗
DOE OSTI2022

Nonlinear electronic excitation in water under proton irradiation: a first principles study

Nonlinear dynamics of electronic excitation bridge physical and physicochemical stages of water radiolysis under proton irradiation, a multi-scale physicochemical process that is fundamental to a wide range of technological and medical applications of high-energy protons. We study the spatial and temporal changes to the excited holes generated in this ionization event using first-principles theory simulation. A significant majority of holes are formed in the immediate vicinity of the irradiating proton paths, and these holes decay rapidly, while secondary excitations are simultaneously induced in regions farther away. While the hole population remains constant, the observed spatially spreading hole distribution cannot be described as concentration-dependent diffusion current. Compared to the primary excitation induced by the irradiating protons, the secondary excitation farther away is somewhat less energetic. Here, the first-principles theory simulation here provides a detailed description of how the primary excitation by proton radiation precedes the formation of cationic holes, which undergo ultrafast chemical processes in water radiolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Surface structure studies in 2D and 3D Nb resonators using GI-XRD

Superconductor radio frequency (SRF) Nb-resonators are a key element in the development of new generations of particle accelerators as well as in the fabrication of 3D circuit QED architecture for quantum computing. Nevertheless, Niobium is extremally reactive to light elements such as C, N, O and H, and therefore to the impurities ordering under special conditions, e.g., cryogenic temperatures. Since these resonators are put through a series of metallurgical and chemical processes, the number of impurities in the solid increases in tens of ppm. Upon operational conditions ~1.6 K, Nb become vulnerable to H atoms ordering, which leads to the nucleation of secondary phases such as Nb-hydrides. Thereupon to the energy dissipation and eventually to the superconductivity breakdown known as Q-disease and potentially High-Field Q-slope. In this contribution, we present a detailed structural analysis by high-energy grazing-incidence X-ray diffraction of specimens extracted from 3D Nb resonators to shed light on the kinetic formation of the resulting secondary phases and their crystal phase identification upon cooling and heating cycles. To our knowledge, this is the first study carried out in resonators samples using a light source, shallow angles and temperatures near ~4 K. Consequently, this work opens new routes to understand the chemical and phase composition, crystal and electronic structure of the Nb surface at temperatures near the operating conditions as a strategy to improve the physical and functional properties of Nb superconducting resonators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

On the influence of over-parameterization in manifold based surrogates and deep neural operators

Constructing accurate and generalizable approximators (surrogate models) for complex physico-chemical processes exhibiting highly non-smooth dynamics is challenging. The main question is what type of surrogate models we should construct and should these models be under-parameterized or over-parameterized. In this work, we propose new developments and perform comparisons for two promising approaches: manifold-based polynomial chaos expansion (m-PCE) and the deep neural operator (DeepONet), and we examine the effect of over-parameterization on generalization. While m-PCE enables the construction of a mapping by first identifying low-dimensional embeddings of the input functions, parameters, and quantities of interest (QoIs), a neural operator learns the nonlinear mapping via the use of deep neural networks. Here, we demonstrate the performance of these methods in terms of generalization accuracy by solving the 2D time-dependent Brusselator reaction-diffusion system with uncertainty sources, modeling an autocatalytic chemical reaction between two species. We first propose an extension of the m-PCE by constructing a mapping between latent spaces formed by two separate embeddings of the input functions and the output QoIs. To further enhance the accuracy of the DeepONet, we introduce weight self-adaptivity in the loss function. We demonstrate that the performance of m-PCE and DeepONet is comparable for cases of relatively smooth input-output mappings. However, when highly non-smooth dynamics is considered, DeepONet shows higher approximation accuracy. We also find that for m-PCE, modest over-parameterization leads to better generalization, both within and outside of distribution, whereas aggressive over-parameterization leads to over-fitting. In contrast, an even highly over-parameterized DeepONet leads to better generalization for both smooth and non-smooth dynamics. Furthermore, we compare the performance of the above models with another recently proposed operator learning model, the Fourier Neural Operator, and show that its over-parameterization also leads to better generalization. Taken together, our studies show that m-PCE can provide very good accuracy at very low training cost, whereas a highly over-parameterized DeepONet can provide better accuracy and robustness to noise but at higher training cost. In both methods, the inference cost is negligible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Machine‐learning‐based construction of barrier functions and models for safe model predictive control

Abstract In this paper, we propose a control Lyapunov‐barrier function‐based model predictive control method utilizing a feed‐forward neural network specified control barrier function (CBF) and a recurrent neural network (RNN) predictive model to stabilize nonlinear processes with input constraints, and to guarantee that safety requirements are met for all times. The nonlinear system is first modeled using RNN techniques, and a CBF is characterized by constructing a feed‐forward neural network (FNN) model with unique structures and properties. The FNN model for the CBF is trained based on data samples collected from safe and unsafe operating regions, and the resulting FNN model is verified to demonstrate that the safety properties of the CBF are satisfied. Given sufficiently small bounded modeling errors for both the FNN and the RNN models, the proposed control system is able to guarantee closed‐loop stability while preventing the closed‐loop states from entering unsafe regions in state‐space under sample‐and‐hold control action implementation. We provide the theoretical analysis for bounded unsafe sets in state‐space, and demonstrate the effectiveness of the proposed control strategy using a nonlinear chemical process example with a bounded unsafe region.

Chen, Scarlett↗
DOE OSTI2022

Review: Induced Seismicity During Geoenergy Development—A Hydromechanical Perspective

The basic triggering mechanism underlying induced seismicity traces back to the mid-1960s that relied on the process of pore-fluid pressure diffusion. The last decade has experienced a renaissance of induced seismicity research and data proliferation. An unprecedent opportunity is presented to us to synthesize the robust growth in knowledge. The objective of this article is to provide a concise review of the triggering mechanisms of induced earthquakes with a focus on hydro-mechanical processes. Four mechanisms are reviewed: pore-fluid pressure diffusion, poroelastic stress, Coulomb static stress transfer, and aseismic slip. For each, an introduction of the concept is presented, followed by case studies. Diving into these mechanisms sheds light on several outstanding questions. For example, why did some earthquakes occur far from fluid injection or after injection stopped? Our review converges on the following conclusions: (a) Pore-fluid pressure diffusion remains a basic mechanism for initiating inducing seismicity in the near-field. (b) Poroelastic stresses and aseismic slip play an important role in inducing seismicity in regions beyond the influence of pore-fluid pressure diffusion. (c) Coulomb static stress transfer from earlier seismicity is shown to be a viable mechanism for increasing stresses on mainshock faults. (d) Multiple mechanisms have operated concurrently or consecutively at most induced seismicity sites. (e) Carbon dioxide injection is succeeding without inducing earthquakes and much can be learned from its success. Future research opportunities exist in deepening the understanding of physical and chemical processes in the nexus of geoenergy development and fluid motion in the Earth’s crust.

58 GEOSCIENCES↗
DOE OSTI2021

Roadmap for Sustainable Mixed Ionic–Electronic Conducting Membranes

Mixed ionic-electronic conducting (MIEC) membranes have gained growing interest recently for various promising environmental and energy applications, such as H 2 and O 2 production, CO 2 reduction, O 2 and H 2 separation, CO 2 separation, membrane reactors for production of chemicals, cathode development for solid oxide fuel cells, solar-driven evaporation and energy-saving regeneration as well as electrolyzer cells for power-to-X technologies. The purpose of this roadmap, written by international specialists in their fields, is to present a snapshot of the state-of-the-art, and provide opinions on the future challenges and opportunities in this complex multidisciplinary research field. As the fundamentals of using MIEC membranes for various applications become increasingly challenging tasks, particularly in view of the growing interdisciplinary nature of this field, a better understanding of the underlying physical and chemical processes is also crucial to enable the career advancement of the next generation of researchers. As an integrated and combined article, it is hoped that this roadmap, covering all these aspects, will be informative to support further progress in academics as well as in the industry-oriented research toward commercialization of MIEC membranes for different applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

African dust transported to Barbados in the wintertime lacks indicators of chemical aging

The chemical processing (“aging”) of mineral dust is thought to increase dust light-scattering efficiency, cloud droplet activation, and nutrient solubility. However, the extent of African dust aging during long-range transport to the western Atlantic is poorly understood. Here, we explore African dust aging in wintertime samples collected from Barbados when dust is transported at lower altitudes. Ion chromatography (IC) analysis indicates that the mass concentrations of bulk nitrate, sulfate, and oxalate increase, relative to background conditions, when African dust reaches Barbados after transatlantic transport, indicating dust aging. However, aerosol mixing-state analysis from computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy (CCSEM/EDX) indicates that approximately 67 % of dust particles are internally mixed with sea salt, while only about 26 % of dust particles contain no internally mixed components. SEM/EDX elemental mapping and time-of-flight secondary ion mass spectrometry (TOF-SIMS) reveals that within internally mixed dust and sea salt particles, only sea salt components contain signs of aging as indicated by the loss of chloride and acquisition of nitrate and/or sulfate. Our results suggest that chemical aging may only modestly increase the solubility of nutrients in African dust during long-range transport. Because most dust that we measured was internally mixed with sea salt, chemical aging is not necessarily required to increase the hygroscopicity of dust, at least in the lower boundary layer. Further, our findings have implications for understanding the release of halogens from sea salts, which may be enhanced in internally mixed dust and sea salt particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Variation in Cation Adsorption Mechanism Controlled by Chemical and Structural Heterogeneities at the Quartz (101)–Water Interface

Mineral–water interfacial reactions are central to chemical processes that control the fate of nutrients and contaminants in natural environments. Mineral surfaces commonly have complex structures and compositions whose impact on interfacial reactivity is poorly understood. Here, in this work, we investigated the effects of surface heterogeneities on Rb + sorption at the quartz (101)–10 mM RbCl solution interface at pH 9.8 using in situ high-resolution X-ray reflectivity. Two surface locales (i.e., Spots A and B) having distinct interfacial structures were chosen: Spot A was characterized by its low defect density (≤20% topmost Si vacancies) and Rb + adsorption occurred predominantly as an inner-sphere complex. In comparison, Spot B had a higher defect density (~50% vacancies) and was covered with poorly crystalline SiO 2 . A substantially larger Rb + uptake (i.e., 7-times higher coverage) was observed on this defective surface where Rb + incorporated in the vacancy sites (confirmed by density functional tight binding-based molecular dynamics simulations) or adsorbed directly on the disordered film. These results provide a direct quantification of how surface heterogeneity influences the geochemical behavior of mineral–water interfaces, in particular highlighting the important role of chemical and structural defects on the sorbate speciation and coverage at silicate mineral surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A survey of deuterated ammonia in the Cepheus star-forming region L1251

ABSTRACT Understanding the chemical processes during starless core and prestellar core evolution is an important step in understanding the initial stages of star and disc formation. This project is a study of deuterated ammonia, o-NH2D, in the L1251 star-forming region towards Cepheus. Twenty-two dense cores (20 of which are starless or prestellar, and two of which have a protostar), previously identified by p-NH3 (1,1) observations, were targeted with the 12m Arizona Radio Observatory telescope on Kitt Peak. o-NH2D J$_{\rm {K_a} \rm {K_c}}^{\pm } =$$1_{11}^{+} \rightarrow 1_{01}^{-}$ was detected in 13 (59 per cent) of the NH3-detected cores with a median sensitivity of $\sigma _{T_{mb}} = 17$ mK. All cores detected in o-NH2D at this sensitivity have p-NH3 column densities >1014 cm−2. The o-NH2D column densities were calculated using the constant excitation temperature (CTEX) approximation while correcting for the filling fraction of the NH3 source size. The median deuterium fraction was found to be 0.11 (including 3σ upper limits). However, there are no strong, discernible trends in plots of deuterium fraction with any physical or evolutionary variables. If the cores in L1251 have similar initial chemical conditions, then this result is evidence of the cores physically evolving at different rates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Molecular-scale mechanisms of CO 2 mineralization in nanoscale interfacial water films

The calamitous impacts of untethered carbon emission from fossil-fuel-burning energy infrastructure calls for accelerated development of large-scale CO 2 capture, utilization, and storage technologies that are underpinned by fundamental understanding of molecular-level chemical processes. In the subsurface, rocks rich in divalent metals can react with CO 2 , permanently sequestering it in the form of stable metal carbonate minerals, with the CO 2 -H 2 O composition of the post-injection pore fluid acting as a primary control variable. Herein, we compare mechanistic reaction pathways for aqueous-mediated carbonation with carbon mineralization occurring in nanoscale adsorbed water films. In the extreme of pores filled with a CO 2 -dominant fluid, carbonation reactions are confined to nanometer-thick water films coating mineral surfaces, which enable metal cation release, transport, nucleation, and crystallization of metal carbonate minerals. Though seemingly counterintuitive, laboratory studies have demonstrated facile carbonation rates in these low water environments, which in recent years has begun to be better understood in mechanistic detail. The overarching objective of this review is to delineate the unique underlying molecular-scale reaction mechanisms that govern CO 2 mineralization in these reactive and dynamic quasi-2D interfaces. Here. we highlight the importance of understanding unique properties in thin water films, such as how water dielectric properties, and consequently ion solvation/hydration behavior, can change under nanoconfinement. We conclude by identifying important frontiers for future work and opportunities to exploit these fundamental chemical insights for decarbonization technologies in the 21st century.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The effect of oxygen concentration on the speciation of laser ablated uranium

Abstract In order to model the fate and transport of particles following a nuclear explosion, there must first be an understanding of individual physical and chemical processes that affect particle formation. One interaction pertinent to fireball chemistry and resultant debris formation is that between uranium and oxygen. In this study, we use laser ablation of uranium metal in different concentrations of oxygen gas, either 16 O 2 or 18 O 2 , to determine the influence of oxygen on rapidly cooling uranium. Analysis of recovered particulates using infrared absorption and Raman spectroscopies indicate that the micrometer-sized particulates are predominantly amorphous UO x (am-UO x , where 3 ≤ x ≤ 4) and UO 2 after ablation in 1 atm of pure O 2 and a 1% O 2 /Ar mixture, respectively. Energy dispersive X-ray spectroscopy (EDS) of particulates formed in pure O 2 suggest an O/U ratio of ~ 3.7, consistent with the vibrational spectroscopy analysis. Both am-UO x and UO 2 particulates convert to α-U 3 O 8 when heated. Lastly, experiments performed in 18 O 2 environments show the formation of 18 O-substituted uranium oxides; vibrational frequencies for am-U 18 O x are reported for the first time. When compared to literature, this work shows that cooling timescales can affect the structural composition of uranium oxides (i.e., crystalline vs. amorphous). This indicator can be used in current models of nuclear explosions to improve our predicative capabilities of chemical speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Technical Evaluation of Accelerated Basin De-Inventory Material Addition to Sludge Batch 11 (Rev. 1)

The Accelerated Basin De-inventory (ABD) program involves discarding spent nuclear fuel that is currently stored in L-Basin to the Defense Waste Processing Facility (DWPF) for vitrification. The first ABD discards will occur during the preparation of Sludge Batch (SB) 11. Savannah River Mission Completion has requested that the Savannah River National Laboratory assess the technical gaps related to the increased gadolinium poisoning requirement and the impacts of performing the Low Temperature Aluminum Dissolution (LTAD) process in Tank 51 with H-Canyon discards present. The following summarizes the evaluation of the impacts of increasing the quantity of gadolinium (and related topics) from what was previously evaluated in the SRNL studies of gadolinium-poisoned ABD material solubility, the overall ABD flowsheet review, and increasing the fissile mass loading in glass: 1) Based on literature surveys, there is no indication that organic interactions with gadolinium will be significant at the high pH (typically >13) conditions of the Concentration, Storage, and Transfer Facilities. Any interactions of gadolinium with organics in DWPF are not expected to adversely impact DWPF or downstream facilities. Thus, there is little-to-no residual risk from organic interactions with gadolinium [Gap closed]; 2) Adding depleted uranium to ABD material, targeting 235 U enrichment of 4.90% within each transfer window, will mitigate potential impacts from an increase in soluble 235 U enrichment during sludge washing and LTAD. The plan to take advantage of previous transfers and allow 235 U enrichment of >5% during the final transfer window carries a risk that Tank 51 supernate will have a 235 U enrichment of >5%, which should be evaluated for acceptance; 3) Increasing the gadolinium mass ratio to 3.0:1 Gd: 235 U(eq SLU ) should lead to the same or higher partitioning of gadolinium into the solid phase within the DWPF Chemical Process Cell, resulting in both liquid and solid phases with expected partitioning of Gd consistent with the prior solubility study [Gap closed for SB11]; 4) There are no expected impacts on DWPF melt temperature and melter operations due to the minimal ~0.2 weight percent (wt%) increase in Gd concentration relative to previous sludge batches [Gap closed for SB11]; 5) As observed previously, Gd is expected to enter the off-gas system via physical entrainment, but at a slightly higher concentration than what was observed for SB9 melter off-gas pluggage deposits (0.07 wt%) [Gap closed for SB11] ; 6) There are no expected impacts on DWPF recycle or the Recycle Collection Tank glycolate destruction process. [Gap closed for SB11]; 7) Gd is projected to be a trace component in the SB11 glass (<0.5 wt%) and can be ignored for process control. Trace components do not significantly impact glass durability, thus the conclusions of the previous Product Consistency Test evaluation at a fissile mass loading of 2,500 g fissile/m3 glass still applies to SB11. The ~0.1 wt% increase in Gd2O3 concentration relative to the previous study will not impact the predictability of SB11 glass with the DWPF Product Composition Control System (PCCS) models for durability or the acceptability of glass according to the Waste Acceptance Product Specifications (WAPS) criterion for product consistency [Gap closed for SB11]; 8) No additional Toxicity Characteristic Leaching Procedure testing is necessary for SB11 and the hazardous waste specification of the SB11 DWPF waste form is unchanged after the addition of the ABD stream [Gap closed for SB11]. The following summarizes the evaluation of the impacts of adding two-thirds of the ABD material to Tank 51 prior to LTAD: 1) The addition of two-thirds of the ABD increases overall aluminum mass from 1.39×10 4 kg to 1.64×10 4 kg (15.5% ABD Al). The form of the insoluble portion of the Al resulting from ABD addition should be the more readily dissolved Al(OH) 3 and amorphous forms. The portion of the ABD aluminum that is processed by LTAD is expected to be completely soluble, thus requiring that less of the boehmite in the sludge be dissolved to reach the same Al target in the SB. [Gap closed for SB11]; The expected LTAD impact on other components, as related primarily to the components in ABD, are discussed. Gd is expected to remain insoluble during LTAD and not impact the solubility of other components. [Gap closed for SB11]; The addition of two-thirds of the ABD increases overall projected SB11 uranium mass from 4,740 kg to 13,100 kg (63% ABD U) and the projected plutonium mass from 86.0 kg to 89.5 kg (3.9% ABD Pu). The addition of all of the ABD increases overall projected SB11 uranium mass from 4,740 kg to 16,100 kg (70% ABD U) and the projected plutonium mass from 86.0 kg to 90.4 kg (5.3% ABD Pu). The 235 U enrichment will be ≤5%. The fissile uranium will be adequately poisoned by Gd and the fissile Pu will be adequately poisoned by Fe from the sludge. [Gap closed for SB11]; There is a low risk that ABD addition will impact the rheology or pumpability of the slurry. There is a low but higher risk of ABD addition prior to LTAD impacting the settling rate; Based on the evaluation of adding two-thirds of the ABD material and all of the ABD material prior to the LTAD process, there is no volume or mass limit that would need to be imposed on ABD additions prior to LTAD. [Gap closed for SB11]. Revision 1 of this report addresses a variation on the ABD additions and LTAD strategy where sodium hydroxide additions for LTAD may be performed intermittently or concurrently with an ABD addition window. The proposed change does not alter the conclusions of this evaluation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li 7 La 3 Zr 2 O 12 solid electrolytes

Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.

25 ENERGY STORAGE↗