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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Core-flood Effluent and Shale Surface Chemistries in Predicting Interaction between Shale, Brine, and Reactive Fluid

We report field and laboratory observations to date indicate that the efficiency of hydraulic fracturing, as it relates to hydrocarbon recovery, depends significantly on geochemical alterations to rock surfaces that diminish accessibility by partial or total plugging of the pore and fracture networks. This is caused by mineral scale deposition such as coating of fracture surfaces with precipitates, particle migration, and/or crack closure due to dissolution under stress. In reactive flow-through experiments, mineral reactions in response to acidic fluid injection significantly reduced system porosity and core permeability. The present study focuses on changes to fluid chemistry and shale surfaces (inlet and fracture walls) resulting from shale-fluid interactions and integrating these findings for an improved estimate of transport-related consequences. The reacted shale surfaces were examined by spatially-resolved scanning electron microscopy - energy dispersive spectroscopy (SEM-EDS) analysis. Importantly, inductively coupled plasma - mass spectrometry/optical emission spectroscopy (ICP-MS/OES) was utilized to probe the chemical evolution of the core-flood effluents. The three study cores selected from the Marcellus formation represent different mineralogies and structural features. In flow-through experiments, lab-generated brine and HCl-based fracture fluid (pH=2) were injected sequentially under effective stress (up to 500 psi) at reservoir temperature (80°C). SEM-EDS results confirmed by the ICP concentration trends showed significant Fe hydroxide precipitates in clay- and pyrite-rich outcrop samples due to partial oxidation of Fe-bearing phases in the case of intrusion of low salinity water-based fluids. Porosity reduction in the MSEEL (Marcellus Shale Energy and Environmental Laboratory) carbonate-rich sample is related to compaction of cores under stress due to matrix softening with substantial dissolution, and pore-filling by hydroxides, as well as barite and salts. Despite the same fluid compositions and experimental conditions used for both MSEEL samples, barite precipitation was much more intense in the MSEEL clay-rich sample due to its greater sorption capacity and additional sulfate source as well as fissile nature with multiple lengthwise cracks. ICP tests revealed time-resolved concentration trends in produced brine and reactive fluids that in turn complemented the pre-/post-reaction SEM-EDS observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Observation of Charmonium Sequential Suppression in Heavy-Ion Collisions at the Relativistic Heavy Ion Collider

We report measurements of charmonium sequential suppression in Ru+Ru and Zr+Zr collisions at $\sqrt{s_{NN}}$ =200 GeV with the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The inclusive yield ratio of 𝜓⁡(2⁢S) to J/𝜓 as a function of transverse momentum is reported, along with the centrality dependence of the double ratio, defined as the 𝜓⁡(2⁢S) to J/𝜓 ratio in heavy-ion collisions relative to that in 𝑝 +𝑝 collisions. In the 0–80% centrality class, the double ratio is found to be 0.41±0.10 (stat)±0.03 (syst)±0.02 (ref), lower than unity with a significance of 5.6 standard deviations. This provides experimental evidence that 𝜓⁡(2⁢S) is significantly more suppressed than J/𝜓 in heavy-ion collisions at RHIC. This sequential suppression pattern seems to increase from peripheral to central collisions, but with no significant dependence on the transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Data from a throughfall exclusion experiment: Fine root dynamics, morphology, chemistry, and AMF colonization across four lowland Panamanian forests

Fine roots regulate forest nutrient, carbon, and water cycling, yet their variation within and among tropical forests remains under-characterized. We quantified root productivity, disappearance, and stocks to 1 m using minirhizotron imaging, and we measured morphology, elemental composition [root carbon (C), root nitrogen (N), root phosphorus (P)], and arbuscular mycorrhizal fungi (AMF) colonization to 20 cm using ingrowth cores and sequential coring. Sampling took place in four distinct lowland Panamanian forests (32 plots; 8 per forest) from 2018 through 2022 under control and throughfall-exclusion (drought) treatments in the Panama Rainforest Changes with Experimental Drying (PARCHED) experiment.The dataset is presented as an Excel workbook with six tabs. The first tab is the data dictionary. Tab S1 contains ingrowth-core production and mortality, morphology and soil moisture. Tab S2 contains sequential-coring standing stocks with associated morphology and soil moisture. Tab S3 contains minirhizotron row data records to 1 m depth, including per-frame root length and diameter, normalized length metrics, and session timing. Tab S4 contains AMF colonization. Tab S5 contains fine-root chemistry at 0–10 cm, reporting %P, %C, %N, and C:N for samples collected via ingrowth cores and sequential-coring standing stocks. CSV mirrors for each tab are provided, and a KML file supplies coordinates for all 32 plots.Key variables span live and dead fine-root biomass (and coarse fractions where applicable), specific root length (SRL) and area (SRA), diameter, root tissue density (RTD), soil moisture, AMF colonization, root %N, %C, %P, and C:N, along with minirhizotron root length and diameter. Depth, season, treatment, and plot/site identifiers are included to support cross-tab integration and analysis from 0–100 cm (minirhizotron) and 0–20 cm (cores).Units are reported in-column and missing values are coded as NA. No special software is required to open or use the files (Excel, CSV, and KML compatible).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Inelastic Neutron Scattering Observation of Plasma-Promoted Nitrogen Reduction Intermediates on Ni/γ-Al 2 O 3

Plasma-assisted catalysis is an emerging technology for the atmospheric pressure and low bulk gas temperature synthesis of ammonia from molecular nitrogen and hydrogen. Direct evidence for plasma-induced surface reaction intermediates relevant to ammonia production, including surface hydrides and NH x (x = 1, 2, 3) species, has remained elusive. In this work, we report inelastic neutron scattering (INS) observations of alumina-supported Ni particles after treatment with N 2 and H 2 plasmas. INS experiments reveal the presence of NH x species and hydrides on Ni sites after exposure to sequential N 2 and H 2 plasma treatments. By separating exposure, we exclude the presence of plasma-phase reactions and demonstrate that these species are generated through plasma-facilitated surface reactions. Computed synthetic INS spectra of NH 3 , NH 2 and NH adsorbates on Ni support the experimental assignments of surface intermediates. The results directly implicate plasma stimulation of dinitrogen in generation of surface-bound nitrogen that participates in further hydrogenation reactions driven either thermally or with H 2 plasma.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Model for the Softening Factor within Stages of Work Hardening

A formulation for a dimensionless coefficient c b is derived that represents a scale of microstructural softening for alloys which follow Kocks-Mecking (K-M) work hardening behavior. The variation of the true plastic strain ε p between the proportional limit σ y and the strength σ u at the instability is determined using the Considère criterion. Parameterization of the model is limited to variables expressly measured within tensile experiments. Further development is now made for the softening factor c bi through the individual and sequential stages 3 and 4 of plastic deformation during K-M work hardening Q behavior. Application is shown for tensile test results of Ti-6Al-4V made by different additively manufactured (AM) processes. It is found that the variation in plastic strain as a function of c bi produces a continuous curve representative of the alloy system. The results of data analysis indicate that Θ o3 and c b3 increase, while Θ o4 and c b4 decrease, as the total plastic strain ε p increases. Furthermore, formulations derived for K-M stages 3 and 4 enable the evaluation of other material parameters such as the activation volume ν* for the onset of plastic deformation. This activation volume is found to be near constant, at a ν*-value of 0.353±0.036 nm 3 as computed using a strain-rate sensitivity of strength exponent m of 0.014, irrespective of the AM method used to produce the Ti-6Al-4V alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transfer learning for probabilistic localization of hidden cracks in concrete structures

Abstract The utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.

Miele, S.↗
DOE OSTI2023

Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate

In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining these in a systematic way for quantities of interest (QoI) remains a challenge. In this paper, we present a forward propagation uncertainty quantification (UQ) process to produce a probabilistic distribution for the observed regression rate r. We characterized two input data uncertainty sources from the experiment (the distortion from the camera U c and the non-zero-angle fuel placement U Y ), the prediction and model form uncertainty from the deep neural network (U m ), as well as the variability from the manually segmented images used for training it (U s ). Here, we conducted seven case studies on combinations of these uncertainty sources with the model form uncertainty. The main contribution of this paper is the investigation and inclusion of the experimental image data uncertainties involved, and how to include them in a workflow when the QoI is the result of multiple sequential processes.

42 ENGINEERING↗
DOE OSTI2024

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

CO2 Capture Strategies via Mineralization with Industrial Waste Brines

Large coal-fired power plants (>500 MW) account for 30% of global CO2 emissions, and long-term management of this CO2 to is urgently needed mitigate global temperature increases. Sequestration of CO2 within stable mineral carbonates (e.g., CaCO3) represents an attractive emission reduction strategy because it offers a leakage-free alternative to geological storage of CO2 in an environmentally friendly form. We have previously described a mineralization process in which divalent cations are sourced from various waste streams (e.g., produced water and brackish water) and alkalinity is induced via regenerable ion-exchange materials (Bustillos et. al. Frontiers in Energy Research. 2020, 8, 352). In our process, aqueous carbonate-bearing streams with pH > 8 are produced by contacting fresh water and carbon dioxide with various ion-exchange materials (e.g., Na form zeolites or ion exchange resins). These streams are mixed with produced water containing varying concentrations (~0.01 – 1.0 M) of Ca2+ leading to the precipitation of solid calcium carbonate (PCC). This process has the advantages of using regenerable solids in a simple and continuous process to increase the pH of water by ion exchange instead of relying on the consumption of costly and unsustainable sources of alkalinity (e.g., sodium hydroxide). While once-through column experiments showed the above benefits, the same were yet to established in a steady-state process with recycle streams. In this work, we set up a process simulation to quantify the energy requirements and CO2 emissions associated with the process and seek optimal produced water compositions and CO2 concentrations (5 – 20 vol%). The process simulation was set up in ASPEN Plus using eRNTL as the thermodynamic property method and sequential modular strategy. Ion exchange alkaline solution was simulated using sodium hydroxide and validated against the experimental data obtained from once-through kinetic experiments. Nanofiltration and reverse osmosis membrane steps were also implemented for the separation of divalent cations and production of fresh water and a regeneration stream following mineralization. Sensitivity analysis was carried out using a range of produced water compositions (0.01 – 1.0 M Ca2+, 0.001 – 0.15 M Mg2+, 0.5 – 3.5 M Na+ and 0.0004 – 0.002 M Fe2+) according to the United States Geological Survey (USGS) database. Calcium carbonate yields increased with increasing CO2 concentrations and were maximized using produced water compositions with larger Ca2+ concentrations. Maximum calcium carbonate yields produced at 5 vol%, 12 vol% and 20 vol% CO2 were 2.3 mmol/L, 5.5 mmol/L, and 9.3 mmol/L, respectively, with the formation of brucite (a magnesium hydroxide phase, Mg(OH)2) and goethite (an iron hydroxide phase, FeOOH) as the primary contaminant phases (99% calcite, 0.6% brucite, 0.4% goethite), which agree with phases detected by XRD experimentally. These results indicate high purity calcium carbonate can be precipitated using industrial waste streams. Consequentially, energy consumption and net CO2 emissions were minimized where precipitated calcium carbonate was maximized for all produced water compositions and CO2 concentrations. Minimum energy consumptions were 0.21 kWh/ton CO2 processed, with 98% of the energy input required coming from the membrane filtration steps. Produced water compositions with large Na+ concentrations (> 0.5 M) were effective at reducing energy consumptions due to faster regeneration time of ion exchange materials. Additionally, calculated net CO2 emissions were negative for the process and ranged from -0.02 kg/ton CO2 to -0.15 kg/ton CO2 processed, indicating a low emission process. We will also present techno-economic assessment showing the economic benefits of the current process as an alternative to the addition of stoichiometric bases to induce alkalinity for the precipitation of CaCO3.

Simonetti, Dante↗
DOE OSTI2023

Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center‐Pivot Irrigation Water Use at High Spatio‐Temporal Resolution

Abstract Estimating irrigation water use accurately is critical for sustainable irrigation and studying terrestrial water cycle in irrigated croplands. However, irrigation is not monitored in most places, and current estimations of irrigation water use has coarse spatial and/or temporal resolutions. This study aims to estimate irrigation water use at the daily and field scale through the proposed model‐data fusion framework, which is achieved by particle filtering with two configurations (concurrent, CON, and sequential, SEQ) by assimilating satellite‐based evapotranspiration (ET) observations into an advanced agroecosystem model, ecosys . Two types of experiments using synthetic and real ET observations were conducted to study the efficacy of the proposed framework for estimating irrigation water use at the irrigated fields in eastern and western Nebraska, United States. The experiments using synthetic ET observations indicated that, for two major sources of uncertainties of ET difference between observations and model simulations, which are bias and noise, noise had larger impacts on degrading the estimation performance of irrigation water use than bias. For the experiments using real ET observations, monthly and annual estimations of irrigation water use matched well with farmer irrigation records, with Pearson correlation coefficient ( r ) around 0.80 and 0.50, respectively. Although detecting daily irrigation records was very challenging, our method still gave a good performance with RMSE, BIAS, and r around 2.90, 0.03, and 0.4 mm/d, respectively. Our proposed model‐data fusion framework for estimating irrigation water use at high spatio‐temporal resolution could contribute to regional water management, sustainable irrigation, and better tracking terrestrial water cycle.

Environmental Sciences & Ecology↗
DOE OSTI2023

Machine learning for automated experimentation in scanning transmission electron microscopy

Abstract Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centric experiment workflow design and optimization. Here, we discuss the associated challenges with the transition to active ML, including sequential data analysis and out-of-distribution drift effects, the requirements for edge operation, local and cloud data storage, and theory in the loop operations. Specifically, we discuss the relative contributions of human scientists and ML agents in the ideation, orchestration, and execution of experimental workflows, as well as the need to develop universal hyper languages that can apply across multiple platforms. These considerations will collectively inform the operationalization of ML in next-generation experimentation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Observations of twinning microstructure in iron ramp-compressed through the α – ε phase transition

Single crystal iron was ramp-compressed along the [100] axis at 4 GPa/ns through the α–ϵ phase transformation at 13 GPa. Unlike shock experiments, in these ramp compression experiments the bcc lattice is observed to be nearly isotropically relaxed before the phase transition. There was a mixed α/ϵ phase region starting at ~13 GPa which was observed for 0.75 ns until the peak stress of 18 GPa was reached. In situ x-ray diffraction measurements show the formation of new hcp orientations not reported in shock or quasistatic compression experiments. The new hcp orientations appear to be caused by {10¯11} <10¯1 ¯2> → {¯1011} <¯101¯2> sequential twins that occur during the phase transition. This twinning mechanism relieves the shear strain caused by the bcc-hcp phase transition from the isotropically relaxed bcc phase while subject to uniaxial compression. Furthermore, these results show that in iron the induced microstructure through a phase transition and the phase transition mechanism depend on the loading history.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Cylindrical Magnetron Development for Nb3sn Deposition via Magnetron Sputtering

Due to its better superconducting properties (critical temperature Tc~ 18.3 K, superheating field Hsh~ 400 mT), Nb₃Sn is considered as a potential alternative to niobium (Tc~ 9.25 K, Hsh~ 200 mT) for superconducting radiofrequency (SRF) cavities for particle acceleration. Magnetron sputtering is an effective method to produce superconducting Nb₃Sn films. We deposited superconducting Nb₃Sn films on samples with magnetron sputtering using co-sputtering, sequential sputtering, and sputtering from a stoichiometric target. Nb₃Sn films produced by magnetron sputtering in our previous experiments have achieved DC superconducting critical temperature up to 17.93 K and RF superconducting transition at 17.2 K. A magnetron sputtering system with two identical cylindrical cathodes that can be used to sputter Nb₃Sn films on cavities has been designed and is under development now. We report on the design and the current progress on the development of the system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Payload concepts for investigations of electrostatic dust motion on the lunar surface

Significant experimental and computational investigations have explored the feasibility of electrostatically-motivated dust motion on the lunar surface. The motion of lunar dust influences our understanding of the evolution of the surface and may also present a hazard to future exploration vehicles and astronauts. The possibility of a sustained exploration presence on the lunar surface opens the door to long-term experiments on the lunar surface, akin to the science facilities on the International Space Station. We have identified four measurements/observations that would significantly advance our understanding of dust-plasma interactions on the lunar surface. In this context, we provide conceptual designs for payloads to obtain these observations: a Langmuir probe, dust deposit witness plate, regolith charge measurement instrument, and cameras to look for evidence of horizon glow. These payloads could deploy independently and sequentially, or together as a suite. The proposed payloads would provide key observations that would inform future modeling efforts and direct future in situ experiments to understand the dust-plasma environment, both for planetary science and spacecraft design applications.

42 ENGINEERING↗
DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Exploratory Investigation of Coal in Nonequilibrium Plasma

Coal is an abundant natural resource and there is motivation to find new uses for it that do not intrinsically involve combustion. One approach is to explore new ways of processing coal, and in this work, we focus on the transformation of coal in a nonequilibrium plasma generated from an equimolar mixture of nitrogen and hydrogen. The outcome of the nonequilibrium plasma reaction is fundamentally different than a thermal control reaction carried out using the same gas composition, pressure, and temperature range. The nonequilibrium plasma produces a gas mixture that is enriched in acetylene and its derivatives. Furthermore, when compared to the thermal control experiment, the solid char byproduct of the nonequilibrium plasma has a very reactive surface and is spontaneously combustible at ambient temperature. Experiments performed to characterize the reaction kinetics of coal in the plasma suggest that the mechanism proceeds through a sequential process by which the coal particle temperature rises to a point where devolatilization can occur, the devolatilization reaction happens, followed by parallel reactions of released organic vapors in the plasma phase and surface activation. In conclusion, the reaction rate appears to be limited by the time it takes for the coal particle temperature to rise, consistent with previous results reported for reactions of coal in thermal plasma.

Acetylene↗
DOE OSTI2021

A correlation between grain boundary character and deformation twin nucleation mechanism in coarse-grained high-Mn austenitic steel

Abstract In polycrystalline materials, grain boundaries are known to be a critical microstructural component controlling material’s mechanical properties, and their characters such as misorientation and crystallographic boundary planes would also influence the dislocation dynamics. Nevertheless, many of generally used mechanistic models for deformation twin nucleation in fcc metal do not take considerable care of the role of grain boundary characters. Here, we experimentally reveal that deformation twin nucleation occurs at an annealing twin (Σ3{111}) boundary in a high-Mn austenitic steel when dislocation pile-up at Σ3{111} boundary produced a local stress exceeding the twining stress, while no obvious local stress concentration was required at relatively high-energy grain boundaries such as Σ21 or Σ31. A periodic contrast reversal associated with a sequential stacking faults emission from Σ3{111} boundary was observed by in-situ transmission electron microscopy (TEM) deformation experiments, proving the successive layer-by-layer stacking fault emission was the deformation twin nucleation mechanism, different from the previously reported observations in the high-Mn steels. Since this is also true for the observed high Σ-value boundaries in this study, our observation demonstrates the practical importance of taking grain boundary characters into account to understand the deformation twin nucleation mechanism besides well-known factors such as stacking fault energy and grain size.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Restoration Insights Gained from a Field Deployment of Dithionite and Acetate at a Uranium In Situ Recovery Mine

Mining uranium by in situ recovery (ISR) typically involves injecting an oxidant and a complexing agent to mobilize and extract uranium in a saturated ore zone. This strategy involves less infrastructure and invasive techniques than traditional mining, but ISR often results in persistently elevated concentrations of U and other contaminants of concern in groundwater after mining. These concentrations may remain elevated for an extended period without remediation. Here, we describe a field experiment at an ISR facility in which both a chemical reductant (sodium dithionite) and a biostimulant (sodium acetate) were sequentially introduced into a previously mined ore zone in an attempt to establish reducing geochemical conditions that, in principle, should decrease and stabilize aqueous U concentrations. While several lines of evidence indicated that reducing conditions were established, U concentrations did not decrease, and in fact increased after the amendment deployments. We discuss likely reasons for this behavior, and we also discuss how the results provide insights into improvements that could be made to the restoration process to benefit from the seemingly detrimental behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗