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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The evolution of the Milky Way’s thin disc radial metallicity gradient with K2 asteroseismic ages

ABSTRACT The radial metallicity distribution of the Milky Way’s disc is an important observational constraint for models of the formation and evolution of our Galaxy. It informs our understanding of the chemical enrichment of the Galactic disc and the dynamical processes therein, particularly radial migration. We investigate how the metallicity changes with guiding radius in the thin disc using a sample of red giant stars with robust astrometric, spectroscopic, and asteroseismic parameters. Our sample contains 668 stars with guiding radii 4 < Rg < 11 kpc and asteroseismic ages covering the whole history of the thin disc with precision ${\approx} 25 {{\, \rm per\ cent}}$. We use MCMC analysis to measure the gradient and its intrinsic spread in bins of age and construct a hierarchical Bayesian model to investigate the evolution of these parameters independently of the bins. We find a smooth evolution of the gradient from ≈−0.07 dex kpc−1 in the youngest stars to ≈−0.04 dex kpc−1 in stars older than 10 Gyr, with no break at intermediate ages. Our results are consistent with those based on asteroseismic ages from CoRoT, with that found in Cepheid variables for stars younger than 1 Gyr, and with open clusters for stars younger than 6 Gyr. For older stars we find a significantly lower metallicity in our sample than in the clusters, suggesting a survival bias favouring more metal-rich clusters. We also find that the chemical evolution model of Chiappini '09 is too metal poor in the early stages of disc formation. Our results provide strong new constraints for the growth and enrichment of the thin disc and radial migration, which will facilitate new tests of model conditions and physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Electron microscopy characterization of the fuel-cladding interaction in medium burnup annular fast reactor MOX

In this work, we present electron microscopy data focused on the fuel-cladding interaction layer in annular fast reactor MOX with HT-9 cladding at medium burnup. In agreement with previous literature data, the volatile fission products Cs, Te and I have migrated radially into the extreme fuel periphery and partially interacted with the cladding. The accumulation of Cs has occurred in the outermost rim of the fuel pellet, where grain recrystallization has also been observed. Significant amounts of Pd have been found in the interaction zone, particularly in the sample taken from the upper half of the fissile column where the cladding temperatures are higher. At this axial location, Cr has been enriched at the cladding inner surface and diffused into the fuel. Furthermore, chromium remains mainly in metallic form, but locally formed oxides. The fission products Cs, Te and I are found, with variable composition, in form of nanocrystalline regions dispersed in the metallic Cr-rich layer. The morphology and chemical characteristics of the layer suggest a non-oxidative corrosion mechanism as principal cladding degradation phenomenon occurring in this sample, with local onset of Cr oxidation within the nanocrystalline precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The ongoing need for high-resolution regional climate models: Process understanding and stakeholder information

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. High resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding regional climate variability and change, and are critical for supporting societal responses to changing climate.

Gutowski, William↗
DOE OSTI2017

The Influence of Microstructure on Deuterium Retention in Polycrystalline Tungsten

The retention of hydrogen isotopes in the plasma-facing materials of a fusion reactor is dependent on the density of trapping sites in the material. One factor that can influence the trapping defects is the surface state of the material before exposure. Mechanically polished, electropolished, and recrystallized tungsten samples were compared by exposing them to 350 eV D + beams with peak fluences of ~1 × 10 24 D + /m 2 at 500 and 740 K at the Multicharged Ion Research Facility (MIRF). At the exposure temperature of 740 K, no significant retention was detected. For material exposed at 500 K, significant differences in retention were observed, and the order of increasing retention was recrystallized, electropolished, and mechanically polished. Lastly, the other variable besides surface treatment was the time delay between ion exposure and thermal desorption spectroscopy which also may have impacted the retention measurements if there was out-gassing of the D while samples were in storage before thermal desorption spectroscopy (TDS).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Temporal Study 2022-2024: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, Chlorophyll A, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions This dataset contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Searches for physics beyond the standard model with the M T2 variable in hadronic final states with and without disappearing tracks in proton–proton collisions at $\sqrt{s}$ = 13 TeV

Two related searches for phenomena beyond the standard model (BSM) are performed using events with hadronic jets and significant transverse momentum imbalance. The results are based on a sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment at the LHC in 2016-2018 and corresponding to an integrated luminosity of 137 fb$^{-1}$. The first search is inclusive, based on signal regions defined by the hadronic energy in the event, the jet multiplicity, the number of jets identified as originating from bottom quarks, and the value of the kinematic variable $M_\mathrm{T2}$ for events with at least two jets. For events with exactly one jet, the transverse momentum of the jet is used instead. The second search looks in addition for disappearing tracks produced by BSM long-lived charged particles that decay within the volume of the tracking detector. No excess event yield is observed above the predicted standard model background. This is used to constrain a range of BSM models that predict the following: the pair production of gluinos and squarks in the context of supersymmetry models conserving $R$-parity, with or without intermediate long-lived charginos produced in the decay chain; the resonant production of a colored scalar state decaying to a massive Dirac fermion and a quark; or the pair production of scalar and vector leptoquarks each decaying to a neutrino and a top, bottom, or light-flavor quark. In most of the cases, the results obtained are the most stringent constraints to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Spatio-temporal microbial community dynamics within soil aggregates

Soil microbial communities are highly spatially organized, shaped in part by the structure of soil itself. Understanding how spatially discrete microbial communities change across years and seasons in response to environmental factors, plant phenology and aggregate turnover, is key to understanding how varying management practices impact the ecology of soil microbial communities. We investigated both seasonal (within year) and annual (across sampling years) changes of discrete microbial communities in soil aggregate fractions, large macroaggregates (LM) and microaggregates (MICRO) in three different bioenergy management systems. We hypothesized that 1) seasonal changes due to plant phenology and aggregate turnover will be most pronounced within the MICRO aggregate soil microbial community; 2) inter-annual variability will lead to changes in microbial diversity across aggregate sizes and the magnitude of change will be mediated by management regime. We found that LM and MICRO aggregates have unique microbial communities within soil. MICRO aggregate microbial communities are more diverse and change more dynamically across the sampling season, peaking in diversity at peak plant growth and maximum biomass. The number of families indicative of specific MICRO aggregate habitats increases over the growing season for both bacteria (from 3 to 51) and fungi (from 8 to 14). The LM aggregates harbored less diverse, yet more stable, communities within a growing season. By contrast, between years the LM aggregates were the most responsive to inter-annual variability. Our study demonstrates the importance of including the spatio-temporal dynamics of soil microbes. We identified “hot spots” of microbial diversity within soil, with a greater diversity of microbes found under prairies, within the MICRO aggregates, and seasonally during peak plant biomass. Targeted analysis of the MICRO aggregates can contribute to deeper understanding of potential diversity and functioning of soil microbial communities for ecosystem maintenance as well as the response to climatic events and environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Revealing the complex chemistry of grain boundaries in K-doped BaFe 2 As 2 with atom probe tomography

Iron-based superconductors have attractive properties for high-field applications, but there is a lack of understanding of the effect of grain boundary chemistry on the in-field performance. The near atomic-scale resolution, ppm sensitivity and 3D analysis offered by atom probe tomography make it a powerful tool to investigate the nanoscale structure and chemistry of these defects in fine-grained K-doped BaFe 2 As 2 samples. A computational method to systematically extract and compare the Gibbsian interfacial excess of chemical species across grain boundaries has been explored in this work. The robustness of the method has been tested by evaluating the effects of selected variables on simulated APT datasets. The accuracy and precision of the calculated Gibbsian interfacial excess were found to be stable over a range of analysis conditions: varying grain boundary widths and detection efficiencies, spatial precisions below 1.5 nm, and bin widths between 1.2 and 1.6 nm. For the K-doped BaFe 2 As 2 samples studied, segregation of As, Ba, K and impurities of O, Na, and Sb were found at grain boundaries. The Gibbsian excess values were found to vary widely between different boundaries, showing the complexity of the grain boundary chemistry in this material. Possible links between the observed critical current density (Jc) of these samples and their nano- and micro-structure have also been investigated and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework

Ice microphysics parameterizations in models must make major simplifications relative to observations, typically employing empirical relationships to represent average functional properties of particles. However, previous studies have established that ice particle properties vary even in similar cloud types and thermodynamic environments, and it remains unclear how this so-called “natural variability” impacts simulated deep convection. This uncertainty is addressed by implementing a stochastic framework into the Predicted Particle Properties microphysics scheme in the Weather Research and Forecasting model. The approach stochastically varies the coefficients of the mass-size (m-D) relationship (m=aD b ) for unrimed and partially rimed ice. Using guidance from aircraft in situ measurements obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), the scheme samples from distributions of the prefactor (a) and the exponent (b) of the m-D relationship. Simulations of two MC3E deep convective cases indicate that the stochastic m-D scheme produces considerable variability of anvil cirrus cloud optical depth (τ) distributions, even for the same ice water path (IWP). Thus, the stochastic scheme produces variable cloud radiative forcing that is independent of IWP. This τ-IWP relationship variability is nonexistent using the deterministic m-D ensemble. Additional sensitivity tests are performed in which the fallspeed-size relationship (V=cD d ) is stochastically varied, resulting in variable precipitation amounts and rain rate distributions. Results are presented in the context of satellite and precipitation observations and include comparison with other ensemble configurations using perturbed initial and lateral boundary conditions and small-amplitude noise added to the potential temperature field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Median Isn’t the Message: soil nutrient hot spots have a disproportionate influence on biogeochemical structure across years, seasons, and depths

Abstract Soil nutrient distribution is heterogeneous in space and time, potentially altering nutrient acquisition by trees and microorganisms. Ecologists have distinguished “hot spots” (HSs) as areas with enhanced and sustained rates of nutrient fluxes relative to the surrounding soil matrix. We evaluated the spatial and temporal patterns in nutrient flux HSs in two mixed-conifer forest soils by repeatedly sampling the soil solution at the same spatial locations (horizontally and vertically) over multiple seasons and years using ion exchange resins incubated in situ. The climate of these forests is Mediterranean, with intense fall rains occurring following summers with little precipitation, and highly variable winter snowfall. Hot spots formed most often for NO 3 − and Na + . Although nutrient HSs often occurred in the same spatial location multiple times, HSs persisted more often for PO 4 3− NH 4 + , and NO 3 − , and were more transient for Ca 2+ , Mg 2+ , and Na + . Sampling year (annual precipitation ranged from 558 to 1223 mm) impacted the occurrence of HSs for most nutrients, but season was only significant for PO 4 3− , NH 4 + , NO 3 − , and Na + , with HSs forming more often after fall rains than after spring snowmelt. The frequency of HSs significantly decreased with soil depth for all nutrients, forming most commonly immediately below the surficial organic horizon. Although HSs accounted for less than 17% of the sampling volume, they were responsible for 56–88% of PO 4 3− , NH 4 + , and NO 3 − resin fluxes. Our results suggest that macronutrient HSs have a disproportional contribution to soil biogeochemical structure, with implications for vegetation nutrient acquisition strategies and biogeochemical models. Graphical abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Combined Machine Learning and High-Energy X-ray Diffraction Approach to Understanding Liquid and Amorphous Metal Oxides

Determining the structure-property relations of liquid and amorphous metal oxides is challenging, due to their variable short-range order and polyhedral connectivity. To predict chemically realistic structures, we have developed a Machine Learned, Gaussian Approximation Potential (GAP) for HfO 2 , with a focus on enhanced sampling of the training database and accurate density functional theory calculations. By using training datasets for the GAP model at the level of Density Functional Theory-Strongly Constrained and Appropriately Normed (DFT-SCAN) level of theory, our results show that the topology of both the low viscosity liquid and the amorphous form are dominated by edge-shared chains and small corner-shared rings of polyhedra. This topology is shown to be consistent with the structure of other liquid and amorphous transition metal oxides of variable ion size, such as TiO 2 and ZrO 2 . Current limitations of the ML-GAP modeling method for obtaining glass structures and future perspectives are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling and Simulation of High-Frequency Solar Irradiance

As the use of solar power as a source of electricity is increasing, so is the interest in modeling radiation at high temporal resolutions. High-dimensional remote sensing data products depend on cloud cover variability, atmosphere aerosol levels, and other atmospheric parameters. Because of weather fronts and aerosols, it is difficult to quantify solar power variability based on distributed solar networks. The global horizontal irradiance (GHI) component in the National Solar Radiation Database (NSRDB) is available at a 30-min time resolution. The algorithm proposed in this paper produces 1-min-resolution GHI samples at locations where NSRDB data are available. The synthetic irradiance datasets are produced using log-additive non-Gaussian mixture models and resampling techniques. The model is trained over historical data, and predicted values are compared with in situ data. This approach allows for estimating the solar irradiance at subhourly temporal resolutions, while featuring variability for locations where measurements are otherwise not available.

14 SOLAR ENERGY↗
DOE OSTI2017

Installing Deep Groundwater Monitoring Wells in a Volcanic Dominated Rift Basin: Los Alamos National Laboratory, New Mexico - 17594

Los Alamos National Laboratory (LANL, or the Laboratory) is located in northern New Mexico near the west margin of the Espanola Basin. LANL is underlain by a complex basin-fill sequence of alluvial fan deposits, volcanic tuff, basaltic and dacitic lavas, and riverine deposits. On-going environmental remediation and characterization activities have evolved to improve the performance of groundwater monitoring wells, ensuring they yield representative groundwater and core samples. Groundwater occurs as canyon-fill alluvial water, perched intermediate-depth water associated with the basalts and other local-scale perching horizons, and as a regional-scale aquifer that is the main water supply for the area. Anthropogenic contaminants are found in all three groundwater zones. The regional aquifer below LANL is nominally 1000-1400 feet below ground surface (bgs). Monitoring wells at the Laboratory, are therefore, among the deepest routinely installed in the US. Logistical challenges at LANL include steep terrain, widespread cultural sites, and threatened and endangered species habitat restrictions. Additionally, the cost of installing monitoring wells is high because of groundwater depths and the variable drilling techniques that are required to characterize and install wells in a complex geologic environment. A major challenge to the characterization approach at LANL has been to meet sample quality requirements while minimizing drilling costs. In the late 1990's threaded drill-casing was advanced by rotary drilling methods using compressed air as the only circulation fluid. This resulted in relatively low impacts to the geochemical integrity of rock and groundwater samples, but led to frequent episodes of stuck casing. Additional fluids were introduced to the air-rotary program, improving penetration rates, but also resulting in non-representative groundwater samples due to long-term impacts to the aquifer in the vicinity of the well screen. Mud-rotary drilling was incorporated into the program, but it also had significant long-term impacts on groundwater quality, and often inhibited identification of perched groundwater zones and accurate identification of the water table in the regional aquifer. Current drilling practice makes limited use of fluid additives (e.g. foam) to supplement air circulation methods in order to advance drill casing through the vadose zone. Starting about 100 feet above the water table, drill casing is advanced to the target horizon in the regional aquifer using only air and municipal water (when needed) for circulation. Additionally, the threaded drill casing couplings have been replaced with welded connections, significantly reducing the occurrence of stuck casing. Careful observations of water production and water levels during drilling, coupled with the ability to retract casing for video and geophysical logs, now allows for robust characterization of perched groundwater systems and accurate definition of the top of regional saturation. Recent advances in the drilling program include combined dual-rotary/sonic drilling to depths up to 1150 feet and dual-rotary casing advance at angles up to 25 deg. from vertical. The former allows for core collection with minimal fluid addition, thereby preserving pore water chemistry. The latter method allows for well installation into portions of the aquifer otherwise inaccessible due to constraints at the surface (e.g., cultural sites or topography). Similar to the development of drilling techniques, both well design and groundwater sampling system design have evolved throughout the program. Current well design emphasizes a minimal annulus of filter pack, maximum screen slot size based on formation sieve analyses, and thorough well development to mitigate formation damage due to drilling. To sample groundwater at multiple levels in the same well, earlier sampling systems included Westbay{sup R} multi-zone systems and dual-screen single-pump and dual-screen dual-pump systems designed in collaboration with Baski, Inc. These multi-zone sampling systems proved difficult to develop and maintain given the depth to groundwater, and most current well installations are configured with a single screen and a submersible pump. The ability to purge from a well-developed single-screen well has substantially improved the collection of representative groundwater samples. A carefully crafted groundwater characterization program in target aquifers at depths ranging from 1,000 to 1,400 feet bgs within a complex geologic setting, while also retaining the ability to collect representative core and groundwater samples, may have application at a number of sites throughout the environmental industry. Optimizing each well to meet program objectives while reducing total project costs benefits all environmental investigations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Western North Pacific Tropical Cyclone Model Tracks in Present and Future Climates

Western North Pacific tropical cyclone (TC) model tracks are analyzed in two large multimodel ensembles, spanning a large variety of models and multiple future climate scenarios. Two methodologies are used to synthesize the properties of TC tracks in this large data set: cluster analysis and mass moment ellipses. First, the models' TC tracks are compared to observed TC tracks' characteristics, and a subset of the models is chosen for analysis, based on the tracks' similarity to observations and sample size. Potential changes in track types in a warming climate are identified by comparing the kernel smoothed probability distributions of various track variables in historical and future scenarios using a Kolmogorov-Smirnov significance test. Two track changes are identified. The first is a statistically significant increase in the north-south expansion, which can also be viewed as a poleward shift, as TC tracks are prevented from expanding equatorward due to the weak Coriolis force near the equator. The second change is an eastward shift in the storm tracks that occur near the central Pacific in one of the multimodel ensembles, indicating a possible increase in the occurrence of storms near Hawaii in a warming climate. The dependence of the results on which model and future scenario are considered emphasizes the necessity of including multiple models and scenarios when considering future changes in TC characteristics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗
DOE OSTI2023

Automatic detection of cataclysmic variables from SDSS images

Abstract Investigating rare and new objects have always been an important direction in astronomy. Cataclysmic variables (CVs) are ideal and natural celestial bodies for studying the accretion process of semi-detached binaries with accretion processes. However, the sample size of CVs must increase because a lager gap exists between the observational and the theoretical expanding CVs. Astronomy has entered the big data era and can provide massive images containing CV candidates. CVs as a type of faint celestial objects, are highly challenging to be identified directly from images using automatic manners. Deep learning has rapidly developed in intelligent image processing and has been widely applied in some astronomical fields with excellent detection results. YOLOX, as the latest YOLO framework, is advantageous in detecting small and dark targets. This work proposes an improved YOLOX-based framework according to the characteristics of CVs and Sloan Digital Sky Survey (SDSS) photometric images to train and verify the model to realise CV detection. We use the Convolutional Block Attention Module to increase the number of output features with the feature extraction network and adjust the feature fusion network to obtain fused features. Accordingly, the loss function is modified. Experimental results demonstrate that the improved model produces satisfactory results, with average accuracy (mean average Precision at 0.5) of 92.0%, Precision of 92.9%, Recall of 94.3%, and $F1-score$ of 93.6% on the test set. The proposed method can efficiently achieve the identification of CVs in test samples and search for CV candidates in unlabeled images. The image data vastly outnumber the spectra in the SDSS-released data. With supplementary follow-up observations or spectra, the proposed model can help astronomers in seeking and detecting CVs in a new manner to ensure that a more extensive CV catalog can be built. The proposed model may also be applied to the detection of other kinds of celestial objects.

Astronomy & Astrophysics↗
DOE OSTI2019

Radiation damage effects in chlorite investigated using microfocus synchrotron techniques

A detailed understanding of the mechanisms and effects of radiation damage in phyllosilicate minerals is a necessary component of the evaluation of the safety case for a deep geological disposal facility (GDF) for radioactive waste. Structural and chemical changes induced by a-particle damage will affect these mineral’s performance as a reactive barrier material (both in the near and far-field) over timescales relevant to GDF integrity. In this study, two examples of chlorite group minerals have been irradiated at a-particle doses comparable to those predicted to be experienced by the clay buffer material surrounding high level radioactive waste canisters. Crystallographic aberrations induced by the focused 4He2+ ion beam are revealed via high-resolution, microfocus X-ray diffraction mapping. Interlayer collapse by up to 0.5 Å is prevalent across both macro- and micro-crystalline samples, with the macro-crystalline specimen displaying a breakdown of the phyllosilicate structure into loosely-connected, multi-oriented crystallites displaying variable lattice parameters. The damaged lattice parameters suggest a localised breakdown and collapse of the OH- rich, ‘brucite-like’ interlayer. Microfocus Fe K-edge X-ray absorption spectroscopy illustrates this defect accumulation, manifest as a severe damping of the X-ray absorption edge. Subtle Fe2+/Fe3+ speciation changes are apparent across the damaged structures. A trend towards Fe reduction is evident at depth in the damaged structures at certain doses (8.76 x 1015 alpha particles/ cm2). Interestingly, this reductive trend does not increase with radiation dose, indeed at the maximum dose (1.26 x 1016 alpha particles/ cm2) administered in this study, there is evidence for a slight increase in Fe binding energy, suggesting the development of a depth-dependant redox gradient concurrent with light ion damage. At the doses examined here, these damaged structures are likely highly reactive, as sorption capacity will, to an extent, be largely enhanced by lattice disruption and an increase in available ‘edge’ sites.

Bower, William R.↗
DOE OSTI2024

Metadynamics investigation of lanthanide solvation free energy landscapes and insights into separations energetics

Lanthanide ion solvation chemistry in nonaqueous phases is key to understanding and developing effective separation processes for these critical materials. Due to the complexity and inherent disorder of the solution phase, a comprehensive picture of the solvated metal ion is often difficult to generate solely from conventional spectroscopic approaches and electronic structure calculations, particularly in the extractant phase. In this work, we use classical molecular dynamics (MD) simulation with an advanced sampling technique, metadynamics, supplemented by experimental spectroscopy and speciation analysis, to measure lanthanide solvation free energy landscapes. We define coordination-based collective variables to probe the entire range of solvation configurations in the organic phase of lanthanum (La), europium (Eu), and lutetium (Lu) nitrate salts bound with a commonly used extractant, N,N′-dimethyl, N,N′-dioctylhexylethoxymalonamide (DMDOHEMA). The known lanthanide extraction trend of La ≈ Eu > Lu is readily explained by the measured free energy surfaces, which show consistent DMDOHEMA coordination from La to Eu, followed by loss of DMDOHEMA coordination from Eu to Lu. These simulations suggest how ligand crowding at the metal center can control selectivity, in this case resulting in the opposite extraction trend as observed with other conventional extractants, where the enthalpic contribution from increasing lanthanide charge density across the series dominates the extraction energetics. We also find that the presence of inner-sphere water, verified by time-resolved fluorescence, diversifies the accessible solvation structures. As a result, understanding solvation requires consideration of an entire thermodynamic ensemble, rather than the single dominant lowest-energy structure, as is often considered out of necessity in interpretation of spectroscopic data or in electronic structure-based ligand design approaches. In general, we demonstrate how metadynamics uniquely enables investigation of complex, multidimensional solvation energetic landscapes, and how it can explain selectivity trends where extraction is controlled by more complex mechanisms than simple charge density-based selectivity.

Wang, Xiaoyu↗