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At least 109 records · Page 6

Exploring the environmental drivers of vegetation seasonality changes in the northern extratropical latitudes: a quantitative analysis *

Abstract Vegetation seasonality in the northern extratropical latitudes (NEL) has changed dramatically, but our understanding of how it responds to climate change (e.g. temperature, soil moisture, shortwave radiation) and human activities (e.g. elevated CO 2 concentration) remains insufficient. In this study, we used two remote-sensing-based leaf area index and factorial simulations from the TRENDY models to attribute the changes in the integrated vegetation seasonality index ( S ), which captures both the concentration and magnitude of vegetation growth throughout the year, to climate, CO 2 , and land use and land cover change (LULCC). We found that from 2003 to 2020, the enhanced average S in the NEL (MODIS: 0.0022 yr −1 , p < 0.05; GLOBMAP: 0.0018 yr −1 , p < 0.05; TRENDY S3 [i.e. the scenario considering both time-varying climate, CO 2 , and LULCC]: 0.0011 ± 7.5174 × 10 −4 yr −1 , p < 0.05) was primarily determined by the elevated CO 2 concentration (5.3 × 10 −4 ± 3.8 × 10 −4 yr −1 , p < 0.05) and secondly controlled by the combined climate change (4.6 × 10 −4 ± 6.6 × 10 −4 yr −1 , p > 0.1). Geographically, negative trends in the vegetation growth concentration were dominated by climate change (31.4%), while both climate change (47.9%) and CO 2 (31.9%) contributed to the enhanced magnitude of vegetation growth. Furthermore, around 60% of the study areas showed that simulated major climatic drivers of S variability exhibited the same dominant factor as observed in either the MODIS or GLOBMAP data. Our research emphasizes the crucial connection between environmental factors and vegetation seasonality, providing valuable insights for policymakers and land managers in developing sustainable ecosystem management strategies amidst a changing climate.

54 ENVIRONMENTAL SCIENCES↗

Michaelis-like complex of SARS-CoV-2 main protease visualized by room-temperature X-ray crystallography

SARS-CoV-2 emerged at the end of 2019 to cause an unprecedented pandemic of the deadly respiratory disease COVID-19 that continues to date. The viral main protease (M pro ) is essential for SARS-CoV-2 replication and is therefore an important drug target. Understanding the catalytic mechanism of M pro , a cysteine protease with a catalytic site comprising the noncanonical Cys145–His41 dyad, can help in guiding drug design. Here, a 2.0 Å resolution room-temperature X-ray crystal structure is reported of a Michaelis-like complex of M pro harboring a single inactivating mutation C145A bound to the octapeptide Ac-SAVLQSGF-CONH 2 corresponding to the nsp4/nsp5 autocleavage site. The peptide substrate is unambiguously defined in subsites S5 to S3′ by strong electron density. Superposition of the Michaelis-like complex with the neutron structure of substrate-free M pro demonstrates that the catalytic site is inherently pre-organized for catalysis prior to substrate binding. Induced fit to the substrate is driven by P1 Gln binding in the predetermined subsite S1 and rearrangement of subsite S2 to accommodate P2 Leu. The Michaelis-like complex structure is ideal for in silico modeling of the SARS-CoV-2 M pro catalytic mechanism.

3CL protease↗

materialsCloudCompute

materialsCloudCompute (mCC) is a software package for running easily parallelizable materials science theoretical computations on Amazon Web Services (AWS) infrastructure. mCC provides tools to partition out computational problem into smaller subproblems which can be run in parallel, and ensure that each of those subproblems completes successfully. It utilizes the following AWS services: EC2, S3, and RDS. It operates by launch a managing EC2 instance, which can launch worker instances that perform the calculations. The Managing instance tracks the subproblems and ensures that the Worker instances continue to operation, killing and relaunching them if they fail.

Forbes, David↗

VISTA

SAND2025-14753O VISTA Image Management is a tool that serves as a thin wrapper around S3 storage, enabling teams to create projects, upload images, and add labels to data. It uses standard open-source libraries, employs conventional authentication and authorization methods, and is expected to run behind a reverse proxy that handles authentication. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Garland, Anthony [Sandia National Lab. (SNL-CA), L↗

Land productivity and land availability for growing bioenergy crop in the Contiguous US. Center for Advanced Bioenergy and Bioproducts Innovation (CABBI)

The dataset consists of two types of data: the estimate of land productivity (the maximum productivity, MP) and the estimate of land that has low productivity for any major crops planted in the Contiguous United States and then may be available for growing bioenergy crops (the marginal land, ML). All data items are in GeoTiff format, under the World Geodetic System (WGS) 84 project, and with a resolution of 0.0020810045 degree (~250 m). The MP values are calculated based on machine learning model estimated yields of major crops in the CONUS, and its expected value (MP_mean.tif), and associated uncertainty (MP_IDP.tif). The ML availability data have two versions: a deterministic version and a version with uncertainty. The deterministic MLs are determined as the land pixels with expected MP values falling in the range defined in the following criteria, and the MLs with uncertainty are determined as the probability that the MP value of a land pixel falls in the range defined in the following criteria: Criteria_____Description S1________ Current crop and pasture land with MP <= P50 S2________ Current crop and pasture land with MP <= P25 S3________ S1 + current grass and shrub land with P25 < MP < P50 S4________ S2 + current grass and shrub land with P10 < MP < P25 Economic__ Current crop and pasture land with potential profitability < 0 Here P10, P25 and P50 are the 10th, 25th and 50th percentile of crop MP values

Land productivity↗

Disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y alloys

This dataset contains input and output files from density functional theory (DFT) simulations used to study the disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y (0 ≤ x + y ≤ 1) alloys and their binary end members MnTe, MnSb, and MnBi. The alloys adopt the hexagonal NiAs-type (nickeline) structure and span ternary (MnTexSb1-x, MnTexBi1-x, MnBixSb1-x), and quaternary compositions across the full MnTe–MnSb–MnBi composition triangle. For each alloy composition, the dataset provides DFT calculations in three magnetic configurations: A-type antiferromagnetic (AFM), C-type AFM, and ferromagnetic (FM). Every magnetic configuration folder contains the fully relaxed crystal structure (CONTCAR), VASP input parameters (INCAR), and the main VASP output file (OUTCAR), from which total electronic energies, Mn magnetic moments, lattice parameters, and percent volume changes between magnetic states are extracted. These data are used to construct compositional phase diagrams, evaluate thermodynamic stability (formability), and map magnetoelastic responses across the alloy space. For A-type AFM and FM configurations, additional data are provided as follows: (i) FORCE_CONSTANTS and thermal_properties.yaml files at the top level of A-type_AFM/ and FM/ folders — present only for compositions marked with an asterisk (*) in Table I of the main text. These are derived from Phonopy finite-displacement calculations on full disordered 128-atom supercells and provide vibrational free energy, entropy (Svib)contribution from explicit disorder calculations. (Table I of the associated main manuscript) (ii) A VCA/ subfolder within A-type_AFM/ and FM/, containing FORCE_CONSTANTS and thermal_properties.yaml from Virtual Crystal Approximation phonon calculations (without spin-orbit coupling). VCA data are available for all compositions and are used to estimate vibrational contributions to the Gibbs free energy across the full composition space. (iii) A SOC/ subfolder containing CONTCAR, INCAR, and OUTCAR from spin-orbit coupling calculations, providing relativistic corrections to electronic energies and lattice parameters (Tables S2–S3 of the SM, and Table I of the main manuscript). (iv) A SOC/VCA/ subfolder containing FORCE_CONSTANTS and thermal_properties.yaml from VCA phonon calculations performed within the SOC framework, combining relativistic and vibrational thermodynamic corrections. The computed properties are used to map the AFM–FM magnetic crossover near MnTe0.75Sb0.25, demonstrate disorder- and spin-induced phonon broadening, identify a semiconductor-to-metal crossover, and quantify the pronounced magnetoelastic volume response near the magnetic phase boundary.

36 MATERIALS SCIENCE↗

covariance libs

This dataset contains covariance libraries created for SCALE. These will be distributed by providing documentation and metadata in GitLab repos hosted by ORNL (code.ornl.gov/scale/data/cov-libs), and the main datasets are hosted in S3-based ORNL servers. The data are also contained in Constellation. More documentation can be found in PUB ID 263037.

Brown, Jesse [ORNL] (ORCID:0000000207694100)↗

GSE Yearly Load Profiles for Each Airport Under Six Charging Scenarios

This dataset contains GSE yearly load profiles for each airport under six charging scenarios: (1) charging when the battery state of charge is insufficient for the next service using 40-kW chargers (S1); (2) charging when the battery state of charge is insufficient for the next service using 20-kW chargers (S2); (3) charging starts immediately after each GSE completes a service task using 40-kW chargers (S3); (4) charging starts immediately after each GSE completes a service task using 20-kW chargers (S4); (5) charging during off-peak hours using 40-kW chargers (S5); and (6) charging during off-peak hours using 20-kW chargers (S6). ![image](gse_load_profile_sample_day.png) GSE load profile of a sample day across different airport categories under charging scenario 1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Charger Requirements for GSE at Each Airport

This dataset contains the required number of chargers for GSE at each airport under six charging scenarios: (1) charging when the battery state of charge is insufficient for the next service using 40-kW chargers (S1); (2) charging when the battery state of charge is insufficient for the next service using 20-kW chargers (S2); (3) charging starts immediately after each GSE completes a service task using 40-kW chargers (S3); (4) charging starts immediately after each GSE completes a service task using 20-kW chargers (S4); (5) charging during off-peak hours using 40-kW chargers (S5); and (6) charging during off-peak hours using 20-kW chargers (S6).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fleet Size Requirements for Each GSE Type at Each Airport

This dataset contains the required number of vehicles for each GSE type at each airport under six charging scenarios: (1) charging when the battery state of charge is insufficient for the next service using 40-kW chargers (S1); (2) charging when the battery state of charge is insufficient for the next service using 20-kW chargers (S2); (3) charging starts immediately after each GSE completes a service task using 40-kW chargers (S3); (4) charging starts immediately after each GSE completes a service task using 20-kW chargers (S4); (5) charging during off-peak hours using 40-kW chargers (S5); and (6) charging during off-peak hours using 20-kW chargers (S6). ![image](gse-vehicles-chargers.png) Number of GSE vehicles per GSE type and chargers required for different airport categories under charging scenario 1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Data associated with Quaternary Research manuscript Latest Pleistocene glacial chronology and paleoclimate reconstruction for the East River watershed, Colorado, USA

The data here are associated with Quaternary Research manuscript Latest Pleistocene glacial chronology and paleoclimate reconstruction for the East River watershed, Colorado, USA and include data associated with cosmogenic exposure and depth profile dating as well as glacier-climate numerical modeling. Reconstructing Pleistocene glaciation timing and extent is vital for understanding paleoclimate. While late Pleistocene glaciation has been studied extensively in western North American mountain ranges, the glacial history of the western Elk Range in Colorado remains understudied, particularly in the East River watershed, a site of intense scientific focus. Here we use cosmogenic nuclide exposure and depth–profile dating methods to determine the timing of glaciation in the East River watershed. We use glacier modeling to reconstruct paleoglacier extents and quantify past climate conditions. Our findings indicate that the East River glacier retreated from its maximum position approximately 17–18 ka, moving to recessional positions between 13–15 ka, before experiencing more substantial retreat to high-elevation cirques around 12.9 ka. Glacier modeling suggests that the maximum ice extents at 17–18 ka could have been sustained by temperature depressions of approximately −6.5°C compared to modern conditions, assuming consistent precipitation. Additionally, the ice position at 13–15 ka could have been supported by temperature depressions of around −4.0°C. These results offer insights into the deglaciation timeline in the East River watershed and broader western Elk Range as well as paleoclimate conditions during the late Pleistocene, which may aid future research on critical zone evolution in the East River watershed.The data files include: 1. Table 1 In situ-produced 10Be sample data (.pdf, .csv, .xlsx)2. Table 2 In situ-produced 10Be exposure age results (.pdf, .csv, .xlsx)3. S1_A CRONUS calculator input assuming no erosion (.csv)4. S1_B CRONUS calculator input assuming erosion (.csv)5. S1_C CRONUS calculator results and comparison (.csv)6. S2_A In situ-produced 10Be sample data for depth profile (.csv)7. S2_B In situ-produced 10Be depth profile model input (.csv)8. S2_C In situ-produced 10Be depth profile model results (.csv)9. S3 Monthly cloudiness, rH, and windspeed data used in glacier climate model (.csv)10. S4 Glacier climate model results (.csv)

54 ENVIRONMENTAL SCIENCES↗

Calcium is associated with specific soil organic carbon decomposition products at Blodgett Forest Research Center, Georgetown, California as analysed with scanning transmission X-ray microscopy carbon near-edge X-ray absorption fine structure spectroscopy

This data is from the paper calcium is associated with specific soil organic carbon decomposition products, published in SOIL. DOI: https://doi.org/10.5194/soil-11-381-2025, 2025.This file contains CSVs with spectral data and bulk soil data and there is no specific program required to open this data. The data includes Scanning transmission X-ray microscopy carbon near-edge X-ray absorption fine structure spectroscopy. data from the measurement of samples from the Whole-soil Warming project, run by the Belowground Biogeochemistry team at Blodgett Forest Research Center, Georgetown, California run by the University of California, Berkeley. It also includes bulk soil chemical properties. The University of California's Blodgett Forest Research Station (Forest) is situated in the Sierra Nevada foothills (1370 m a.s.l.) near Georgetown, California. The samples were collected from here: 38.912013, -120.661469, https://maps.app.goo.gl/291bCJ1zVqUhgktz6. The Forest soils were characterised as Alfisols, which are equivalent to Dystric Cambisols (IUSS Working Group WRB, 2015), and formed in granitic parent materials, in a temperate climate, under thinned, mixed-coniferous forest (Fig. S3; Gaudinski et al., 2009). With these analyses we aimed to answer the question, is calcium associated with a specific type of organic matter enriched in aromatic and phenolic carbon at the microscale in samples from Blodgett Forest Research Center? and how does this specific type of carbon respond to experiments targetted at removing and adding calcium to the soils, specifically cation exchange and incubation after calcium addition? Abstract from the paper can be found below: Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil-types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca-SOC is removed through cation-exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, highlighting a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca, and in turn, this association inhibits dissolved organic carbon export or further decomposition. We propose that this mechanism could be driven by Ca hotspots on the microscale shifting local decomposition processes and thereby explaining the colocation of Ca with SOC of a specific composition across different acidic soil environments. Incorporating this biogeochemical process into Earth System Models could improve our understanding, predictions, and management of carbon dynamics in soils, and account for their response to Ca-rich amendments.

54 ENVIRONMENTAL SCIENCES↗

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↗

Materials Data on Sr6Sb6S17 by Materials Project

Sr6Sb6S14(S3) crystallizes in the orthorhombic P2_12_12_1 space group. The structure is three-dimensional. there are six inequivalent Sr2+ sites. In the first Sr2+ site, Sr2+ is bonded in a 8-coordinate geometry to eight S2- atoms. There are a spread of Sr–S bond distances ranging from 3.01–3.27 Å. In the second Sr2+ site, Sr2+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Sr–S bond distances ranging from 3.05–3.60 Å. In the third Sr2+ site, Sr2+ is bonded to seven S2- atoms to form distorted SrS7 pentagonal bipyramids that share a cornercorner with one SbS5 square pyramid and edges with two equivalent SrS7 pentagonal bipyramids. There are a spread of Sr–S bond distances ranging from 3.02–3.32 Å. In the fourth Sr2+ site, Sr2+ is bonded to seven S2- atoms to form distorted SrS7 pentagonal bipyramids that share a cornercorner with one SbS5 square pyramid and edges with two equivalent SrS7 pentagonal bipyramids. There are a spread of Sr–S bond distances ranging from 3.03–3.19 Å. In the fifth Sr2+ site, Sr2+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Sr–S bond distances ranging from 3.04–3.31 Å. In the sixth Sr2+ site, Sr2+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Sr–S bond distances ranging from 3.03–3.32 Å. There are six inequivalent Sb+3.67+ sites. In the first Sb+3.67+ site, Sb+3.67+ is bonded in a distorted trigonal non-coplanar geometry to three S2- atoms. There are two shorter (2.47 Å) and one longer (2.53 Å) Sb–S bond lengths. In the second Sb+3.67+ site, Sb+3.67+ is bonded to five S2- atoms to form SbS5 square pyramids that share corners with two SrS7 pentagonal bipyramids. There are a spread of Sb–S bond distances ranging from 2.44–3.08 Å. In the third Sb+3.67+ site, Sb+3.67+ is bonded in a distorted rectangular see-saw-like geometry to four S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–3.17 Å. In the fourth Sb+3.67+ site, Sb+3.67+ is bonded in a 4-coordinate geometry to three S2- atoms. There are a spread of Sb–S bond distances ranging from 2.46–2.57 Å. In the fifth Sb+3.67+ site, Sb+3.67+ is bonded in a distorted rectangular see-saw-like geometry to four S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–2.87 Å. In the sixth Sb+3.67+ site, Sb+3.67+ is bonded in a distorted trigonal non-coplanar geometry to three S2- atoms. There are a spread of Sb–S bond distances ranging from 2.46–2.53 Å. There are seventeen inequivalent S2- sites. In the first S2- site, S2- is bonded in a 5-coordinate geometry to four Sr2+ and one S2- atom. The S–S bond length is 2.10 Å. In the second S2- site, S2- is bonded in a 6-coordinate geometry to four Sr2+ and two S2- atoms. The S–S bond length is 2.09 Å. In the third S2- site, S2- is bonded in a 5-coordinate geometry to four Sr2+ and one S2- atom. In the fourth S2- site, S2- is bonded to two Sr2+ and two Sb+3.67+ atoms to form distorted SSr2Sb2 trigonal pyramids that share a cornercorner with one SSr4Sb square pyramid, a cornercorner with one SSr4Sb trigonal bipyramid, corners with two equivalent SSr2Sb2 trigonal pyramids, and edges with three SSr4Sb trigonal bipyramids. In the fifth S2- site, S2- is bonded to four Sr2+ and one Sb+3.67+ atom to form distorted SSr4Sb trigonal bipyramids that share corners with four SSr4Sb trigonal bipyramids, an edgeedge with one SSr4Sb square pyramid, an edgeedge with one SSr4Sb trigonal bipyramid, and edges with two SSr2Sb2 trigonal pyramids. In the sixth S2- site, S2- is bonded to two Sr2+ and two Sb+3.67+ atoms to form SSr2Sb2 trigonal pyramids that share a cornercorner with one SSr4Sb square pyramid, a cornercorner with one SSr4Sb trigonal bipyramid, corners with two equivalent SSr2Sb2 trigonal pyramids, and edges with three SSr4Sb trigonal bipyramids. In the seventh S2- site, S2- is bonded in a 5-coordinate geometry to four Sr2+ and one Sb+3.67+ atom. In the eighth S2- site, S2- is bonded in a 3-coordinate geometry to one Sr2+ and two Sb+3.67+ atoms. In the ninth S2- site, S2- is bonded in a 3-coordinate geometry to one Sr2+ and two Sb+3.67+ atoms. In the tenth S2- site, S2- is bonded to four Sr2+ and one Sb+3.67+ atom to form distorted SSr4Sb trigonal bipyramids that share corners with four SSr4Sb trigonal bipyramids, corners with two SSr2Sb2 trigonal pyramids, edges with two equivalent SSr4Sb square pyramids, and an edgeedge with one SSr4Sb trigonal bipyramid. In the eleventh S2- site, S2- is bonded in a 4-coordinate geometry to one Sr2+ and two Sb+3.67+ atoms. In the twelfth S2- site, S2- is bonded in a distorted rectangular see-saw-like geometry to one Sr2+ and three Sb+3.67+ atoms. In the thirteenth S2- site, S2- is bonded to four Sr2+ and one Sb+3.67+ atom to form SSr4Sb square pyramids that share corners with two equivalent SSr4Sb trigonal bipyramids, corners with two SSr2Sb2 trigonal pyramids, and edges with four SSr4Sb trigonal bipyramids. In the fourteenth S2- site, S2- is bonded in a 3-coordinate geometry to three Sr2+ and one Sb+3.67+ atom. In the fifteenth S2- site, S2- is bonded in a distorted rectangular see-saw-like geometry to two Sr2+ and two Sb+3.67+ atoms. In the sixteenth S2- site, S2- is bonded to four Sr2+ and one Sb+3.67+ atom to form distorted SSr4Sb trigonal bipyramids that share corners with two equivalent SSr4Sb square pyramids, edges with four SSr4Sb trigonal bipyramids, and edges with two SSr2Sb2 trigonal pyramids. In the seventeenth S2- site, S2- is bonded to four Sr2+ and one Sb+3.67+ atom to form distorted SSr4Sb trigonal bipyramids that share corners with four SSr4Sb trigonal bipyramids, an edgeedge with one SSr4Sb square pyramid, edges with two equivalent SSr4Sb trigonal bipyramids, and edges with two SSr2Sb2 trigonal pyramids.

36 MATERIALS SCIENCE↗

Materials Data on Sb6Pb6S17 by Materials Project

Pb6Sb6S14(S3) crystallizes in the orthorhombic P2_12_12 space group. The structure is three-dimensional. there are three inequivalent Pb2+ sites. In the first Pb2+ site, Pb2+ is bonded in a 7-coordinate geometry to seven S2- atoms. There are a spread of Pb–S bond distances ranging from 2.80–3.49 Å. In the second Pb2+ site, Pb2+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Pb–S bond distances ranging from 3.00–3.31 Å. In the third Pb2+ site, Pb2+ is bonded in a 8-coordinate geometry to eight S2- atoms. There are a spread of Pb–S bond distances ranging from 2.90–3.40 Å. There are three inequivalent Sb+3.67+ sites. In the first Sb+3.67+ site, Sb+3.67+ is bonded to five S2- atoms to form a mixture of distorted edge and corner-sharing SbS5 square pyramids. There are a spread of Sb–S bond distances ranging from 2.44–3.16 Å. In the second Sb+3.67+ site, Sb+3.67+ is bonded to five S2- atoms to form a mixture of edge and corner-sharing SbS5 square pyramids. There are a spread of Sb–S bond distances ranging from 2.48–2.91 Å. In the third Sb+3.67+ site, Sb+3.67+ is bonded in a 5-coordinate geometry to five S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–3.24 Å. There are nine inequivalent S2- sites. In the first S2- site, S2- is bonded in a 1-coordinate geometry to four Pb2+ and one Sb+3.67+ atom. In the second S2- site, S2- is bonded in a 1-coordinate geometry to four Pb2+ and one S2- atom. The S–S bond length is 2.08 Å. In the third S2- site, S2- is bonded in a distorted water-like geometry to two Pb2+ and two equivalent Sb+3.67+ atoms. In the fourth S2- site, S2- is bonded in a distorted water-like geometry to two Pb2+ and two equivalent Sb+3.67+ atoms. In the fifth S2- site, S2- is bonded in a 5-coordinate geometry to one Pb2+ and four Sb+3.67+ atoms. In the sixth S2- site, S2- is bonded to four Pb2+ and one Sb+3.67+ atom to form distorted edge-sharing SSbPb4 square pyramids. In the seventh S2- site, S2- is bonded in a distorted bent 120 degrees geometry to four Pb2+ and two equivalent S2- atoms. In the eighth S2- site, S2- is bonded to one Pb2+ and four Sb+3.67+ atoms to form distorted edge-sharing SSb4Pb square pyramids. In the ninth S2- site, S2- is bonded in a 1-coordinate geometry to four Pb2+ and one Sb+3.67+ atom.

36 MATERIALS SCIENCE↗

Materials Data on Eu6Sb6S17 by Materials Project

Eu6Sb6S14(S3) crystallizes in the orthorhombic P2_12_12_1 space group. The structure is three-dimensional. there are six inequivalent Eu+2.67+ sites. In the first Eu+2.67+ site, Eu+2.67+ is bonded to seven S2- atoms to form distorted EuS7 pentagonal bipyramids that share a cornercorner with one SbS5 square pyramid and edges with two equivalent EuS7 pentagonal bipyramids. There are a spread of Eu–S bond distances ranging from 3.00–3.12 Å. In the second Eu+2.67+ site, Eu+2.67+ is bonded to seven S2- atoms to form distorted EuS7 pentagonal bipyramids that share a cornercorner with one SbS5 square pyramid and edges with two equivalent EuS7 pentagonal bipyramids. There are a spread of Eu–S bond distances ranging from 2.96–3.25 Å. In the third Eu+2.67+ site, Eu+2.67+ is bonded in a 8-coordinate geometry to eight S2- atoms. There are a spread of Eu–S bond distances ranging from 2.98–3.26 Å. In the fourth Eu+2.67+ site, Eu+2.67+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Eu–S bond distances ranging from 3.03–3.41 Å. In the fifth Eu+2.67+ site, Eu+2.67+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Eu–S bond distances ranging from 3.00–3.23 Å. In the sixth Eu+2.67+ site, Eu+2.67+ is bonded in a 9-coordinate geometry to nine S2- atoms. There are a spread of Eu–S bond distances ranging from 3.01–3.22 Å. There are six inequivalent Sb3+ sites. In the first Sb3+ site, Sb3+ is bonded in a distorted rectangular see-saw-like geometry to four S2- atoms. There are a spread of Sb–S bond distances ranging from 2.50–2.98 Å. In the second Sb3+ site, Sb3+ is bonded in a 4-coordinate geometry to four S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–3.13 Å. In the third Sb3+ site, Sb3+ is bonded in a distorted rectangular see-saw-like geometry to four S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–3.13 Å. In the fourth Sb3+ site, Sb3+ is bonded to five S2- atoms to form SbS5 square pyramids that share corners with two EuS7 pentagonal bipyramids. There are a spread of Sb–S bond distances ranging from 2.46–3.12 Å. In the fifth Sb3+ site, Sb3+ is bonded in a 3-coordinate geometry to four S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–3.28 Å. In the sixth Sb3+ site, Sb3+ is bonded in a 3-coordinate geometry to three S2- atoms. There are a spread of Sb–S bond distances ranging from 2.47–2.55 Å. There are seventeen inequivalent S2- sites. In the first S2- site, S2- is bonded in a 5-coordinate geometry to four Eu+2.67+ and one S2- atom. The S–S bond length is 2.12 Å. In the second S2- site, S2- is bonded in a 6-coordinate geometry to four Eu+2.67+ and two S2- atoms. The S–S bond length is 2.12 Å. In the third S2- site, S2- is bonded in a 5-coordinate geometry to four Eu+2.67+ and one S2- atom. In the fourth S2- site, S2- is bonded to four Eu+2.67+ and one Sb3+ atom to form distorted SEu4Sb trigonal bipyramids that share corners with four SEu4Sb trigonal bipyramids, edges with three SEu4Sb trigonal bipyramids, and edges with two SEu2Sb2 trigonal pyramids. In the fifth S2- site, S2- is bonded in a 3-coordinate geometry to one Eu+2.67+ and two Sb3+ atoms. In the sixth S2- site, S2- is bonded in a distorted rectangular see-saw-like geometry to one Eu+2.67+ and three Sb3+ atoms. In the seventh S2- site, S2- is bonded to four Eu+2.67+ and one Sb3+ atom to form distorted SEu4Sb trigonal bipyramids that share corners with two equivalent SEu4Sb trigonal bipyramids, corners with two SEu2Sb2 trigonal pyramids, and edges with four SEu4Sb trigonal bipyramids. In the eighth S2- site, S2- is bonded to four Eu+2.67+ and one Sb3+ atom to form distorted SEu4Sb trigonal bipyramids that share corners with four SEu4Sb trigonal bipyramids, corners with two SEu2Sb2 trigonal pyramids, and edges with three SEu4Sb trigonal bipyramids. In the ninth S2- site, S2- is bonded in a 5-coordinate geometry to one Eu+2.67+ and four Sb3+ atoms. In the tenth S2- site, S2- is bonded in a 3-coordinate geometry to one Eu+2.67+ and two Sb3+ atoms. In the eleventh S2- site, S2- is bonded in a 5-coordinate geometry to four Eu+2.67+ and one Sb3+ atom. In the twelfth S2- site, S2- is bonded to four Eu+2.67+ and one Sb3+ atom to form distorted SEu4Sb trigonal bipyramids that share corners with four SEu4Sb trigonal bipyramids, edges with two SEu4Sb trigonal bipyramids, and edges with two SEu2Sb2 trigonal pyramids. In the thirteenth S2- site, S2- is bonded to two Eu+2.67+ and two Sb3+ atoms to form SEu2Sb2 trigonal pyramids that share corners with two SEu4Sb trigonal bipyramids, corners with two equivalent SEu2Sb2 trigonal pyramids, and edges with three SEu4Sb trigonal bipyramids. In the fourteenth S2- site, S2- is bonded to two Eu+2.67+ and two Sb3+ atoms to form distorted SEu2Sb2 trigonal pyramids that share corners with two SEu4Sb trigonal bipyramids, corners with two equivalent SEu2Sb2 trigonal pyramids, and edges with three SEu4Sb trigonal bipyramids. In the fifteenth S2- site, S2- is bonded in a 4-coordinate geometry to two Eu+2.67+ and two Sb3+ atoms. In the sixteenth S2- site, S2- is bonded in a 4-coordinate geometry to three Eu+2.67+ and one Sb3+ atom. In the seventeenth S2- site, S2- is bonded to four Eu+2.67+ and one Sb3+ atom to form distorted SEu4Sb trigonal bipyramids that share corners with two equivalent SEu4Sb trigonal bipyramids, edges with four SEu4Sb trigonal bipyramids, and edges with two SEu2Sb2 trigonal pyramids.

36 MATERIALS SCIENCE↗

Polarization Imaging for International Safeguards (FY2019)

A polarization imaging camera, Salsa (Bossa Nova Technologies) was evaluated for use in nuclear safeguards inspection with a focus on swipe sampling. The camera and supporting electronics and software determine the full Stokes parameters for the entire image field. The camera can be used for real-time video or still images. Stokes parameters S0, S1, S2, and S3 can be recorded for each pixel and exported for post processing. This study compared color photography to polarization imaging for powders on many surfaces under ambient lighting. False color images can be created from the Stokes parameters directly from the vendor software to highlight the various polarization states. In most cases, linear polarization showed the greatest effects. The polarization images are easy to collect and very sensitive to surfaces and textures. Fine powders are highlighted in the images, and particle size and refractive index effects were noticed. The images are not affected by ambient lighting (angle, or intensity). Lens choice is key and may require expert knowledge. Very small deposits of 1 µm particles were difficult to image using the standard video lens. General dirt on smooth surfaces and handprints are easily documented as well as powders on textured painted surfaces. Scratches on metal surfaces can be readily separated from other image features. The camera may be useful for tamper indication as surface damage is easy to discern and ambient lighting is not a concern.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Plutonium Age Dating Interlaboratory Comparison Overview - Project Design, Sample Preparation, and Results [Slides]

Project Design – How do you validate measured Pu model age? There are no certified reference materials (CRMs) that are certified for Pu model age or purification dates. There are no Am isotopic CRMs - IRMM 0243 243 Am spike has 241 Am impurity that can be used; Community working toward "consensus ages." This project executed and evaluated results from a Pu age dating interlaboratory comparison with six IAEA NWAL participant laboratories. It also ran the first quality control evaluation of single-picogram to sub-picogram scale interlaboratory 241 Am assay measurements from cotton swipe matrices. Results are promising, with a majority of 241 Am/ 241 Pu model age results agree to within 1 to 4 years. The calculated 241 Am assay results show interlaboratory variability, expanded percent uncertainties on calculated consensus 241 Am concentrations were: PuAge-S1 = 3.1 %, PuAge-S2 = 23 %, and PuAge-S3 = 26 %. Data can be used to investigate laboratory methods and improve precision and accuracy of 241 Pu and 241 Am assay for future campaigns.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗