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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 OSTI2026

Evaluating Protection System Performance for a Real-World Weak Grid Area With High Inverter-Based Resources

This paper evaluates an existing protection scheme implemented in a real-world weak grid area with a high penetration of inverter-based resources (IBRs). The study aims to assess the reliability and adequacy of protection schemes originally designed for traditional synchronous machine systems and determine whether they can continue to operate reliably in systems with high levels of IBRs. Hardware relays are tested using a controller-hardware-in-the-loop setup. PSCAD electromagnetic transient simulation with an IBR original equipment manufacturer black-box model is used to perform fault studies and generate COMTRADE data, which are replayed by a realtime digital simulator (RTDS) to feed input to the hardware relays. Three scenarios are analyzed: normal operation, an N-1 contingency, and an IBR-only scenario. The evaluation results reveal the following: 1) the protection scheme remains reliable under normal conditions and N-1 contingencies and 2) in IBRonly scenarios, differential protection (87L) continues to operate reliably, whereas local protection elements, such as distance and directional elements, fail because of the lack of regulated negative sequence current contributed by IBRs. These findings provide utilities with valuable insights for improving their protection systems in high-IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Impact of Baloxavir Resistance-Associated Substitutions on Influenza Virus Growth and Drug Susceptibility

Baloxavir marboxil (baloxavir) is a recently FDA-approved influenza virus polymerase acidic (PA) endonuclease inhibitor. Several PA substitutions have been demonstrated to confer reduced susceptibility to baloxavir; however, their impacts on measurements of antiviral drug susceptibility and replication capacity when present as a fraction of the viral population have not been established. We generated recombinant A/California/04/09 (H1N1)-like viruses (IAV) with PA I38L, I38T, or E199D substitutions and B/Victoria/504/2000-like virus (IBV) with PA I38T. These substitutions reduced baloxavir susceptibility by 15.3-, 72.3-, 5.4-, and 54.5-fold, respectively, when tested in normal human bronchial epithelial (NHBE) cells. We then assessed the replication kinetics, polymerase activity, and baloxavir susceptibility of the wild-type:mutant (WT:MUT) virus mixtures in NHBE cells. The percentage of MUT relative to WT virus necessary to detect reduced baloxavir susceptibility in phenotypic assays ranged from 10% (IBV I38T) to 92% (IAV E199D). While I38T did not alter IAV replication kinetics or polymerase activity, IAV PA I38L and E199D MUTs and the IBV PA I38T MUT exhibited reduced replication levels and significantly altered polymerase activity. Differences in replication were detectable when the MUTs comprised ≥90%, ≥90%, or ≥75% of the population, respectively. Here, droplet digital PCR (ddPCR) and next-generation sequencing (NGS) analyses showed that WT viruses generally outcompeted the respective MUTs after multiple replication cycles and serial passaging in NHBE cells when initial mixtures contained ≥50% of the WT viruses; however, we also identified potential compensatory substitutions (IAV PA D394N and IBV PA E329G) that emerged and appeared to improve the replication capacity of baloxavir-resistant virus in cell culture.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multiple spillovers from humans and onward transmission of SARS-CoV-2 in white-tailed deer

Many animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and could act as reservoirs; however, transmission in free-living animals has not been documented. White-tailed deer, the predominant cervid in North America, are susceptible to SARS-CoV-2 infection, and experimentally infected fawns can transmit the virus. To test the hypothesis that SARS-CoV-2 is circulating in deer, 283 retropharyngeal lymph node (RPLN) samples collected from 151 free-living and 132 captive deer in Iowa from April 2020 through January of 2021 were assayed for the presence of SARS-CoV-2 RNA. Ninety-four of the 283 (33.2%) deer samples were positive for SARS-CoV-2 RNA as assessed by RT-PCR. Notably, following the November 2020 peak of human cases in Iowa, and coinciding with the onset of winter and the peak deer hunting season, SARS-CoV-2 RNA was detected in 80 of 97 (82.5%) RPLN samples collected over a 7-wk period. Whole genome sequencing of all 94 positive RPLN samples identified 12 SARS-CoV-2 lineages, with B.1.2 (n = 51; 54.5%) and B.1.311 (n = 19; 20%) accounting for ~75% of all samples. The geographic distribution and nesting of clusters of deer and human lineages strongly suggest multiple human-to-deer transmission events followed by subsequent deer-to-deer spread. These discoveries have important implications for the long-term persistence of the SARS-CoV-2 pandemic. Our findings highlight an urgent need for a robust and proactive “One Health” approach to obtain enhanced understanding of the ecology, molecular evolution, and dissemination of SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

3D-equivariant graph neural networks for protein model quality assessment

Quality assessment (QA) of predicted protein tertiary structure models plays an important role in ranking and using them. With the recent development of deep learning end-to-end protein structure prediction techniques for generating highly confident tertiary structures for most proteins, it is important to explore corresponding QA strategies to evaluate and select the structural models predicted by them since these models have better quality and different properties than the models predicted by traditional tertiary structure prediction methods. We develop EnQA, a novel graph-based 3D-equivariant neural network method that is equivariant to rotation and translation of 3D objects to estimate the accuracy of protein structural models by leveraging the structural features acquired from the state-of-the-art tertiary structure prediction method—AlphaFold2. We train and test the method on both traditional model datasets (e.g. the datasets of the Critical Assessment of Techniques for Protein Structure Prediction) and a new dataset of high-quality structural models predicted only by AlphaFold2 for the proteins whose experimental structures were released recently. Our approach achieves state-of-the-art performance on protein structural models predicted by both traditional protein structure prediction methods and the latest end-to-end deep learning method—AlphaFold2. It performs even better than the model QA scores provided by AlphaFold2 itself. The results illustrate that the 3D-equivariant graph neural network is a promising approach to the evaluation of protein structural models. Integrating AlphaFold2 features with other complementary sequence and structural features is important for improving protein model QA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Amplicon Sequencing Assessment to Measure Microbial Community Response from Heavy Metal Contaminated Soils in Savannah River site, Tims Branch watershed

Long-term presence of heavy metal contamination in soils is correlated with changes in microbial community structures and can lead to the reduction of indigenous species. Tolerance to soil heavy metal toxicity varies among different microbial communities. It remains unclear whether long term effects caused by metal perturbations are associated with soil microbial community dysregulation in Tims Branch watershed. Research Questions: Does heavy metal contamination in Tims Branch soils decrease microbial species diversity significantly compared to non-contaminated soils? Does the species richness decrease in contaminated samples? between samples? Is diversity in low, mid and high contamination soils significantly different compared to control samples? Hypothesis: The relative abundance and diversity of species are significantly altered in soils which are contaminated with heavy metals in the Tims Branch watershed. Objectives: Use amplicon sequencing technology along with bioinformatics to compare bacterial communities between four sites in Tims Branch watershed. Evaluate the percent relative abundance and diversity across the site. Conclusions: All bacterial communities exposed to different heavy metal concentrations were dominated by four major groups (Proteobacteria, Acidobacteria, Chloroflexi and Verrucomicrobia). The dominant phyla Proteobacteria, Acidobacteria and Chloroflexi accounted for 61 % of the relative abundance. Soil bacterial α-diversity, expressed as observed species richness metric and Shannon's diversity index, was the highest in sample location four (high contamination). The lowest observed was at the control location. Species richness increased when concentrations of heavy metals were localized, inferring that the metals can alter microbial community structure. PERMANOVA analysis between contaminated groups tested significant using the Adonis (F (4,29) =1.9712; p < 0.001). There is a 20 percent variation explained between groups (R2 = 0.214). This analysis proves to be beneficial in detecting microbial communities altered by contaminated soils. Moreover, certain concentrations of heavy metals can alter microbial community structures.

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

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Photometric calibration in u -band using blue halo stars

ABSTRACT We develop a method to calibrate u-band photometry based on the observed colour of blue Galactic halo stars. The Galactic halo stars belong to an old stellar population of the Milky Way and have relatively low metallicity. The ‘blue tip’ of the halo population – the main sequence turn-off (MSTO) stars – is known to have a relatively uniform intrinsic edge u-g colour with only slow spatial variation. In SDSS data, the observed variation is correlated with Galactic Latitude, which we attribute to contamination by higher metallicity disc stars and fit with an empirical curve. This curve can then be used to calibrate u-band imaging if g-band imaging of matching depth is available. Our approach can be applied to single-field observations at |b| > 30°, and removes the need for standard star observations or overlap with calibrated u-band imaging. We include in our method the calibration of g-band data with ATLAS-Refcat2. We test our approach on stars in KiDS DR 4, ATLAS DR 4, and DECam imaging from the NOIRLab Source Catalog (NSC DR2), and compare our calibration with SDSS. For this process, we use synthetic magnitudes to derive the colour equations between these data sets, in order to improve zero-point accuracy. We find an improvement for all data sets, reaching a zero-point precision of 0.016 mag for KiDS (compared to the original 0.033 mag), 0.020 mag for ATLAS (originally 0.027 mag), and 0.016 mag for DECam (originally 0.041 mag). Thus, this method alone reaches the goal of 0.02 mag photometric precision in u-band for the Rubin Observatory’s Legacy Survey of Space and Time (LSST).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Automated detection of double nuclei galaxies using GOTHIC and the discovery of a large sample of dual AGN

We present a novel algorithm to detect double nuclei galaxies (DNG) called Gothic (Graph-bOosTed iterated HIll Climbing) – that detects whether a given image of a galaxy has two or more closely separated nuclei. Our aim is to test for the presence of dual/multiple active galactic nuclei (AGN) in galaxies that visually represent a DNG. Although galaxy mergers are common, the detection of dual AGN is rare. Their detection is very important as they help us understand the formation of supermassive black hole (SMBH) binaries, SMBH growth and AGN feedback effects in multiple nuclei systems. There is thus a need for an algorithm to do a systematic survey of existing imaging data for the discovery of DNGs and dual AGNs. We have tested Gothic on an established sample of DNGs with a 100 per cent detection rate and subsequently conducted a blind search of 1 million SDSS DR16 galaxies (with spectroscopic data available) lying in the redshift range of z = 0 to 0.75. From the list of candidate DNGs found, we have detected 159 dual AGNs, of which 2 are triple AGN systems. Our results show that dual AGNs are not common, and triple AGN even rarer. The colour (u–r) magnitude plots of the DNGs indicate that star formation is quenched as the nuclei come closer and as the AGN fraction increases. The quenching is especially prominent for dual/triple AGN galaxies that lie at the extreme end of the red sequence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Impact of K-factor on Short Circuit Program Convergence for Inverter-Based Resources during Faults

Classical short-circuit programs that linearize the power network are no longer applicable for inverter based resources (IBRs), necessitating an iterative approach. Phasor domain programs can model the IBRs using an iterative approach considering nonlinear fault responses. In phasor domain models, the IBR can be modeled as a voltage controlled current source (VCCS) in tabular form with positive, negative, and zero sequence information for balanced and unbalance short-circuit faults. In the VCCS modeling of the IBR, positive and negative incremental reactive current, also known as the k-factor, plays an important role in short circuit program convergence. In this work, a few approaches: conventional VCCS modeling with a k-factor of 2, conventional VCCS modeling with a k-factor of 2 with modified pre-fault voltages, VCCS characteristics based on the power flow solution with a k-factor of 2, and VCCS characteristics based on the power flow solution with a k-factor of 1 are investigated for short circuit program convergence under higher IBR penetration. The IEEE 39 bus New England Test System is taken as the test system, and simulations are carried out in PSS®CAPE 15.0.26 simulation software. Simulation results demonstrate that IBR penetration is higher for the VCCS model, which corresponds to the power flow solution with k-factor 1, compared to other approaches.

42 ENGINEERING↗
DOE OSTI2026

Evaluating Protection System Performance for a Real-World Weak Grid Area With High Inverter-Based Resources: Preprint

This paper evaluates an existing protection scheme implemented in a real-world weak grid area with a high penetration of inverter-based resources (IBRs). The study aims to assess the reliability and adequacy of protection schemes originally designed for traditional synchronous machine systems and determine whether they can continue to operate reliably in systems with high levels of IBRs. Hardware relays are tested using a controller-hardware-in-the-loop setup. PSCAD electromagnetic transient simulation with an IBR original equipment manufacturer black-box model is used to perform fault studies and generate COMTRADE data, which are replayed by a real-time digital simulator (RTDS) to feed input to the hardware relays. Three scenarios are analyzed: normal operation, an N-1 contingency, and an IBR-only scenario. The evaluation results reveal the following: 1) the protection scheme remains reliable under normal conditions and N-1 contingencies and 2) in IBR-only scenarios, differential protection (87L) continues to operate reliably, whereas local protection elements, such as distance and directional elements, fail because of the lack of regulated negative sequence current contributed by IBRs. These findings provide utilities with valuable insights for improving their protection systems in high-IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Physiological, genomic, and sulfur isotopic characterization of methanol metabolism by Desulfovibrio carbinolicus

Methanol is often considered as a non-competitive substrate for methanogenic archaea, but an increasing number of sulfate-reducing microorganisms (SRMs) have been reported to be capable of respiring with methanol as an electron donor. A better understanding of the fate of methanol in natural or artificial anaerobic systems thus requires knowledge of the methanol dissimilation by SRMs. In this study, we describe the growth kinetics and sulfur isotope effects of Desulfovibrio carbinolicus, a methanol-oxidizing sulfate-reducing deltaproteobacterium, together with its genome sequence and annotation. D. carbinolicus can grow with a series of alcohols from methanol to butanol. Compared to longer-chain alcohols, however, specific growth and respiration rates decrease by several fold with methanol as an electron donor. Larger sulfur isotope fractionation accompanies slowed growth kinetics, indicating low chemical potential at terminal reductive steps of respiration. In a medium containing both ethanol and methanol, D. carbinolicus does not consume methanol even after the cessation of growth on ethanol. Among the two known methanol dissimilatory systems, the genome of D. carbinolicus contains the genes coding for alcohol dehydrogenase but lacks enzymes analogous to methanol methyltransferase. We analyzed the genomes of 52 additional species of sulfate-reducing bacteria that have been tested for methanol oxidation. There is no apparent relationship between phylogeny and methanol metabolizing capacity, but most gram-negative methanol oxidizers grow poorly, and none carry homologs for methyltransferase (mtaB). Although the amount of available data is limited, it is notable that more than half of the known gram-positive methanol oxidizers have both enzymatic systems, showing enhanced growth relative to the SRMs containing only alcohol dehydrogenase genes. Thus, physiological, genomic, and sulfur isotopic results suggest that D. carbinolicus and close relatives have the ability to metabolize methanol but likely play a limited role in methanol degradation in most natural environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation

Accurate cell type annotation remains a major bottleneck in plant single-cell RNA sequencing (scRNA-seq), where existing tools are often adapted from animal studies and perform sub-optimally on plant data. The lack of plant-specific computational frameworks limits the construction of plant cell atlases and downstream biological discovery. We develop and evaluate scPlantAnnotate, a Transformer-based reference annotation framework tailored for plant scRNA-seq data, and benchmark it against state-of-the-art deep learning and conventional methods across multiple plant species. Species-specific scPlantAnnotate models were trained using curated datasets from Arabidopsis thaliana, Zea mays, Oryza sativa, and Glycine max. We compared scPlantAnnotate with leading baselines under both standard random-split evaluation and a more stringent leave-one-dataset-out setting, which tests robustness to completely unseen datasets and tissue types. scPlantAnnotate consistently outperforms existing approaches across all four species under random-split evaluation. In the leave-one-dataset-out setting for A. thaliana, where performance drops markedly for all methods due to strong batch effects and dataset heterogeneity, scPlantAnnotate nonetheless achieves the highest Accuracy, Macro-F1, Balanced Accuracy, and Macro-AUROC on average and ranks first on most held-out datasets. These results demonstrate improved robustness to dataset shifts, a critical yet underexplored challenge in plant scRNA-seq analysis. A freely accessible web server enables users to annotate their own datasets using pretrained models. scPlantAnnotate provides a plant-specific, Transformer-based framework for single-cell annotation that delivers state-of-the-art performance and enhanced robustness to unseen datasets. By addressing limitations of existing tools and enabling scalable reference-based annotation, scPlantAnnotate supports the development of comprehensive plant cell atlases and facilitates broader use of single-cell genomics in plant biology.

Bioinformatics↗
DOE OSTI2022

Polar algae flaunt their zinc assets

Metal ions have been at the centre of pivotal points in the evolution of extant life. Oxygen-evolving photosynthesis, which irrevocably reshaped the geochemistry and biology of our planet, has an absolute requirement for metal ions to harvest light, split water and transfer electrons. Access to abundant oxygen then led to the propagation of organisms capable of oxidative metabolism, a process that is also dependent on metal ions for electron transfer and reduction of molecular oxygen. Because of the essential links between metal ions and the proteins that require them to function, as well as changes in metal bioavailability through time, metals have shaped the trajectories that evolution can take. Iron typically steals this show, but with access to whole-genome sequences and transcriptomes, the imprint that zinc has made on biology is coming into focus. Writing in Nature Ecology & Evolution, Ye and colleagues present new insights into the complex connections between zinc bioavailability, adaptation of algae to the polar oceans and the evolution of regulatory networks. By combining field and laboratory-based analyses, the authors suggest that expanded families of zinc-binding proteins have enabled the green alga Microglena sp. YARC to flourish in the harsh conditions of the polar Southern Ocean (Fig. 1). As the waters where this alga occurs are known for their enrichment of zinc, the authors further propose that availability of this metal ion was directly responsible for successful microalgal colonization of polar oceans. To test this hypothesis, the authors compare meta-transcriptomes collected from pole-to-pole and find positive correlations between higher copy numbers for transcripts encoding putative zinc-binding proteins, higher latitudes, lower surface temperatures and dissolved zinc.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation

A comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3' RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of timeseries transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. Our data confirm that DroNcseq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Continuous-Energy ENDF/B-VIII.0 Cross Section and SCALE 6.2.4 Performance for Nuclear Criticality Safety Applications: 1 H, C, 58,60 Ni, 182,183,184,186 W, 235,238 U, 239 Pu

As part of the nuclear data evaluation and validation cycle, the ENDF/B-VIII.0 cross-section library released in 2018 requires testing to determine areas of improvement and deterioration. Previous work by the authors investigated the performance of 16 O, 56 Fe, and 63,65 Cu cross sections, with this study acting as an extension of the prior work. In addition to the isotopes and nuclear criticality safety benchmarks of interest to the prior work, benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook were selected for their k eff sensitivity to 1 H, C, 58,60 Ni, 182,183,184,186 W, 235,238U, or 239 Pu cross sections and were modeled in the SCALE code system maintained by Oak Ridge National Laboratory. In total, 253 benchmark configurations were selected for their sensitivities and modeled using SCALE 6.2.4 Criticality Safety Analysis Sequences (CSAS) continuous-energy Monte Carlo k eff calculations. This collection includes and expands upon the 99 benchmarks in the prior work. The AMPX-processed ENDF/B-VIII.0 library was decomposed into individual ENDF/B-VIII.0 datum libraries for each isotope of interest. Doing so allowed for the individual substitution of an ENDF/B-VIII.0 cross section in the place of ENDF/B-VII.1, determining isotope-specific effects of ENDF/B-VIII.0 relative to ENDF/B-VII.1. Full library calculations with entirely ENDF/B-VII.1 data or entirely ENDF/B-VIII.0 data were also executed. As a measure of performance, the average relative deviation was determined as the ratio of the deviation between calculated and experimental keff to the propagated calculational and experimental uncertainty. With calculated full library and isotope-specific ENDF/B-VIII.0 k eff ’s, an optimized combination of data libraries was estimated and confirmed with SCALE calculations. This showed that reverting 239 Pu, 58 Ni, 16 O, and 65 Cu cross sections to ENDF/B-VII.1 resulted in improved performance relative to the full ENDF/B-VIII.0 library. Across all 253 benchmarks, the average relative deviation was 1.29σ for the full ENDF/B-VII.1 library, 1.17σ for the full ENDF/B-VIII.0 library, and 0.97σ for the optimized combination. The reversion of 239 Pu, 58 Ni, 16 O, and 65 Cu cross sections to ENDF/B-VII.1 in the 99 benchmarks of the prior work resulted in further improved experimental agreement compared to the previously reported improvement from 16 O and 65 Cu alone. Therefore, it is suggested that applications with significant sensitivities to 239 Pu, 58 Ni, 16 O, and 65 Cu consider their choice of nuclear data library.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Climatic controls on soil and saprock nitrogen distribution and persistence in the Sierra Nevada

Nitrogen (N) is an essential nutrient in soil that regulates plant growth, terrestrial sequestration of atmospheric carbon dioxide, and persistence of organic compounds. However, major knowledge gaps remain about how climate change may impact N accumulation and persistence, especially in deep soil and saprock (friable weakly weathered bedrock). Our objective was to understand how climate impacts the accumulation of N in soil and saprock and how climate impacts soil N distribution, persistence, and mechanisms of N persistence. We investigated N concentration in bulk soil and density fractions. We estimated N persistence along a bio-climatic sequence—sites range from a low-elevation oak savannah, mid-elevation pine-oak/mixed-conifer forest, to a high-elevation subalpine forest—in the southern Sierra Nevada in California. A combination of radiocarbon and elemental composition measurements along with a first-order kinetic model was used. The N concentration in the bulk soil and density fractions declined with depth, and there was a relatively greater mineral-associated heavy fraction (HF) N in deeper samples. The cooler/wetter mixed conifer site held 37% of profile N in saprock, which was greater than that of the entire soil profile at the drier/hotter oak savannah. The majority of N in soil, which was in the HF, was not influenced by climate proxies tested. However, both unprotected and occluded fractions of N were strongly influenced by climate. Soil N mean residence time (MRT) showed that drier/hotter climates have a shorter MRT, compared to mid-elevation sites with cooler/wetter climates. The effect of climate on deep saprock N storage might be indirect, primarily through climatic influence on the thickness of saprock. Overall, our findings suggest the mineral-associated HF N pool will not be vulnerable to changes in climate and will continue to contribute to the persistent soil N pool. The amount of topsoil and subsoil unprotected and occluded N can be explained by gross primary productivity and mean annual precipitation indicating that changes in climate can influence N partitioning. N stored in deep soil and saprock may be less vulnerable to climate than N stored in drier/hotter climates with less deeply stored N. It is critical to dig deeper to understand terrestrial ecosystems’ response to climate.

58 GEOSCIENCES↗
DOE OSTI2025

LABQ3: Bayesian method for quantification of mineral compositions and nano-scale elemental mapping of 3D synchrotron XCT data

Quantitative analysis of mineral compositions is essential in understanding geochemical, mineralogical and environmental processes. Fine-resolution 3D imaging is widely done using synchrotron X-ray computed tomography (XCT), but existing analyses are limited to visualization and segmentation. This paper presents a new method, Linear Attenuation Bayesian Quantitative 3D-mapper (LABQ3), based on the linearity of X-ray attenuation with respect to elemental concentrations. To address the random variability in attenuation measurements, LABQ3 employs Bayesian decision theory to minimize classification error, using reference attenuation distributions from scans of pure mineral standards. To demonstrate LABQ3 and test its performance, we studied precipitated carbonate samples. XCT scans were done at multiple energies using the transmission X-ray microscope (TXM) at beamline 32-ID-C of the Advanced Photon Source at Argonne National Laboratory. The reconstructed 3D images have a voxel size of 20 nm. Analyses revealed rich nano-scale compositional heterogeneity within individual particles. A mixture of calcium and cadmium produced an overall stoichiometric composition of (Ca 0.78 ,Cd 0.22 )CO 3 , with some voxels containing nearly pure CdCO 3 . The addition of zinc led to an overall stoichiometric composition of 33% Ca, 28% Cd, 39% Zn, with a nearly pure CaCO 3 core and compositional zonation through the rim. These compositional gradients are related to temporal sequences of carbonate mineral formation where Cd precipitated at the beginning in (Ca,Cd)CO 3 , while Cd and Zn precipitated at the end in (Ca, Cd,Zn)CO 3 . Results differ from bulk analyses using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), showing that LABQ3 provides particle-specific insights. LABQ3 distinguishes itself by quantifying chemical compositions along a continuum, making it different from XCT analyses based on segmentation. LABQ3 allows simultaneous acquisition of morphology and chemical composition in 3D, facilitating the interpretation of chemical gradients of trace elements, quantification of solid solution compositions, inferences about temporal sequences of mineral precipitation, and addressing other concerns about solid-phase chemistry.

58 GEOSCIENCES↗
DOE OSTI2026

Comparing Tandem Cell Designs for Electrochemical CO 2 Reduction to Ethylene

Electrochemical carbon dioxide reduction (CO 2 R) is a promising approach for the decentralized production of fuels such as ethylene (C 2 H 4 ). However, the use of Cu, the most efficient metal CO 2 R catalyst for the generation of C 2 H 4 known to date, generally yields a product stream with poor selectivity. In an effort to increase selectivity, the reaction from CO 2 to C 2 H 4 can be broken down into two steps using tandem CO 2 R electrolyzers: formation of CO from CO 2 and subsequent reduction of CO to C 2 H 4 . Here, in this study, we present two novel tandem electrolyzer architectures that closely integrate two cathodes, one for CO generation and one for conversion to C 2 H 4 , while still enabling independent electrical control of the cathodic surfaces. Cathode segmentation in each of these designs also permits the controlled sequencing of mass flow of chemical intermediates in the order of Au to Cu cathode catalysts, in contrast to earlier work relying on uncontrolled, passive diffusion to facilitate the flow of chemical intermediates between catalysts. When comparing the performance of the newly developed electrolyzer cell designs with a dual electrolyzer system, we found that the dual electrolyzer system yields the highest C 2 H 4 faradaic efficiencies (FEs) of 31% and C 2 H 4 concentrations (∼8 mol %). However, a single Cu-containing electrolyzer outperformed all three tandem systems in terms of C 2 H 4 FE (34%). Our findings, enabled by independent control of the two tandem cathode surfaces, indicate that tandem CO 2 R systems need to be evaluated carefully by testing them at various relevant current densities.

C2H4↗