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At least 487 records · Page 27

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DOE OSTI2025

Energy, greenhouse gas, and water life cycle analysis of synthetic graphite anode production in the United States

This study presents a comprehensive life cycle analysis of potential synthetic graphite battery anode material (BAM) production in the U.S. based on industrial-scale data. The analysis focuses on three impacts: greenhouse gas (GHG) emissions, total energy use, and water consumption. We also conducted sensitivity analyses to evaluate the effect of variation in process parameters and energy sources used for synthetic graphite BAM production on its life cycle GHG emissions. A detailed supply chain analysis of graphite BAM in the U.S. was also undertaken, along with a study of its associated GHG emissions. The results show GHG emissions of 29.7 kg CO 2 -eq. per kg BAM, total energy use of 580 MJ kg −1 BAM, and water consumption of 121 L kg −1 BAM for the baseline condition. The graphitization step is a major process hotspot, contributing to over 74% of all impacts. This is attributed to the energy and material input requirements for this step, particularly through the use of crucibles. Across the entire synthetic graphite production process, electricity is the primary contributor, followed by crucibles used in graphite block production, and then calcined petroleum coke. Sensitivity analyses indicate that improvement in micronization yield, reuse of crucibles, and use of low-carbon nuclear energy can significantly reduce GHG emissions of potential domestic graphite production (by ∼70%). Supply chain analysis identified major graphite BAM sources in the U.S. and showed that the U.S. has a competitive advantage in domestic production of synthetic graphite BAM in terms of reduced life cycle GHG emissions compared to present-day imported sources (by ∼20%).

Battery anode↗

DOE OSTI2026

Quantifying Temperature Dependence of Pu(IV) Absorbance Spectra for Advanced Online Monitoring of Nuclear Processes

This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

CryoEM reveals the stochastic nature of individual ATP binding events in a group II chaperonin

Chaperonins are homo- or hetero-oligomeric complexes that use ATP binding and hydrolysis to facilitate protein folding. ATP hydrolysis exhibits both positive and negative cooperativity. The mechanism by which chaperonins coordinate ATP utilization in their multiple subunits remains unclear. Here we use cryoEM to study ATP binding in the homo-oligomeric archaeal chaperonin from Methanococcus maripaludis (MmCpn), consisting of two stacked rings composed of eight identical subunits each. Using a series of image classification steps, we obtained different structural snapshots of individual chaperonins undergoing the nucleotide binding process. We identified nucleotide-bound and free states of individual subunits in each chaperonin, allowing us to determine the ATP occupancy state of each MmCpn particle. We observe distinctive tertiary and quaternary structures reflecting variations in nucleotide occupancy and subunit conformations in each chaperonin complex. Detailed analysis of the nucleotide distribution in each MmCpn complex indicates that individual ATP binding events occur in a statistically random manner for MmCpn, both within and across the rings. Our findings illustrate the power of cryoEM to characterize a biochemical property of multi-subunit ligand binding cooperativity at the individual particle level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Exploring the effects of molecular beam epitaxy growth characteristics on the temperature performance of state-of-the-art terahertz quantum cascade lasers

This study conducts a comparative analysis, using non-equilibrium Green’s functions (NEGF), of two state-of-the-art two-well (TW) Terahertz Quantum Cascade Lasers (THz QCLs) supporting clean 3-level systems. The devices have nearly identical parameters and the NEGF calculations with an abrupt-interface roughness height of 0.12 nm predict a maximum operating temperature (T max ) of ~ 250 K for both devices. However, experimentally, one device reaches a T max of ~ 250 K and the other a T max of only ~ 134 K. Both devices were fabricated and measured under identical conditions in the same laboratory, with high quality processes as verified by reference devices. The main difference between the two devices is that they were grown in different MBE reactors. Our NEGF-based analysis considered all parameters related to MBE growth, including the maximum estimated variation in aluminum content, growth rate, doping density, background doping, and abrupt-interface roughness height. From our NEGF calculations it is evident that the sole parameter to which a drastic drop in T max could be attributed is the abrupt-interface roughness height. We can also learn from the simulations that both devices exhibit high-quality interfaces, with one having an abrupt-interface roughness height of approximately an atomic layer and the other approximately a monolayer. However, these small differences in interface sharpness are the cause of the large performance discrepancy. This underscores the sensitivity of device performance to interface roughness and emphasizes its strategic role in achieving higher operating temperatures for THz QCLs. We suggest Atom Probe Tomography (APT) as a path to analyze and measure the (graded)-interfaces roughness (IFR) parameters for THz QCLs, and subsequently as a design tool for higher performance THz QCLs, as was done for mid-IR QCLs. Our study not only addresses challenges faced by other groups in reproducing the record T max of ~ 250 K and ~ 261 K but also proposes a systematic pathway for further improving the temperature performance of THz QCLs beyond the state-of-the-art.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Relativistic resolution-of-the-identity with Cholesky integral decomposition

In this study, we present an efficient integral decomposition approach called the restricted-kinetic-balance resolution-of-the-identity (RKB-RI) algorithm, which utilizes a tunable RI method based on the Cholesky integral decomposition for in-core relativistic quantum chemistry calculations. The RKB-RI algorithm incorporates the restricted-kinetic-balance condition and offers a versatile framework for accurate computations. Notably, the Cholesky integral decomposition is employed not only to approximate symmetric large-component electron repulsion integrals but also those involving small-component basis functions. In addition to comprehensive error analysis, we investigate crucial conditions, such as the kinetic balance condition and variational stability, which underlie the applicability of Dirac relativistic electronic structure theory. Here we compare the computational cost of the RKB-RI approach with the full in-core method to assess its efficiency. To evaluate the accuracy and reliability of the RKB-RI method proposed in this work, we employ actinyl oxides as benchmark systems, leveraging their properties for validation purposes. This investigation provides valuable insights into the capabilities and performance of the RKB-RI algorithm and establishes its potential as a powerful tool in the field of relativistic quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Predictive outlook for experiments resolving prompt vs local redeposition of high- Z materials in tokamaks

High-Z plasma facing components redeposit within the sheath through a combination of two distinct mechanisms: prompt (or geometric-driven) and local (or sheath-driven) redeposition. Experimental efforts are needed to determine the leading-order parameters influencing prompt-vs-local trade-off, which sets the fraction of material entering the scrape-off layer. In preparation for such experiments, leading-order parameters are isolated within the PYEAD-RustBCA-GITR coupled net erosion code using Sobol’ sensitivity analysis. Then, experiments resolving prompt-vs-local trade-off under variation of these leading-order parameters are proposed using an isotopic coupon design with multifaceted diagnostic coverage. The measurability of these experiments is evaluated using synthetic diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

A variant selection framework for genome graphs

Abstract Motivation Variation graph representations are projected to either replace or supplement conventional single genome references due to their ability to capture population genetic diversity and reduce reference bias. Vast catalogues of genetic variants for many species now exist, and it is natural to ask which among these are crucial to circumvent reference bias during read mapping. Results In this work, we propose a novel mathematical framework for variant selection, by casting it in terms of minimizing variation graph size subject to preserving paths of length α with at most δ differences. This framework leads to a rich set of problems based on the types of variants [e.g. single nucleotide polymorphisms (SNPs), indels or structural variants (SVs)], and whether the goal is to minimize the number of positions at which variants are listed or to minimize the total number of variants listed. We classify the computational complexity of these problems and provide efficient algorithms along with their software implementation when feasible. We empirically evaluate the magnitude of graph reduction achieved in human chromosome variation graphs using multiple α and δ parameter values corresponding to short and long-read resequencing characteristics. When our algorithm is run with parameter settings amenable to long-read mapping (α = 10 kbp, δ = 1000), 99.99% SNPs and 73% SVs can be safely excluded from human chromosome 1 variation graph. The graph size reduction can benefit downstream pan-genome analysis. Availability and implementation https://github.com/AT-CG/VF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Superconducting phase diagram in Bi x Ni 1 – x thin films: The effects of Bi stoichiometry on superconductivity

The Bi-Ni binary system has been of interest due to possible unconventional superconductivity aroused therein, such as time-reversal symmetry breaking in Bi/Ni bilayers or the coexistence of superconductivity and ferromagnetism in Bi 3 ⁢Ni crystals. While Ni acts as a ferromagnetic element in such systems, the role of the strong spin-orbit coupling element Bi in superconductivity has remained unexplored. In this work, we systematically studied the effects of Bi stoichiometry on the superconductivity of Bi x ⁢Ni 1–x thin films (x ≈ 0.5–0.9) fabricated via a composition-spread approach. Here, the superconducting phase map of Bi x ⁢Ni 1–x thin films exhibited a superconducting composition region attributable to the intermetallic Bi 3 ⁢Ni phase with different amounts of excess Bi, revealed by synchrotron x-ray diffraction analysis. Interestingly, the mixed-phase region with Bi 3 ⁢Ni and Bi showed unusual increases in the superconducting transition temperature and residual resistance ratio as more Bi impurities were included, with the maximum T c (=4.2K) observed at x ≈ 0.79. A correlation analysis of structural, electrical, and magneto-transport characteristics across the composition variation revealed that the unusual superconducting “dome” is due to two competing roles of Bi: impurity scattering and carrier doping. We found that the carrier doping effect is dominant in the mild doping regime (0.74 ≤ x ≤ 0.79), while impurity scattering becomes more pronounced at larger Bi stoichiometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Cy-Phy ADS: Cyber Physical Anomaly Detection Framework for EV Charging Systems

Today’s large-scale Electric Vehicle (EV) infrastructures are heavily dependent on information communication technologies to maintain their operation and to support communication within sub-system components as well as the outside world. These technologies are vulnerable to various cyber and physical threats. Timely identification and mitigation of these threats are critical for improving human safety, avoiding economic losses, and preventing catastrophic system failures. By addressing this, our work presents a ResNet Autoencoder (AE) based Cyber-Physical Anomaly Detection System (Cy-Phy ADS) for detecting anomalies in EV Controller Area Network (CAN) protocol communication. It consists of four main components: Cyber-Physical Feature Extractor, ResNet AE-based Anomaly Detection Framework, Cyber-Physical Health Metric (CPHM), and Visualization Dashboard. The presented framework was trained and tested using CAN data collected from the EV charging system testbed at the Idaho National Laboratory. The presented Cy-Phy ADS compared against six widely used unsupervised anomaly detection algorithms: One Class Support Vector Machine (OCSVM), Variational Autoencoder (VAE), LSTM Autoencoder (LSTM AE), Isolation Forest (IForest), Principle Component Analysis (PCA) and Local Outlier Factor (LOF). Here the presented approach showed the highest accuracy among the compared methods. Further, the proposed approach showed comparable performance in terms of precision, F1, and False positive rate. It also showed the lowest training and inference time compared to the neural network-based baseline algorithms compared against with. Additionally, the Cy-Phy ADS has advantages such as unsupervised training, the ability to provide a holistic metric for system health characterization, and non-linear feature extraction.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

The Seismic Signature of a High-Energy Density Physics Laboratory and Its Potential for Measuring Time-Dependent Velocity Structure

The Z Machine at Sandia National Laboratories is a pulsed power facility for high-energy density physics experiments that can shock materials to extreme temperatures and pressures through a focused energy release of up to ~ 25 MJ in < 100 nanoseconds. It has been in operation for more than two decades and conducts up to ~ 100 experiments, or “shots,” per year. Based on a set of 74 known shot times from 2018, we determined that Z Machine shots produce detectable ~ 3–17 Hz ground motion 12 km away at the Albuquerque Seismological Laboratory, New Mexico (ANMO), borehole seismograph, with peak signal at ~ 7 Hz. The known shot waveforms were used to create a three-component template, leading to the detection of 2339 Z Machine shots since 1998 through single-station cross-correlation. Local seismic magnitude estimates range from local magnitude (M L ) —2 to —1.3 and indicate that only a small fraction of the shot energy is transmitted by seismic phases observable at 12 km distance. The most recent major facility renovation, which was intended to decrease mechanical dissipation, is associated with an abrupt decrease in observed seismic amplitudes at ANMO despite stable maximum shot energy. The highly repetitive impulsive sources are well suited to coda-wave interferometry to investigate time-dependent velocity structures. Relative velocity variations (dv/v) show an annual cycle with amplitude of ~ 0.2%. Local minima are observed in the late spring, and dv/v increases through the summer monsoon rainfall, possibly reflecting patchy saturation as rainfall infiltrates near the eastern edge of the Albuquerque basin. Importantly, the cumulative results demonstrate that forensic seismology can provide insight into long-term operation of facilities such as pulsed-power laboratories, and that their recurring signals may be valuable for studies of time-dependent structure

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Sulfur speciation in dacitic melts using X-ray absorption near-edge structure spectroscopy of the S K -edge (S-XANES): Consideration of radiation-induced changes and the implications for sulfur in natural arc systems

Abstract The synchrotron technique of micro X-ray absorption near-edge structure spectroscopy at the sulfur K-edge (S-XANES) provides a unique opportunity to measure the proportion of different oxidation states of sulfur (S) in silicate glasses. Although applied extensively in the analysis of basaltic silicate glasses, few S-XANES studies have investigated variations in S oxidation states with fO2 in felsic silicate glasses. In addition, no study has systematically compared the S-XANES results obtained from the same samples at different photon flux densities to quantify the relationship between exposure time and changes in S speciation in silicate glass, as has been done for Fe and V. This study evaluates observed differences in S speciation measured in experimentally produced H2O-saturated dacitic glasses over a range of reducing to oxidizing conditions (from log fO2 = ΔFMQ-0.7 to ΔFMQ+3.3; FMQ is the fayalite-magnetite-quartz mineral redox buffer) and equilibrated at 1000 °C and 300 MPa. S-XANES spectra were collected at three different photon flux densities using three microspectroscopy beamlines. As is observed in S-XANES analyses of basaltic silicate glasses, beam-induced changes to the S6+/ΣS are observed as a function of photon flux density and beam exposure time. Our results demonstrate that silicate glasses of dacitic composition undergo beam-induced photo-reduction in samples equilibrated at ΔFMQ > +1.75 and photo-oxidation if equilibrated at ΔFMQ < +1. The time required to observe beam-induced changes in the spectra varies as a function of flux density, and our study establishes an upper photon density limit at ~1.0 × 1012 photons/µm2. The S6+/ΣS calculated from spectra collected below this absorbed photon limit at intermediate flux densities (~1–4 × 109 photons/s per µm2) are affected by beam damage, as no conditions were found to be completely free of beam-induced changes. However, the S6+/ΣS ratios calculated below the limit at intermediate flux densities are consistent with thermodynamic constraints, demonstrating that S6+/ΣS ratios calculated from S-XANES spectra can be considered reliable for estimating the oxygen fugacity. Our results carry important implications for the S budget of felsic magmas and dissolution mechanisms in evolved melts. While our results from all three flux densities show the presence of S4+ dissolved in relatively oxidized (ΔFMQ > +1.75) dacitic glass, even in the spectra exposed to the lowest photon densities, we are unable to rule out the possibility that the S4+ signal is the result of instantaneous X-ray irradiation induced beam damage using S-XANES alone. When our spectra are compared to S-XANES spectra from basaltic silicate glasses, important differences exist in the solubility of S2– and S6+ between dacitic silicate melts, pointing to differences in solubility mechanisms as melt composition changes. This study highlights the need for further investigation into beam damage systematics, presence of S4+, and the solubility mechanisms of different oxidation states of S as silicate melt composition changes.

Geochemistry & Geophysics↗

DOE OSTI2023

Evaluation of Historic Nuclear Cloud Measurement for Entrainment Parameter Determination

We evaluated the uncertainties associated with the entrainment parameters computed from nuclear cloud measurements taken during historic weapon testing campaigns. This evaluation found that variations in the way cloud heights and diameters were defined during the analysis of film records result in very large uncertainties in the entrainment parameters, severely limiting the utility of these data. For the measurements of atmospheric conditions at the time of the tests, the main sources of error are associated with the differences in the location and timing of the soundings.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2022

On the Existence of Fast Modes in Compressible Magnetohydrodynamic Turbulence

Abstract We study the existence and properties of fast magnetosonic modes in 3D compressible MHD turbulence by carrying out a number of simulations with compressible and incompressible driving conditions. We use two approaches to determine the presence of fast modes: mode decomposition based on spatial variations only and spatio-temporal 4D fast Fourier transform (4D FFT) analysis of all fluctuations. The latter method enables us to quantify fluctuations that satisfy the dispersion relation of fast modes with finite frequency. Overall, we find that the fraction of fast modes identified via the spatio-temporal 4D FFT approach in total fluctuation power is either tiny with nearly incompressible driving or ∼2% with highly compressible driving. We discuss the implications of our results for understanding the compressible fluctuations in space and astrophysical plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Identification of uncommon objects in containers

A system for identifying in an image an object that is commonly found in a collection of images and for identifying a portion of an image that represents an object based on a consensus analysis of segmentations of the image. The system collects images of containers that contain objects for generating a collection of common objects within the containers. To process the images, the system generates a segmentation of each image. The image analysis system may also generate multiple segmentations for each image by introducing variations in the selection of voxels to be merged into a segment. The system then generates clusters of the segments based on similarity among the segments. Each cluster represents a common object found in the containers. Once the clustering is complete, the system may be used to identify common objects in images of new containers based on similarity between segments of images and the clusters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Geological characterization and ROZ potential of the Tar Springs Sandstone

This report focuses on regional and field scale geological characterization of the Tar Springs in Illinois using well records, including drilling and completion reports, well logs, and core data (core descriptions/core analyses) to analyze and interpret geological variations. In addition, oil saturation indicators (oil shows, oil saturation from core analysis, and drill stem test data) were analyzed to determine the ROZ potential of the Tar Springs Sandstone

02 PETROLEUM↗

DOE OSTI2023

An Interpretable Index of Social Vulnerability to Environmental Hazards

Index-based measures of social vulnerability to environmental hazards are commonly modeled from composites of population-level risk factors. These models overlook individual context in communities' experiences of environmental hazards, producing metrics that may hinder spatial decision support for mitigating and responding to hazards. This paper introduces an interpretable, high-resolution model for generating an individual-oriented social vulnerability index (IOSVI) for the United States built on synthetic populations that couples individual and social determinants of vulnerability. The IOSVI combines an individual vulnerability index (IVI) that ranks individuals in an area’s synthetic population based on intersecting risk factors, with a social vulnerability index (SVI) based on the population’s cumulative distribution of IVI scores. Interpretability of the IOSVI procedure is demonstrated through examples of national, metropolitan, and neighborhood (census tract) level spatial variation in index scores and IVI themes, as well as an exploratory analysis examining risk factors affecting a specific sub-population (military veterans) in areas of high social and environmental vulnerability.

Tuccillo, Joe↗

DOE OSTI2026

Hybrid Cooling and Water Treatment for Resilient, Water-Self-Sufficient Data Centers

The continued growth of data center infrastructure is intensifying demand for freshwater resources, particularly in water-stressed regions, and is increasingly limiting sustainable capacity expansion. This work investigates a conceptual hybrid system that integrates freeze desalination with ultrasonic-assisted ice separation to enable on-site production of pure water from diverse sources, including seawater, brackish groundwater, and reclaimed industrial or agricultural wastewater. Simultaneously, the system produces low-temperature cooling streams that enhance heat removal in high power density computing environments. A process-level thermodynamic analysis is performed across a range of boundary and operating conditions, including variations in feed concentration, freezing temperature, and mass flow rate. The results are presented as performance curves relating feedwater concentration and target purified water output to the corresponding intake flow requirements, enabling estimation of source water demand per unit of Information Technology Equipment (ITE) energy consumption (kWh) across varying data center scales and operational scenarios. The corresponding electrical energy consumption for integrated cooling and water treatment is also evaluated as a function of system operating parameters and target water production levels. These results provide a basis for evaluating system feasibility across different conditions and for identifying parameter ranges in which integrated water treatment and cooling improve resource efficiency, thermal performance, and operational flexibility in data centers.

Elhefny, Aly [ORNL] (ORCID:0000000284907923)↗

DOE OSTI2024

Deciphering controls on metal migration within floodplains: The critical role of redox environments on metal-organic complexes (Final Technical Report)

Our project elucidates the effect of differing hydrologic regimes on nutrient and contaminant dynamics within floodplains, and we explore the impact of varying sources of hydrologic extremes on nutrient-contaminant fate and transport. We use a combination of field measurements and laboratory experiments to examine the relationships between redox conditions, functionality of dissolved organic matter, metal speciation (specifically examining metal-ligand complexes), and nutrient-contaminant fate, particularly during hydrologic extremes. Floodplain biogeochemical variation through climatic extremes and beaver-induced hydrologic variation provide a unique look at controls on nutrient-contaminant fate and transport. Through our work, we have developed a novel approach that provides an unprecedented ability to resolve aqueous metal-organic complexes that reveals metal binding preferences for natural organic matter based on metal-ligand chemistry. We have developed novel methods to separate, quantify, and characterize organic-metal complexes in natural DOM that pair with field experiments comprising floodplains having systematic variation in biogeochemical conditions. We also developed a comprehensive computational approach for molecular characterization of metal-organic species that merges LC-coupled high resolution (HR) mass spectrometry and ICP-MS analysis. Importantly, we show that beaver dams have an outsized influence on hydrologic extremes, dwarfing the impact of climatic variation, that ultimate control biogeochemical conditions and water quality. Additionally, beaver dams impose a hydrologic driver that leads to improved, river water quality by divert water through soils and the hyporheic zone. We further show that iron(III) minerals have a dominant control on carbon mineralization across floodplains independent of hydrologic conditions, and that iron and aluminum associations with organic matter are a controlling factor in carbon mineralization. Ultimately, our work is helping to advancing a robust predictive understanding of how hydrologic changes in watersheds affect water quality and carbon and metal cycling in riparian zones.

54 ENVIRONMENTAL SCIENCES↗