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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Polaronic Quasiparticles in the Valence-Transition Compound TmSe 1−𝑥⁢ Te 𝑥

Exotic quasiparticle states have been proposed in mixed-valent compounds exhibiting valence transitions. However, clear spectroscopic evidence identifying these states has remained elusive. Here, using synchrotron-based hard x-ray and extreme ultraviolet photoemission spectroscopy, we have probed the Tm 3⁢𝑑 and 4⁢𝑓 emissions in TmSe 1−𝑥 ⁢Te 𝑥 , where a Te concentration-dependent semimetal–insulator transition occurs alongside the valence transition. Our photoemission results, which are characteristic of the bulk, track this combined transition across the critical concentration (𝑥 𝑐 = 0.29). Notably, our results reveal a noninteger valence for the insulating phase and a novel quasiparticle excitation in the semimetallic phase: a Holstein polaron that extends beyond the standard periodic Anderson model.

Min, Chul H. [Christian-Albrechts-Univ. zu Kiel (G↗
DOE OSTI2025

Observation of Unprecedented Fractional Magnetization Plateaus in a New Shastry-Sutherland Ising Compound

Geometrically frustrated magnetic systems, such as those based on the Shastry-Sutherland lattice (SSL), offer a rich playground for exploring unconventional magnetic states. The delicate balance between competing interactions in these systems leads to the emergence of novel phases. We present the characterization of Er 2 ⁢Be 2⁢ GeO 7 , an SSL compound with Er 3+ ions forming orthogonal dimers separated by nonmagnetic layers whose structure is invariant under the 𝑃⁢$\bar{4}21$⁢𝑚 space group. Neutron scattering reveals an antiferromagnetic dimer structure at zero field, typical of Ising spins on that lattice and consistent with the anisotropic magnetization observed. However, magnetization measurements exhibit fractional plateaus at 1/4 and 1/2 of saturation, in contrast to the expected 1/3 plateau of the SSL Ising model. By comparing the energy of candidate states with ground-state lower bounds we show that this behavior requires spatially anisotropic interactions, leading to an anisotropic Shastry-Sutherland Ising model symmetric under the 𝐶⁢𝑚⁢𝑚⁢2 space group. This anisotropy is consistent with the small orthorhombic distortion observed with single-crystal neutron diffraction. The other properties, including thermodynamics, which have been investigated theoretically using tensor networks, point to small residual interactions, potentially due to further couplings and quantum fluctuations. This study highlights Er 2 ⁢Be 2 ⁢GeO 7 as a promising platform for investigating exotic magnetic phenomena.

Yadav, Lalit [Duke University, Durham, NC (United ↗
DOE OSTI2025

Manipulating Cu vacancy in Yb triangular lattice Materials: Investigating the quantum disordered compound CuYbSe 2 and spin glass Cu 2.73 ⁢YbP 2

Yb-based triangular lattice materials have attracted significant attention due to their potential for hosting exotic magnetic quantum states. In this paper, we report the structural, magnetic, and thermodynamic properties of two Yb triangular lattice compounds with vacancy disorder at nonmagnetic Cu sites: CuYbSe 2 and Cu 2.73 ⁢YbP 2 . Single-crystal x-ray diffraction determines notable Cu-site vacancies in both materials. Unlike a single Cu site with 0.5 occupancy in CuYbSe 2 , Cu 2.73 ⁢YbP 2 only presents 27% vacancies on one of three Cu sites. Magnetic susceptibility measurements indicate dominant antiferromagnetic interactions between Yb 3+ ions. The effective magnetic moment is consistent with an effective spin-1/2 state of Yb 3+ . CuYbSe 2 exhibits strong magnetic anisotropy between in-plane and out-of-plane directions with the estimated exchange interactions 𝐽 𝑎 /𝑘 B = 6.48 K and 𝐽 𝑐 /𝑘 B = 2.55 K. No magnetic ordering is observed down to 0.4 K, supporting its quantum disordered ground state and candidacy as a quantum spin liquid. In contrast, Cu 2.73 ⁢YbP 2 shows clear evidence of spin freezing at 4.5 K in both magnetization and heat capacity data, indicating a spin glass state. The field-induced magnetic orders are found in CuYbSe 2 . These results highlight the critical role of structural vacancies in perturbing Yb-based triangular lattices. In conclusion, we demonstrate that while the intrinsic Yb triangular lattices are comparable, the presence of Cu vacancies can fundamentally alter the magnetic ground state—tuning the system between quantum disordered and spin glass behavior.

Frustrated magnetism↗
DOE OSTI2024

Origin of metal-insulator transitions in the parent compounds of ruthenium-pnictide superconductors

Here we study the interplay of the structural phase transition, flat electronic band dispersion, and metal-to-insulator transition (MIT) in the parent compounds of the Ru-pnictide superconductors by using first-principles calculations. Our electron and phonon calculations reveal that Ru(P,As) undergo MIT accompanied by orthorhombic to monoclinic distortion at low temperature, but RuSb stays orthorhombic and metallic in agreement with the experimental findings. It is demonstrated that electronic correlation, as treated in DFT + U, DFT + Gutzwiller, and dynamical mean-field theory (DMFT), cannot induce MIT in the undistorted crystal structure. We find that, although small monoclinic distortion can remove the van Hove singularity at the Fermi level, it does not immediately gap out the Fermi surface and a large value of monoclinic distortion is necessary for a clear MIT, suggesting the possibility of an intermediate pseudogapped monoclinic metallic phase. Furthermore, we predict a light-induced two-step insulator-to-metal and structural transitions in the monoclinic phases of RuP and RuAs, which can be tested in future ultrafast pump-probe experiments as an alternative ideal playground to VO 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Microscopic origin of temperature-dependent magnetism in spin-orbit-coupled transition metal compounds

A few 4 d and 5 d transition metal compounds with various electron fillings were recently found to exhibit magnetic susceptibilities χ and magnetic moments that deviate from the well-established Kotani model. This model has been considered for decades to be the canonical expression for descriing the temperature dependence of magnetism in systems with nonnegligible spin-orbit coupling effects. In this paper, we uncover the origin of such discrepancies and determine the applicability and limitations of the Kotani model by calculating the temperature dependence of the magnetic moments of a series of 4 d (Ru-based) and 5 d (W-based) systems at different electron fillings. For this purpose, we perform exact diagonalization of -derived relativistic multiorbital Hubbard models on finite clusters and compute their magnetic susceptibilities. Comparison with experimentally measured magnetic properties indicates that contributions such as a temperature-independent χ 0 background, crystal field effects, Coulomb and Hund's couplings, and intersite interactions—not included in the Kotani model—are especially crucial for correctly describing the temperature dependence of χ and magnetic moments at various electron fillings in these systems. Based on our results, we propose a generalized approach beyond the Kotani model to accurately describe their magnetism. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Deuteron Evaporation from N = Z Compound Nuclei

Deuteron evaporation was observed from the N = Z compound nuclei 52 Fe ⋆ , 56 Ni ⋆ , and 64 Ge ⋆ in an experiment conducted at Argonne National Laboratory, USA. The experiment included a novel combination of two highly pixelated double-sided Si-strip detectors inside the Microball chargedparticle detection array, allowing for unequivocal discrimination of evaporated deuterons from protons and α particles. In conjunction with the Gammasphere array, Neutron Shell, and additional ancillary detectors, decay paths into various residual nuclei were investigated. The study provides insights into the competition of deuteron vs. proton-neutron evaporation as a function of available excitation energy and populated angular momentum. Results are interpreted using a statistical evaporation formalism for multiple subsequent particle emissions. The decisive factor in the comparison appears to be the available excitation energy in the residual system, with single nucleon evaporation preferred over deuteron evaporation for higher excitation energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Codimension-two spiral spin liquid in the effective honeycomb-lattice compound Cs 3 ⁢Fe 2 ⁢Cl 9

A codimension-two spiral spin liquid is a correlated paramagnetic state with one-dimensional ground state degeneracy hosted within a three-dimensional lattice. Here, in this work, via neutron scattering experiments and numerical simulations, we establish the existence of a codimension-two spiral spin liquid in the effective honeycomb-lattice compound Cs 3 ⁢Fe 2⁢ Cl 9 , which demonstrates an alternate path to spiral spin liquids by overcoming the long-standing impediment of weak further-neighbor interactions. In the long-range ordered regime, competing spiral and spin density wave orders emerge as a function of applied magnetic field, among which a possible order-by-disorder transition is identified.

Monte Carlo methods↗
DOE OSTI2024

Intelligent Electrochemical Sensors for Precise Identification of Volatile Organic Compounds Enabled by Neural Network Analysis

The volatile organic compounds (VOCs) in a wide spectrum of categories were identified as biomarkers in aquatic environments, playing an important role in marine and freshwater ecology and global atmospheric chemistry. VOCs released from biofuel have also attracted increasing attention. Although the importance has been recognized, the portable detection and analysis methods of VOC in aquatic systems have not yet been well developed and understood. Here, in this work, we innovatively proposed an intelligent electrochemical sensing approach to classify and quantify VOCs in solution. Utilizing the cyclic voltammetry (CV) method with an ionic liquid (IL)-based electrolyte, we analyzed 50 μL samples of various VOC analytes, including acetic acid (AC), acetone, dimethylformamide (DMF), dimethyl sulfoxide (DMSO), ethanol, formaldehyde, formic acid, methanol, methyl formate (MF), toluene, and a formaldehyde-methanol mixture, along with deionized water (DI water). The generated voltammograms were subsequently analyzed using our uniquely designed and optimized 1-D convolutional neural network (1D-CNN). This deep-learning algorithm achieved a 99.09% accuracy in VOC classification validated through fivefold cross-validation and demonstrated an impressive 94.4% test accuracy for methanol detection within a 10 μL error range. For quantification, the system accurately categorized methanol volumes ranging from 0 to 50 μL in 10 μL increments, achieving a 98.18% accuracy. A notable linear correlation (R2 = 95.56%) was found between max current density at the oxidation peak and methanol volume, with the limit of detection (LOD) at 9.3 μL. Such a sensing method exhibits potential for portability, high accuracy, and generalization in the classification and quantification, ultimately reshaping the realm of VOC analysis in solution.

42 ENGINEERING↗
DOE OSTI2024

A Compound Data Poisoning Technique with Significant Adversarial Effects on Transformer-based Sentiment Classification Tasks

Transformer-based models have demonstrated much success in various natural language processing tasks. However, they are often vulnerable to adversarial attacks, such as data poisoning, which can intentionally fool the model into generating incorrect results. In this article, we present a novel, compound variant of a data poisoning attack on a transformer-based model that maximizes the poisoning effect while minimizing the scope of poisoning. Here we do so by combining the established data poisoning technique (label flipping) with a novel adversarial artifact selection and insertion technique aimed at minimizing detectability and the scope of the poisoning footprint. We find that by using a combination of these two techniques, we achieve a state-of-the-art attack success rate of approximately 90% while poisoning only 0.5% of the original training set, thus minimizing the scope and detectability of the poisoning action. These findings have the potential to advance the development of better data poisoning detection methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Model data for infrastructure-aware simulation of compound flooding at Alligator Bayou Watershed, southeast Texas

This dataset supports infrastructure-aware hydrologic modeling and flood scenario analysis for the Alligator Bayou Watershed, a highly managed urban watershed in Southeast Texas. It includes Jupyter notebooks for figure reproduction, model configuration files, simulation outputs, and derived products used to quantify the influence of engineered stormwater infrastructure on flood behavior across multiple spatial scales. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations on a channel-aligned mesh with explicit representations of pump stations, gate structures, detention basins, and impervious surfaces. Outputs include time series of gate and pump flows, stage observations, and water balance components, as well as spatially explicit fields of peak ponded depth and flood duration across multiple infrastructure scenarios spanning a single-location detention basin expansion, distributed drainage limitations, and compound coastal flooding. These data facilitate full reproducibility of the manuscript figures and support further research on urban flood dynamics and the role of stormwater infrastructure in shaping watershed-scale flood response.

EARTH SCIENCE > OCEANS > COASTAL PROCESSES↗
DOE OSTI2024

IC w22_phadiagractox Highlight: Composition-dependent melting temperature of a compound [Poster]

Figure 1 displays, ambient melting points of the Au-Cu system as a function of Cu atomic percent: present model vs. experimental data from four different sources. Figure 2 displays, ambient melting points of the U-O system as a function of O atomic percent: present model vs. both experiment and quantum molecular dynamics (QMD) simulations on the stoichiometric U-O compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Gas-Phase Oxidation Mechanisms of Nitrogen-Containing Organic Compounds

Nitrogen-containing organic molecules play essential roles in nearly every aspect of chemistry. The importance of these species within gas-phase chemistry has increased in recent years, due to their emissions from wildfires, crude biofuels, ammonia combustion, and CO 2 capture facilities. However, there is a lack of detailed relevant mechanistic and kinetic studies of N-compounds, resulting in poor representation of these pathways within chemical models. In this report, we detail our exploration of the gas-phase oxidation mechanisms of pyrrole, imidazole, pyrrolidine, methylamine, and dimethylamine, done by employing multiplexed VUV photoionization mass spectrometry coupled with KinBot, a computational tool that automatically explores multi-well potential energy surfaces. Overall, we vastly expanded the known gas-phase oxidation mechanisms and chemical kinetics of these species. This work will improve the accuracy and completeness of atmospheric and combustion chemistry models, ultimately leading to better-informed decision-makers in the energy and environmental sectors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Bioremediation of Chlorinated Volatile Organic Compounds: DOE Experiences and Lessons Learned

From the mid-1980s to the present, the Department of Energy (DOE) has developed, tested, and deployed diverse bioremediation strategies for chlorinated volatile organic compounds (cVOCs). A systematic review of these projects after decades of activity provides an opportunity to identify crosscutting themes and lessons learned. The knowledge provided by a DOE bioremediation retrospective represents a resource to support current and future bioremediation operations, and future decisions related to cVOC bioremediation. This systematic review examined the design, objectives, performance and outcomes for remediation projects at DOE sites including Savannah River, Hanford, Idaho, Mound and Pinellas. The results were used to identify emergent themes to provide actionable insights. The bioremediation retrospective technical team first developed standardized criteria to support the systematic review. Then, the evaluation was performed using a sequential process that was informed by local technical experts who identified and provided the structured information that served as the basis for the evaluation. The participation of these experts was invaluable to the effort. Importantly, DOE cVOC bioremediation efforts were implemented based on the foundational knowledge developed by U.S. Department of Defense (DoD) strategic and applied environmental technology development and certification programs, as well as technical, policy and regulatory guidance from the U.S. Environmental Protection Agency (EPA), Interstate Technology and Regulatory Council (ITRC), U.S. Geological Survey (USGS), industry, and universities. To maximize the value of the DOE cVOC bioremediation retrospective, the systematic review strategy focused on identifying important DOE-specific experiences, trends and lessons learned that would extend the knowledge available from these other key entities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Analyzing Tradeoffs Associated with the Manufacture of Refined Fuels by Comparing Volatile Organic Compound (VOC) Emissions Model Results with Carbon Impacts

A first-of-its kind, publicly-available model for estimating emissions of volatile organic compounds from operations along the supply chain of liquid fuels and refinery products is presented and demonstrated. This standardized model permits comprehensive, reproducible, and comparable evaluation of the supply chain/life cycle VOC emissions of liquid fuels and refinery products.

09 BIOMASS FUELS↗
DOE OSTI2025

Finch: Toxicity Dose Response Curve Prediction of Chemical Compounds and Mixtures

A paradigm shift in chemical risk assessment is emphasizing mixture testing over single compound analysis, eliminating animal testing, and adopting advanced modeling approaches to understand mixture activity profiles. However, existing computational models largely focus on single chemicals, with few effective solutions for modeling complex mixtures that account for synergistic or antagonistic effects and multiple Modes of Action (MoA). Conventional methods like concentration addition (CA) and independent action (IA) are insufficient for this task as they are designed for simplistic interactions and struggle to account for the dynamic and multifaceted nature of chemical mixtures, such as overlapping MoA and non-linear interactions. Finch offers a novel approach utilizing deep learning (DL) embeddings and multi-task quantitative structure-activity relationship (QSAR) models to improve chemical exposure prediction. By leveraging molecular descriptors, physiochemical properties, and large language model (LLM) embeddings from SMILES inputs, Finch preserves critical information in a latent space thereby enhancing predictive accuracy. The multi-task learning aspect of Finch is highly advantageous, as it simultaneously optimizes multiple loss functions, leveraging all available data across tasks to develop generalized representations that effectively capture complex ingredient interactions within mixtures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bacterial Volatile Organic Compounds as a Strategy to Increase Drought Tolerance in Maize (Zea mays L.): Influence on Plant Biochemistry

Maize is highly susceptible to drought, which affects growth and yield. This study investigated how bacterial volatile organic compounds (BVOCs) affect maize drought tolerance. Drought reduced shoot size but increased root length, an adaptation for accessing deeper soil moisture. BVOCs from strain D12 significantly increased root length and shoot growth under drought conditions. Drought also altered root biochemistry, decreasing enzyme activity, and increased osmolyte levels. BVOCs from strains F11 and FS4-14 further increased osmolyte levels but did not protect membranes from oxidative damage, while BVOCs from strains D12 and D7 strains reduced osmolyte levels and cell damage. In shoots, drought increased the levels of osmolytes and oxidative stress markers. BVOCs from FS4-14 had minimal effects on shoot biochemistry. BVOCs from D12 and F11 partially restored metabolic activity but did not reduce cell damage. BVOCs from D7 reduced metabolic activity and cell damage. These results suggest that BVOCs can modulate the biochemical response of maize to drought, with some strains evidencing the potential to enhance drought tolerance.

Lopes, Tiago (ORCID:0000000330603315)↗
DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗
DOE OSTI2024

Spectroscopic Analysis of Pu-bearing Compounds in Double-Walled Cells

Spectroscopic analysis of radiological materials has been historically limited to radiological labs with 11 older or less advanced scientific instrumentation. The development of double-walled cells (DWCs) at 12 the Savannah River National Laboratory (SRNL) has enabled Pu-bearing compounds to be removed 13 from radiological laboratories and studied in our radiologically clean spectroscopy lab with state-of14 the-art instrumentation. In this manuscript, we discuss the contributions of DWCs that have allowed 15 the application of Raman spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy 16 (DRIFTS), diffuse reflectance spectroscopy (DRS) in the shortwave infrared, and gamma 17 spectroscopy at SRNL. Significant advances have been made in the understanding of thermal 18 decomposition of Pu(III) and Pu(IV) oxalates, the alpha-induced damage to the PuO2 crystal lattice, 19 and the effect of calcination temperatures to the quality of PuO2. These techniques have enabled 20 methods to conduct PuO2 age dating since last calcination and estimate the calcination temperature 21 with Raman and DRS. Additional spectroscopic information measured with DRIFTS has provided a 22 path to observe the evolution of carbon species with calcination temperature while gamma 23 spectroscopy provides information on age dating since last purification.

Villa-Aleman, Eliel↗