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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of Solvents on Lignin–Surface Interactions via Molecular Dynamics Simulations

Lignin, an essential building block of lignocellulosic biomass, is a potential abundant source of aromatic monomers for the polymer and chemical industry. Reductive catalytic fractionation (RCF) is one promising process that can produce high yields of phenolic monomers and oligomers from lignin under different catalytic conditions. An important choice in optimizing RCF is the selection of solvent; however, detailed insights into solvent effects on lignin behaviors and interactions remain limited. Here, in this work, we perform all-atom molecular dynamics simulations to study the solvation of lignin, solvent-mediated conformational changes, and the interaction of solvated lignin oligomers with model surfaces. We focus on the behavior of an oligomeric lignin model compound in methanol, ethanol, a binary mixture of ethanol and water, and water at both the RCF reaction temperature (473 K) and room temperature. Analysis of structural features of lignin suggests that these three organic solvent systems favorably solvate lignin, resulting in a more extended conformation suitable for catalytic conversion to valuable chemicals. We further introduce model palladium (Pd) and carbon (C) surfaces to understand how solvent choice impacts adsorption onto a representative catalytic surface and support, and to quantify the competition among the reactant and solvent molecules for the surface. Unbiased simulations suggest strong adsorption of lignin on both Pd and C surfaces at 473 K, with notable solvent-mediated differences in adsorption energies. Additionally, our findings indicate that lignin adsorption is promoted by the entropy change resulting from the displacement of solvent molecules from the surface. This study provides a molecular perspective of adsorption of lignin onto varying surfaces, which is a step towards understanding and optimizing the catalytic conversion of lignin into valuable chemicals.

adsorption↗
DOE OSTI2025

Combining coordination and chelation moieties to engineer a new linker for lanthanide coordination chemistry

Organic linkers play a crucial role in constructing lanthanide (Ln) coordination polymers (CPs), influencing structural topologies and physicochemical properties. Herein, we introduce 6-oxo-1,6-dihydro-2,5-pyridinedicarboxylic acid (2,5-H 3 PODC) as a new ligand for constructing lanthanide coordination polymers that integrates the structural features of terephthalic acid with the chelation capabilities of pyridinone-based functional groups. Six lanthanide-based coordination polymers were synthesized with 2,5-H 3 PODC, forming two types of CPs – type 1: [Ln(HPODC)(Ox) 0.5 (H 2 O) 2 ] (where (Ox) = oxalic acid and Ln = Pr 3+ (1), Nd 3+ (2)) and type 2: [Ln(H 2 PODC)(HPODC)(H 2 O)] (Ln = Eu 3+ (3), Gd 3+ (4), Dy 3+ (5), Er 3+ (6)). All compounds were structurally characterized by single-crystal and powder X-ray diffraction, and both compound types are 2D ladder-like networks with cem topologies where the trivalent metal centers are bridged via HPODC 2− and Ox 2− ligands in type 1 structures and H 2 PODC − and HPODC 2− linkers in type 2 structures. Thermogravimetric analysis (TGA) demonstrated that the metal–organic networks of type 1 and type 2 compounds exhibit distinct decomposition patterns, and the photoluminescent properties of 3 were also examined, revealing efficient ligand based sensitization and characteristic emission bands for Eu(III).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
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 OSTI2025

Structural architecture of TolQ-TolR inner membrane protein complex from opportunistic pathogen Acinetobacter baumannii

Gram-negative bacteria harness the proton motive force (PMF) within their inner membrane (IM) to uphold cell envelope integrity, an indispensable aspect for both division and survival. The IM TolQ-TolR complex is the essential part of the Tol-Pal system, serving as a conduit for PMF energy transfer to the outer membrane. Here we present cryo–electron microscopy reconstructions ofAcinetobacter baumanniiTolQ in apo and TolR-bound forms at atomic resolution. The apo TolQ configuration manifests as a symmetric pentameric pore, featuring a transmembrane funnel leading toward a cytoplasmic chamber. In contrast, the TolQ-TolR complex assumes a proton nonpermeable stance, characterized by the TolQ pentamer’s flexure to accommodate the TolR dimer, where two protomers undergo a translation-based relationship. Our structure-guided analysis and simulations support the rotor-stator mechanism of action, wherein the rotation of the TolQ pentamer harmonizes with the TolR protomers’ interplay. These findings broaden our mechanistic comprehension of molecular stator units empowering critical functions within the Gram-negative bacterial cell envelope.

Science & Technology - Other Topics↗
DOE OSTI2024

The direct and indirect drivers shaping RNA viral communities in grassland soils

ABSTRACT Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from bulk metatranscriptomes sequenced from grassland soils managed for 5 years under multiple environmental conditions including water content, plant presence, cultivar type, and soil depth. More than half of the unique RNA viral contigs (64.6%) were assigned with putative hosts. About 74.7% of these classified RNA viral contigs are known as eukaryotic RNA viruses suggesting eukaryotic RNA viruses may outnumber prokaryotic RNA viruses by nearly three times in this grassland. Of the identified eukaryotic RNA viruses and the associated eukaryotic species, the most dominant taxa were Mitoviridae with an average relative abundance of 72.4%, and their natural hosts, Fungi with an average relative abundance of 56.6%. Network analysis and structural equation modeling support that soil water content, plant presence, and type of cultivar individually demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members. A significant negative influence of soil depth on soil eukaryotic richness and abundance indirectly impacts soil eukaryotic RNA viral communities. These results provide new insights into the collective influence of multiple environmental and community factors that shape soil RNA viral communities and offer a structured perspective of how RNA virus diversity and ecology respond to environmental changes. IMPORTANCE Climate change has been reshaping the soil environment as well as the residing microbiome. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil. This knowledge is critical for predicting the viral responses to climate change and the potential emergence of biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Computational Analysis of the Effect of Structured Packing Design on Absorption Column Hydrodynamics for Post-Combustion Carbon Capture Applications

Solvent based post-combustion carbon capture technologies have a potential for reducing carbon emissions from fossil-fuel-fired power plants and industrial sources where CO2 emissions are inherently harder to mitigate, such as steel or cement industries. A prominent technology to achieve this is by retrofitting absorption columns to the existing infrastructure. While these systems have been among the less costly alternatives for carbon capture, they still impose a considerable energy penalty to the operation of power plants or industrial facilities. The optimization of CO2 capture rate in solvent-based absorption process is complex as it depends on several factors including CO2 solubility, solvent reaction kinetics and temperature effects on the solubility, reaction rates, surface tension, and thermophysical properties of the solvent and the flue gas. The overall heat and mass transfer also depends on the hydrodynamics, which in turn, is affected by the packing geometry. In the current work, we systematically quantify the effects the design of the structured packing has on the column hydrodynamics, by performing detailed CFD simulations for different geometrical configurations and operating conditions. We then obtain relationships between the key hydrodynamic metrics, such as liquid holdup, interfacial area, wetted area, and pressure drop to the parameters defining the packing geometries and identify new more effective packing designs for the given operating conditions.

Shah, Yash Girish↗
DOE OSTI2024

Sierra/SD – Verification Test Manual – 5.22

Verification and validation (V&V) of scientific computing programs are important at Sandia National Labs due to the expanding role of computational simulation in managing the United States nuclear stockpile. The complexities of structural response calculations used to analyze physical problems, the varieties of codes applied to the calculations, and the importance of accurate predictions when assessing field conditions demand confidence in the consistency and accuracy of computer codes. Confidence in the accuracy of the predictions arising from computer simulations must ultimately be gained through verification and validation. The Sierra salinas structural dynamics analysis code, Sierra/SD, is used at the DOE Laboratories, and in several DOD projects. The roles of Sierra/SD in the qualification of weapon systems and components for normal and hostile environments throughout the Stockpile-to-Target Sequence include to, • Redesign weapon components. • Certify weapon components and systems for target environments such as hypersonic vehicles. • Certify that components will survive the thermal mechanical shock loads associated with hostile environments. • Evaluate current stockpile issues, including issues associated with uncertainty quantification. • Address many other problems that are encountered in stockpile management. The Sierra/SD verification plan is described, and an evolving set of key verification tests are described in detail. The verification tests ensure the correctness of the mathematics and numerical algorithms associated with functionality describing engineering phenomena. Development is in accordance with a set of tailored Software Quality Engineering (SQE) practices. SQE practices guide the overall verification and validation effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Status Update for the Bearing Test Article Design Development – FY2025

Argonne National Laboratory’s (ANL) Mechanism Engineering Test Loop (METL) team has completed the design of a new Bearing Test Article (BTA) to test mechanical bearings for sodium fast reactor (SFR) mechanism applications. Recognition of the need for further bearing testing arose due to failure of rolling element bearings during testing of components for in-vessel fuel handling machines (FHMs) conducted at ANL in the METL facility. While the initial concept of the BTA arose from a need for bearing testing for FHM applications, the BTA design is configurable to test bearings of various sizes, types, and materials submerged in liquid sodium. Requirements for loading, shaft speed, temperature, and bearing size range were chosen based on requirements for SFR fuel handling. Modular components in the test bearing housings and shaft sleeves allow the design to accommodate a wide range of bearing sizes without modification to the larger assembly. Loading will be applied with screw jacks on the air side of the test article that will be adjusted to apply radial, thrust, or combined loading conditions. Applied force will be measured by load cells in-line with the loading mechanisms. In FY25 we have completed the design of the test article that will be fabricated and undergo testing at the METL facility. Drawing packages for the fabrication of the test article have been drafted and are being reviewed to add part tolerances and we have started ordering off-the-shelf components. The report will summarize the development of the Bearing Test Article design starting with an overview of the entire test article, then a more detailed examination of the bearing test section, loading mechanisms, test article ports and seals, and support structures, including analysis that went into significant design choices.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Summary of Potential Incidents and Consequences from Carbon Dioxide Pipeline and Storage Systems Construction and Operation

This document provides a high-level summary of the potential human and environmental impacts associated with carbon dioxide (CO 2 ) pipeline transport, injection, and storage activities. It also reviews lessons learned from natural and industrial analogs of CO 2 storage as well as case studies of notable accidental CO 2 releases. The analysis is structured into several key sections, each addressing specific resource impacts and potential consequences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Understanding Peelle’s Pertinent Puzzle bias in generalized least squares regression through eigenspectrum analysis

Certain correlation structures in the data covariance matrix (DCM) used for generalized least squares (GLS) regression can result in biased estimates, commonly known in the field of nuclear data evaluation as Peele’s Pertinent Puzzle (PPP). This article introduces a generative, forward modeling framework within which the PPP bias is characterized through an eigenspectrum analysis of the DCM. This analysis highlights the root cause of the bias, generalizes the problem beyond the nuclear data field, and provides insight to the problem regimes where it can occur. What follows is an understanding that the bias can show up for any experimental neutron time-of-flight data for which systematic uncertainties have been quantified. Lastly, a discussion of the adaptation of cross validation approaches that require pre-whitening to incorporate the known ‘fix’ to the PPP bias in the GLS estimator.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.

Dislocation structures↗
DOE OSTI2025

Comparative Study of Solvatomorphs of Stryker's Reagent Using MicroED and Quantum Mechanics

Abstract The atomic position of hydrogen atoms in metal hydrides has been a long‐standing structural question in inorganic chemistry given that hydride delivery is integral to diverse chemical reactions. Microcrystal electron diffraction (microED), with it's increased sensitivity toward hydrogen atoms relative to X‐ray diffraction, offers a potential path to addressing this challenge. Herein, the first microED study of Stryker's reagent is reported, resulting in the structure of a new benzene solvate. Improved accuracy for hydrogen atom positions was obtained via a quantum crystallography (QCr) approach, Hirshfeld atom refinement (HAR). Structural and topological analysis supports edge bridging hydrides in the microED structure of a THF solvate form, consistent with previous diffraction studies. Interestingly, analysis of a new benzene solvate, discovered in this study, is consistent with mixed edge‐ and face‐bridging hydrides.

Jha, Kunal K. [Division of Chemistry &amp, Chemica↗
DOE OSTI2024

Agrivoltaic Racking Design Optimization Based on Wind and Snow Loading Finite Element Analysis

The racking structure of photovoltaic (PV) systems plays a critical role in ensuring the PV panels generate power properly as it provides integral structural support and sometimes even solar tracking ability. Distinct applications of PV systems require variations of racking structure designs, which yield different mechanical performances under external loading conditions from the environment, such as heavy wind and snow. Past works, such as Reddy et al. [1], have analyzed the pressure effects of wind and snow loading on the racking structure of conventional rooftop and utility PV systems, but there is little knowledge of how various agrivoltaic racking systems perform, in terms of stress and strain, under the same loading conditions. There is also a knowledge gap in the industry on a set of optimized agrivoltaic racking design standards. This study investigates the mechanical performance of various existing racking systems and proposes novel designs that are optimized for agrivoltaics applications under wind and snow loading.

Liao, Quanhuan↗
DOE OSTI2025

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

High-Resolution Tandem Mass Spectrometry-Based Analysis of Model Lignin–Iron Complexes: Novel Pipeline and Complex Structures

Understanding the chemical nature of soil organic carbon (SOC) with great potential to bind iron (Fe) minerals is critical for predicting the stability of SOC. Organic ligands of Fe are among the top candidates for SOCs able to strongly sorb on Fe minerals, but most of them are still molecularly uncharacterized. To shed insights into the chemical nature of organic ligands in soil and their fate, this study developed a protocol for identifying organic ligands using ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and metabolomic tools. The protocol was used for investigating the Fe complexes formed by model compounds of lignin-derived organic ligands, namely, caffeic acid (CA), p-coumaric acid (CMA), vanillin (VNL), and cinnamic acid (CNA). Isotopologue analysis of 54/56 Fe was used to screen out the potential UHPLC-HRMS (m/z) features for complexes formed between organic ligands and Fe, with multiple features captured for CA, CMA, VNL, and CNA when 35/37 Cl isotopologue analysis was used as supplementary evidence for the complexes with Cl. MS/MS spectra, fragment analysis, and structure prediction with SIRIUS were used to annotate the structures of mono/bidentate mono/biligand complexes. The analysis determined the structures of monodentate and bidentate complexes of FeL x Cl y (L: organic ligand, x = 1–4, y = 0–3) formed by model compounds. The protocol developed in this study can be used to identify unknown organic ligands occurring in complex environmental samples and shed light on the molecular-level processes governing the stability of the SOC.

54 ENVIRONMENTAL SCIENCES↗