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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 235 records · Page 13

Efficiency analysis of helium-cooled MAS DNP: case studies of surface-modified nanoparticles and homogeneous small-molecule solutions

Despite the growing number of successful applications of dynamic nuclear polarization (DNP)-enhanced magic-angle spinning (MAS) NMR in structural biology and materials science, the nuclear polarizations achieved by current MAS DNP instrumentation are still considerably lower than the theoretical maximum. Here, the method could be significantly strengthened if experiments were performed at temperatures much lower than those currently widely used (~100 K). Recently, the prospects of helium (He)-cooled MAS DNP have been increased with the instrumental developments in MAS technology that uses cold helium gas for sample cooling. Despite the additional gains in sensitivity that have been observed with He-cooled MAS DNP, the performance of the technique has not been evaluated in the case of surfaces and interfaces that benefit the most from DNP. Herein, we studied the efficiency of DNP at temperatures between ~30 K and ~100 K for organically functionalized silica material and a homogeneous solution of small organic molecules at a magnetic field B 0 = 16.4 T. We recorded the changes in signal enhancement, paramagnet-induced quenching and depolarization effects, DNP build-up rate, and Boltzmann polarization. For these samples, the increases in MAS-induced depolarization and DNP build-up times at around 30 K were not as severe as anticipated. In the case of the surface species, we determined that MAS DNP at 30 K provided ~10 times higher sensitivity than MAS DNP at 90 K, which corresponds to the acceleration of experiments by multiplicative factors of up to 100.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of position-dependent cavity parameters in irradiated metals to obtain insight on fundamental defect migration phenomena

Motion of point defects is a fundamental process that governs microstructure and properties of materials. Here, we examine the near-surface and grain boundary cavity swelling depth profiles in neutron- and ion-irradiated simple metals (Cu, Ni, and Fe-Cr) and investigate diffusional broadening of implanted Ni ions in Fe-Cr alloys. Vacancy migration energies and radiation-enhanced diffusion were experimentally estimated. Cavity denuded zone widths near planar sinks are shown to be dependent on temperature, damage rate, balance of point defects and sinks, and vacancy migration energies. An enhanced cavity swelling zone adjacent to the void-denuded zone was observed in specimens with low to moderate sink strength and interpreted as evidence of 1D gliding interstitial clusters. Radiation-enhanced diffusional broadening of implanted Ni ions (at 400–550 °C) in Fe and Fe-Cr was up to 250 nm toward the surface, which leads to a much broader near-peak-damage region where cavity swelling is suppressed. Diffusional broadening of implanted ions is calculated to be similarly pronounced for self-ion irradiations, particularly near the peak and higher swelling temperature regimes. Adequately high ion energies (~8–15 MeV) are recommended for ion-irradiation studies to provide a sufficiently broad midrange safe analysis region with minimized surface and injected ion effects.

36 MATERIALS SCIENCE↗

Updating the Building Science Advisor (BSA): A Tool to Assist in the Design of Durable Building Envelopes

Predicting the moisture durability of building envelope components remains challenging due to multiple influencing factors, including material selection, assembly positioning, local climate conditions, air tightness, interior environment, and construction quality. Building codes increasingly emphasize energy efficiency through enhanced insulation and tighter envelopes but offer limited guidance on moisture durability considerations. Consequently, builders face uncertainty, particularly as new materials and assemblies enter the market.The Building Science Advisor (BSA) is a free, web-based expert system developed to address these challenges by providing actionable insights into the moisture durability and energy efficiency of both new and retrofit wall designs. Recently updated, we are now providing version 3.0 of the tool. BSA features significant user interface improvements, enhancing navigation and user interaction through a refreshed, intuitive design. Additionally, the tool incorporates a newly developed database containing pre-simulated wall assembly cases, significantly reducing response times and improving the accuracy of moisture durability assessments. Furthermore, the updated BSA includes moisture content as a performance criterion, providing users with a more comprehensive understanding of moisture-related durability risks. These enhancements enable rapid, reliable assessments tailored to specific climate zones and local building practices. BSA continues to offer targeted guidance on wall retrofit scenarios and delivers access to an expanded library of location-specific building science resources.This paper describes these key updates, highlighting the enhanced features, expanded capabilities, and overall improvements to user experience and educational content. The paper includes a demonstration that illustrates how the revised BSA effectively supports practitioners in designing durable, energy-efficient building envelope assemblies.

Salonvaara, Mikael [ORNL] (ORCID:0000000318991554)↗

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗

Regional Geology Capstone Report for the Midwestern Regional Carbon Sequestration Partnership (Volume V)

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The MRCSP regional geology Capstone report summarizes the regional characterization of geologic storage subtasks performed under MRCSP Phase III. The regional characterization work was completed by the state geological surveys of Delaware, Indiana, Kentucky, Maryland, New York, Ohio, Pennsylvania, and West Virginia along with Western Michigan University and Rutgers University. Building on the Phases I and II, the Phase III research was focused on key research topics identified in previous MRCSP efforts: [1] Regional Geologic Cross Sections for Potential Storage and Containment Zones; [2] Appalachian Basin: Enhanced Recovery Opportunities; [3] Michigan Basin: Assessment of Enhanced Oil Recovery Using Carbon Dioxide in Silurian Pinnacle Reefs; [4] Mid-Atlantic Coastal Plain and Adjacent Offshore Region: Characterization of Carbon Storage Targets; [5] Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates; [6] Upper Silurian to Middle Devonian Strata of Ohio: Structural Characterization of Potential CO 2 Reservoirs and Adjacent Strata; [7] Triassic Rift Basins: Preliminary Study of Long-Term CO 2 Storage Potential Together, the regional characterization effort developed useful products to support project developers, policy makers and other stakeholders in the MRCSP region seeking to understand where potential storage exists relative to large stationary sources of CO 2 emissions.

01 COAL, LIGNITE, AND PEAT↗

Flow Enhanced Electrochemical Sensor Performance in Complex Salt Systems

To advance MSR MC&A practices, Argonne National Laboratory developed and optimized robust flow enhanced electrochemical sensors (FEES) and multielectrode array voltammetry sensors (MAVS) which provide accurate near-real time measurements of actinides in molten salts. Flow-enhanced electrochemical sensors are installed directly into MSR flow conduits for inline salt chemistry measurement, while MAVS are deployed in quiescent salt conditions enabling online species concentration determination in stationary salt vessels. This report summarizes efforts to improve electrochemical sensor technological readiness through (1) sensor testing in complex, high concentration molten salt systems to demonstrate low uncertainty actinide measurements in MSR-representative solutions and (2) demonstrations of sensor performance in challenging real-world conditions in collaboration with partner MSR institutions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CSGL: chemical synthesis graph learning for molecule representation

Abstract Motivation Molecule representation learning (MRL) translates molecules into a real vector space, serving as input to downstream tasks in biology, chemistry, and computer science. This article introduces a chemical synthesis graph learning (CSGL) framework, which enhances MRL by considering both the atomic structures of molecules and their roles in chemical reactions through a hierarchical graph representation. Specifically, molecules are first modeled based on their molecular graphs, which capture atomic-level structural information. They are then further refined using a chemical synthesis graph, where nodes represent reactant and product molecule sets, and edges encode chemical transformations between reactants and products (e.g. changes in molecular structures). CSGL optimizes molecular embeddings of reactant and product nodes in a fashion that ensures the embeddings conform to a chemical balance constraint. Results Experimental results show that our method CSGL achieves strong performance on a variety of tasks, including product prediction, reaction classification, and molecular property prediction. Availability and implementation https://github.com/li-2023/CSGL.

Biochemistry & Molecular Biology↗

Electrical property enhancement of non-heat-treatable wrought aluminum alloys using graphene additives

With growing efforts of electrification, aluminum’s role as a light-weight conductor material has become increasingly prominent. There is a critical need to improve the electrical performance of aluminum at room temperature and high operating temperatures. In this study, the effect of graphene nanoparticle additives on the electrical performance of a non-heat treatable alloy were (AA3003) explored. Graphene’s unusual structure and electronic properties were used to improve AA3003 properties. Here, in this work, the effects of graphene on the evolution of electrical properties and microstructural features have been explored on lab scale hot extruded AA3003-graphene composites. Hot pressing schedules and extrusion temperatures were varied to investigate changes in intermetallic dispersion characteristics in the presence of dispersed graphene. We measured a reduction of 10.3 % in the temperature coefficient of resistance in the AA3003 sample with 0.05 wt% graphene extruded at 400 °C, along with a maximum increase of 1.1 % in electrical conductivity at 20 °C. Increasing the hot-pressing times up to 8 hours was also found to consistently increase the electrical conductivity, due to increased precipitation of intermetallic phases. Despite being a non-heat treatable alloy, AA3003 displays interesting precipitation dynamics and grain recrystallization trends that can be modulated with varying levels of heat treatment, graphene concentrations, and hot extrusion process parameters.

36 MATERIALS SCIENCE↗

Enhanced Oxygen Reduction Performance on {101} CoMn 2 O 4 Spinel Facets

Here, we present a facile colloidal synthesis method for producing {101}-facet-tailored CoMn 2 O 4 spinel nano-octahedra with uniform size (9 nm). These nano-octahedra exhibit superior electrocatalytic activity for the oxygen reduction reaction (ORR) in alkaline media compared to their spherical counterparts and previously reported spinel electrocatalysts. At 0.85 V, they achieve a high mass activity (MA) of 60.0 A/g, surpassing the spherical counterparts (38.6 A/g). Furthermore, the CoMn 2 O 4 nano-octahedra demonstrate excellent stability, maintaining an MA of 47.2 A/g after 10,000 durability cycles. This work highlights a promising approach for synthesizing advanced spinel nano-oxides with controlled crystal facets, offering potential as non-precious metal ORR electrocatalysts. The exposed active catalyst surfaces and well-defined structures contribute to their enhanced ORR performance.

36 MATERIALS SCIENCE↗

Demonstration of Non-linear Optical Spectroscopy Enhancement utilizing Entangled Photons

Laser-based nonlinear optical spectroscopy approaches have enabled the direct sensing of important chemistry in nearly every fundamental or applied field of science. Yet in many applications, increased detectivity is needed to unravel fundamental mechanisms. One possibility is the use of quantum entanglement to increase detection cross-sections, but it is unproven that enhancement from quantum light extends to practical intensities for chemical sensing. In this report, we investigated the creation and use of entangled photons in nonlinear optical mixing for second harmonic generation and infrared imaging. We observe that the linear scaling of nonlinear mixing from entangled photon sources extends to the mW laser power regime, and enhances direct infrared imaging on Si-based charge coupled device cameras. These results motivate future experimentation on practical uses of entangled photons for nonlinear optical sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of ancestral gnathostome Gli3 enhancers with activity in mammals

Abnormal expression of the transcriptional regulator and hedgehog (Hh) signaling pathway effector Gli3 is known to trigger congenital disease, most frequently affecting the central nervous system (CNS) and the limbs. Accurate delineation of the genomic cis-regulatory landscape controlling Gli3 transcription during embryonic development is critical for the interpretation of noncoding variants associated with congenital defects. Here, we employed a comparative genomic analysis on fish species with a slow rate of molecular evolution to identify seven previously unknown conserved noncoding elements (CNEs) in Gli3 intronic intervals (CNE15–21). Transgenic assays in zebrafish revealed that most of these elements drive activities in Gli3 expressing tissues, predominantly the fins, CNS, and the heart. Intersection of these CNEs with human disease associated SNPs identified CNE15 as a putative mammalian craniofacial enhancer, with conserved activity in vertebrates and potentially affected by mutation associated with human craniofacial morphology. Finally, comparative functional dissection of an appendage-specific CNE conserved in slowly evolving fish (elephant shark), but not in teleost (CNE14/hs1586) indicates co-option of limb specificity from other tissues prior to the divergence of amniotes and lobe-finned fish. In conclusion, these results uncover a novel subset of intronic Gli3 enhancers that arose in the common ancestor of gnathostomes and whose sequence components were likely gradually modified in other species during the process of evolutionary diversification.

59 BASIC BIOLOGICAL SCIENCES↗

Science and Solutions for a Planet Under Pressure: Synthetic Research, Analytics, and Community Engagement on Five Priority Theme Areas

Support from the Department of Energy proved instrumental in supporting the work of Global Council for Science and the Environment (GCSE) on synthetic research, analysis, and community engagement, oriented around the themes and discussions from the GCSE Drawdown 2021 Conference — Research to Action: Science and Solutions for a Planet Under Pressure. These efforts helped inform and enhance the societal relevance of the knowledge that has been generated through the conference and, at the same time, advance the scientific insights acquired through synthesis and scientific translation efforts. The work centered on three main objectives: 1) documentation of findings from the completed GCSE 2021, culminating in the publication of a synthesis report; 2) development and vetting of integrated use cases that illustrate synthesis methods and enable scientific outreach, communications, and translational discussions among universities and the broader research community; and 3) strengthening the scientific basis for energy education research by sharing findings in university-educator fora.

54 ENVIRONMENTAL SCIENCES↗

New Dimensions in the Theory of Excited States and X-ray Spectra (Final Report)

This Final Technical Report briefly summarizes the achievements during the lifetime of our DOE BES grant DE-FG02-97ER45623. The long-term goal of this project has been the development of quantitative theories of the interaction between radiation and matter, with a focus on x-ray spectroscopies. X-ray spectra have long been among the most important probes of atomic-scale structure and properties of matter, ranging from atoms and molecular systems to condensed matter and exotic states. These spectroscopies are widely used in investigations at the major DOE synchrotron x-ray facilities and related centers world-wide. In addition to fundamental theory, a major goal of our project has been the development of computational software that implements the theory for calculations of x-ray spectra of various materials throughout the periodic table. Due to the complex nature of x-ray spectra, quantitative theory is essential for its interpretation. The theory is challenging since it involves excited state electronic structure and many-body correlation effects that go beyond independent particle approximations like DFT or Hartree-Fock. Moreover, the experimental investigations typically involve a broad range of energy, time, and temperature scales, from the UV-Vis to hard x-ray energies of order 10 4 eV, and temperatures T from ambient up to the warm-dense-matter regime where the Fermi energy kBTF is of order a few eV, i.e., temperatures of order 105 Kelvin. This broad range of experimental conditions has fostered many novel theoretical approaches and computational techniques, many of which we have developed systematically over the duration of the grant. In contrast to the traditional wave-function approach of quantum theory and electronic structure methods, our theoretical approach is based on modern Green's function techniques. This approach is better suited for aperiodic structures, excited states, and broad spectral ranges, since it avoids the computational bottlenecks of sum-over-states approaches, as in the Fermi golden rule. This theoretical framework has been incorporated into efficient, user-friendly x-ray spectroscopy software which is now used routinely worldwide to simulate and analyze spectra. These theoretical tools provide an essential complement to synchrotron and next-generation light sources, which are used to investigate complex materials with ever increasing precision. Moreover, the synergism between theory, computation and experiment contributed by our research enhances scientific understanding and creates opportunities for innovations in materials and energy science and in many fields. As documented in this Report, this research grant has been remarkably successful in achieving these goals. In particular, this grant has supported the development of the x-ray spectroscopy software suite known as FEFF (named for an effective scattering amplitude f eff in the theory). The FEFF codes have become one of the premier tools for quantitative simulations of x-ray spectra as documented by many thousands of citations in the Web of Science and Google-Scholar.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Temperature dependent index of refraction compensation and radiation resistance in monolithic optical systems

Monolithic catadioptric optical systems are susceptible to defocus errors caused by inhomogeneous temperature within the glass material due to temperature dependent index of refraction. This invention discloses methods to mitigate these errors using tuned materials in its optical design coupled with active optical radiative heating to provide optimal performance and includes methods to enhance radiation resistance.

36 MATERIALS SCIENCE↗

Scaling Containment on a Large Centrifuge

Containment science concerns the trapping or leakage of radioactive cavity gases from underground nuclear explosions (UNEs). The most physically relevant data for validation of containment science comes from legacy UNE testing or large field-scale chemical explosions. Field-scale tests can inform on the degree of residual stress imparted to host geology and possible formation of an accompanying gas-containing “stress cage”, for example, as a function of chemical explosion yield. However, field testing can be expensive, difficult to conduct, and challenging to instrument with limitations on data coverage (i.e., the number of boreholes; difficult coring through damage zones). Small-scale laboratory tests are typically simpler to conduct and more thoroughly characterize, but may not include the right scale of containment processes for stress-cage or chimney formation. This report presents the theory and fundamentals of large centrifuge physical modeling, including a history of explosive or similar testing relevant to containment science investigations on centrifuges. Subscale models with embedded chemical explosives in the enhanced gravity of a large centrifuge can represent hundreds of meters of depth and large explosions not otherwise attainable in the laboratory as based on scaling of length, energy, and other processes by the g-factor of the centrifuge (i.e., the number of times larger the centrifugal force is than the gravitational force on the Earth’s surface). The centrifuge uniquely joins the simplicity and exhaustiveness of laboratory-scale characterization with the physics of field-scale processes. This report is part of Sandia National Laboratories’ (SNL’s) effort to prepare for physical modeling with approximately one-meter tall geologic models of stress cage and/or chimney formation on its 29-foot [8.84 m] radius centrifuge with a load capacity of 1.6 million 𝑔-pounds [726 𝑔-ton]. The scaling relationships herein will inform model design decisions and performance requirements for in-flight sensors.

42 ENGINEERING↗

Mechanism of Peptide Agonist Binding in CXCR4 Chemokine Receptor

Chemokine receptors are key G-protein-coupled receptors (GPCRs) that control cell migration in immune system responses, development of cardiovascular and central nervous systems, and numerous diseases. In particular, the CXCR4 chemokine receptor promotes metastasis, tumor growth and angiogenesis in cancers. CXCR4 is also used as one of the two co-receptors for T-tropic HIV-1 entry into host cells. Therefore, CXCR4 serves as an important therapeutic target for treating cancers and HIV infection. Apart from the CXCL12 endogenous peptide agonist, previous studies suggested that the first 17 amino acids of CXCL12 are sufficient to activate CXCR4. Two 17-residue peptides with positions 1–4 mutated to RSVM and ASLW functioned as super and partial agonists of CXCR4, respectively. However, the mechanism of peptide agonist binding in CXCR4 remains unclear. Here, we have investigated this mechanism through all-atom simulations using a novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method. The Pep-GaMD simulations have allowed us to explore representative binding conformations of each peptide and identify critical low-energy states of CXCR4 activated by the super versus partial peptide agonists. Our simulations have provided important mechanistic insights into peptide agonist binding in CXCR4, which are expected to facilitate rational design of new peptide modulators of CXCR4 and other chemokine receptors.

59 BASIC BIOLOGICAL SCIENCES↗