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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Precursor selection in hybrid molecular beam epitaxy of alkaline-earth stannates

One of the challenges of oxide molecular beam epitaxy (MBE) is the synthesis of oxides containing metals with high electronegativity (metals that are hard to oxidize). The use of reactive organometallic precursors can potentially address this issue. To investigate the formation of radicals in MBE, we explored three carefully chosen metal-organic precursors of tin for SnO 2 and BaSnO 3 growth: tetramethyltin (TMT), tetraethyltin (TET), and hexamethylditin (HMDT). All three precursors produced single-crystalline, atomically smooth, and epitaxial SnO 2 (101) films on r-Al 2 O 3 (101¯2) in the presence of oxygen plasma. The study of growth kinetics revealed reaction-limited and flux-limited regimes except for TET, which also exhibited a decrease in the deposition rate with increasing temperature above ~800 °C. Contrary to these similarities, the performance of these precursors was dramatically different for BaSnO 3 growth. TMT and TET were ineffective in supplying adequate tin, whereas HMDT yielded phase-pure, stoichiometric BaSnO 3 films. Significantly, HMDT resulted in phase-pure and stoichiometric BaSnO 3 films even without the use of an oxygen plasma (i.e., with molecular oxygen alone). Furthermore, these results are discussed using the ability of HMDT to form tin radicals and therefore assisting with Sn → Sn 4+ oxidation reaction. Structural and electronic transport properties of films grown using HMDT with and without oxygen plasma are compared. This study provides guideline for the choice of precursors that will enable the synthesis of metal oxides containing hard-to-oxidize metals using reactive radicals in MBE.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomic layer deposition of nanofilms on porous polymer substrates: Strategies for success

Atomic layer deposition (ALD) is a versatile technique for engineering the surfaces of porous polymers, imbuing the flexible, high-surface-area substrates with inorganic and hybrid material properties. Previously reported enhancements include fouling resistance, electrical conductance, thermal stability, photocatalytic activity, hydrophilicity, and oleophilicity. However, there are many poorly understood phenomena that introduce challenges in applying ALD to porous polymers. In this paper, we address five common challenges and ways to overcome them: (1) entrapped precursor, (2) embrittlement, (3) film fracture, (4) deformation, and (5) pore collapse. These challenges are often interrelated and can exacerbate one another. To investigate these phenomena, we applied various ALD chemistries to porous polymers including polyethersulfone, polysulfone, polyvinylidene fluoride, and polycarbonate track-etched membranes. Reaction-diffusion modeling revealed why certain precursors and processing conditions result in embrittling subsurface material growth, entrapment of unreacted precursors, and nongrowth. We quantify the limits of ALD processing temperatures that are dictated by thermal expansion mismatch and can lead to fractured ALD films. The results herein allow us to make recommendations to avoid, mitigate, or overcome the difficulties encountered when performing ALD and plasma-enhanced ALD on porous polymers. We intend this article to serve as a “lessons learned” guide informed by previous experience to provide a better understanding of the difficulties and limitations of ALD on porous polymers and knowledge-based guidelines for successful depositions. This knowledge can accelerate future research and help experimentalists navigate and troubleshoot as they expose porous polymers to reactive precursor vapors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Experimental realization of an additively manufactured monatomic lattice for studying wave propagation

Increasing interest in wave propagation in phononic systems and metamaterials motivates the development of experimental designs, measurement techniques, and fabrication methods for use in basic research and classroom demonstrations. The simplest phononic system, the monatomic chain, exhibits rich physics such as dispersion and frequency-domain filtering. However, a limited number of experimental studies showcase monatomic chains for macroscale observation of phonons. Herein, we discuss the design, fabrication, and testing of monatomic lattices as enabled by three-dimensional (3D) printing. Using this widely available technology, we provide design guidelines for realization of a monatomic chain composed of 3D printed serpentine springs and press-fitted cylindrical masses. We also present measurement techniques that record propagating waves and algorithms for the experimental determination of dispersion behavior.

Mork, Nehemiah↗
DOE OSTI2022

Stabilization of garnet/Li interphase by diluting the electronic conductor

The high interfacial resistance and lithium (Li) dendrite growth are two major challenges for solid-state Li batteries (SSLBs). The lack of understanding on the correlations between electronic conductivity and Li dendrite formation limits the success of SSLBs. Here, by diluting the electronic conductor from the interphase to bulk Li during annealing of the aluminium nitride (AlN) interlayer, we changed the interphase from mixed ionic/electronic conductive to solely ionic conductive, and from lithiophilic to lithiophobic to fundamentally understand the correlation among electronic conductivity, Li dendrite, and interfacial resistance. During the conversion-alloy reaction between AlN and Li, the lithiophilic and electronic conductive Li x Al diffused into Li, forming a compact lithiophobic and ionic conductive Li 3 N, which achieved an ultrahigh critical current density of 2.6/14.0 mA/cm 2 in the time/capacity-constant mode, respectively. The fundamental understanding on the effect of interphase nature on interfacial resistance and Li dendrite suppression will provide guidelines for designing high-performance SSLBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Associations between hormone therapy use and tau accumulation in brain regions vulnerable to Alzheimer’s disease

Elucidating the downstream impact of exogenous hormones on the aging brain will have far-reaching consequences for understanding why Alzheimer’s disease (AD) predominates in women almost twofold over men. We tested the extent to which menopausal hormone therapy (HT) use is associated with later-life amyloid-β (Aβ) and tau accumulation using PET onN = 146 baseline clinically normal women, aged 51 to 89 years. Women were scanned over a 4.5-year (SD, 2.1; range, 1.3 to 10.4) and 3.5-year (SD, 1.5; range, 1.2 to 8.1) period for Aβ and tau, respectively, ~14 years after the initiation of HT. In older women (aged >70 years), HT users exhibited faster regional tau accumulation relative to non-users, localized to the entorhinal cortex and the inferior temporal and fusiform gyri, with an indirect effect of HT on cognitive decline through regional tau accumulation. In younger women (aged <70 years), HT associations with tau accumulation were negligible. Findings are relevant for optimizing menopausal treatment guidelines.

Science & Technology - Other Topics↗
DOE OSTI2021

Multiscale Airborne Infectious Disease Transmission

Airborne disease transmission is central to many scientific disciplines, including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated; e.g., the U.S. National Library of Medicine’s Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences, as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation. To inform future work, this paper highlights selected, well-established airborne transmission events, largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations, and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the ability to cause disease in plants, animals, and humans over multiple distances, from near range (<5 m) to continental (>500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burdens for several airborne-transmitted diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Early initiation of prophylactic anticoagulation for prevention of coronavirus disease 2019 mortality in patients admitted to hospital in the United States: cohort study

Early initiation of prophylactic anticoagulation compared with no anticoagulation among patients admitted to hospital with covid-19 was associated with a decreased risk of 30 day mortality and no increased risk of serious bleeding events. These findings provide strong real world evidence to support guidelines recommending the use of prophylactic anticoagulation as initial treatment for patients with covid-19 on hospital admission.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Galerkin Neural Networks: A Framework for Approximating Variational Equations with Error Control

Herein, we present a new approach to using neural networks to approximate the solutions of variational equations, based on the adaptive construction of a sequence of finite-dimensional sub-spaces whose basis functions are realizations of a sequence of neural networks. Here, the finite-dimensional subspaces are then used to define a standard Galerkin approximation of the variational equation. This approach enjoys a number of advantages, including: the sequential nature of the algorithm offers a systematic approach to enhancing the accuracy of a given approximation; the sequential enhancements provide a useful indicator for the error that can be used as a criterion for terminating the sequential updates; the basic approach is largely oblivious to the nature of the partial differential equation under consideration; and, some basic theoretical results are presented regarding the convergence (or otherwise) of the method which are used to formulate basic guidelines for applying the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bias-Variance Trade-Off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs

Physics-Informed Neural Networks (PINNs) have triggered a paradigm shift in scientific computing, leveraging mesh-free properties and robust approximation capabilities. While proving effective for low-dimensional partial differential equations (PDEs), the computational cost of PINNs remains a hurdle in high-dimensional scenarios. This is particularly pronounced when computing high-order and high-dimensional derivatives in the physics-informed loss. Randomized Smoothing PINN (RS-PINN) introduces Gaussian noise for stochastic smoothing of the original neural net model, enabling the use of Monte Carlo methods for derivative approximation, which eliminates the need for costly automatic differentiation. Despite its computational efficiency, especially in the approximation of high-dimensional derivatives, RS-PINN introduces biases in both loss and gradients, negatively impacting convergence, especially when coupled with stochastic gradient descent (SGD) algorithms. We present a comprehensive analysis of biases in RS-PINN, attributing them to the nonlinearity of the Mean Squared Error (MSE) loss as well as the intrinsic nonlinearity of the PDE itself. We propose tailored bias correction techniques, delineating their application based on the order of PDE nonlinearity. The derivation of an unbiased RS-PINN allows for a detailed examination of its advantages and disadvantages compared to the biased version. Specifically, the biased version has a lower variance and runs faster than the unbiased version, but it is less accurate due to the bias. To optimize the bias-variance trade-off, we combine the two approaches in a hybrid method that balances the rapid convergence of the biased version with the high accuracy of the unbiased version. In addition to methodological contributions, we present an enhanced implementation of RS-PINN. Extensive experiments on diverse high-dimensional PDEs, including Fokker-Planck, Hamilton-Jacobi-Bellman (HJB), viscous Burgers’, Allen-Cahn, and Sine-Gordon equations, illustrate the bias-variance trade-off and highlight the effectiveness of the hybrid RS-PINN. Empirical guidelines are provided for selecting biased, unbiased, or hybrid versions, depending on the dimensionality and nonlinearity of the specific PDE problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

t -channel dark matter models – a whitepaper

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t -channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t -channel dark matter models at colliders and in cosmology.

Arina, Chiara [Universite Catholique de Louvain, L↗
DOE OSTI2021

Accelerated Assessment of Critical Infrastructure in Aiding Recovery Efforts During Natural and Human-made Disaster

Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as "Acute Phase" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.

Thakur, Gautam Malviya↗
DOE OSTI2025

FAIR Ecosystems for Science at Scale

High Performance Computing (HPC) centers provide resources to users who require greater scale to “get science done”. They deploy infrastructure with singular hardware architectures, cutting-edge software environments, and stricter security measures as compared with users’ own resources. As a result, users often create and configure digital artifacts in ways that are specialized for the unique infrastructure at a given HPC center. Each user of that center will face similar challenges as they develop specialized solutions to take full advantages of the center’s resources, potentially resulting in significant duplication of effort. Much duplicated effort could be avoided, however, if users of these centers found it easier to discover others’ solutions and artifacts as well as share their own. The FAIR principles address this problem by presenting guidelines focused around metadata practices to be implemented by vaguely defined “communities”; in practice, these tend to gather by domain (e.g. bioinformatics, geosciences, agriculture). Domain-based communities can unfortunately end up functioning as silos that tend both to inhibit sharing of solutions and best practices as well as to encourage fragile and unsustainable improvised solutions in the absence of best-practice guidance. We propose that these communities pursuing “science at scale” be nurtured both individually and collectively by HPC centers so that users can take advantage of shared challenges across disciplines and potentially across HPC centers. We describe an architecture based on the EOSC-Life FAIR Workflows Collaboratory, specialized for use with and inside HPC centers such as the Oak Ridge Leadership Computing Facility (OLCF), and we speculate on user incentives to encourage adoption. We note that a focus on FAIR workflow components rather than FAIR workflows is more likely to benefit the users of HPC centers.

Wilkinson, Sean [ORNL] (ORCID:0000000214437479)↗
DOE OSTI2025

Characterizing the Impact of GPU Power Management on an Exascale System

As GPU-accelerated high-performance computing (HPC) systems approach exascale performance, controlling energy consumption without compromising throughput is essential. Architectures such as the AMD MI250X-based Frontier supercomputer provide runtime mechanisms like frequency and power capping, enabling energy tuning without modifying application code. Although both target energy reduction, they operate via distinct hardware control paths and influence workloads differently. We present a comprehensive evaluation of these strategies on a leadership-class system using diverse HPC proxy applications representative of production workloads. Our study analyzes performance–energy trade-offs across multiple capping levels, node counts (1 and 32), and application profiles. Results show that frequency capping generally achieves higher energy efficiency and scalability, with gains of up to 13.2% without performance loss, while power capping is more effective for single-node runs or bursty GPU utilization. We also provide practical guidelines to help system administrators and users balance energy efficiency and performance in large-scale scientific workloads.

Costa, Mariana [Universidade Federal do Rio Grande↗
DOE OSTI2023

Engineered Wood: Sustainable Technologies and Applications

Natural wood has been used for construction, fuel, and furniture for thousands of years because of its versatility, renewability, and aesthetic appeal. However, new opportunities for wood are arising as researchers have developed ways to tune the material's optical, thermal, mechanical, and ionic transport properties by chemically and physically modifying wood's naturally porous structure and chemical composition. Such modifications can be used to produce sustainable, functional materials for various emerging applications such as automobiles, construction, energy storage, and environmental remediation. In this review, we highlight recent advancements in engineered wood for sustainable technologies, including thermal and light management, environmental remediation, nanofluidics, batteries, and structural materials with high strength-to-weight ratios. Additionally, the current challenges, opportunities, and future of wood research are discussed, providing a guideline for the further development of next-generation, sustainable wood-based materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-Pressure Electrides: A Quantum Chemical Perspective

It has long been assumed that all matter will adopt simple close-packed lattices and become metallic under pressure, in accordance with the Thomas–Fermi–Dirac (TFD) model. However, this model struggles to explain pressure-driven complex structural transitions that have been observed in elements, including sodium, challenging our conventional understanding of compressed matter. Moreover, in stark contrast to the TFD model, first-principles calculations suggest that various elements and compounds become electrides under pressure. Electrides, characterized by concentrations of charge density at interstitial regions, can be thought of as ionic compounds where electrons behave as the anions. Though ambient-pressure molecular electrides have been extensively studied via experiments and computations, high-pressure electrides (HPEs) are not well-understood. The identification and characterization of HPEs have been, to date, based purely on theory, including topological analysis of the electron density and the electron localization function. Here, we review these theoretical analysis tools and suggest guidelines that can be used to classify systems as electrides. Moreover, we describe models used to rationalize the electronic structure of HPEs, drawing parallels with ambient-pressure molecular systems, and encourage the development of experimental techniques that provide evidence for the theoretically calculated charge localization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Oxygen Evolution on Iron Oxide Nanoparticles: The Impact of Crystallinity and Size on the Overpotential

The oxygen evolution reaction (OER) is a critical reaction in electrolysis and photoelectrolysis of water to generate and store clean energy. Therefore, the development of low-cost and efficient electrocatalysts for the OER is of great scientific and technological importance. Although promising iron oxide-based electrocatalysts have been recently developed for the OER, an in-depth experimental and theoretical analysis of the OER mechanism on iron oxide-based electrocatalysts is still needed to provide guidelines to optimize the performance of iron oxide-based electrocatalysts further. To address this need, we synthesized a series of monodisperse iron oxide nanoparticles to analyze their intrinsic OER activities. Using nanoparticles of the same size but different crystallinity, we show that amorphous iron oxide nanoparticles have better OER activity than crystalline ones. The size effect studies further revealed that the edge/defect sites are the active sites for the OER. Density functional theory calculations demonstrated that the edge/defect sites provide bridge sites to adsorb OER intermediates, resulting in low OER overpotential. These calculations confirm that the high OER activity of amorphous nanoparticles results from a high concentration of defect sites on their surface. These results provide novel strategies to increase the performance of iron oxide-based and likely other oxide-based OER electrocatalysts.

Electrochemistry↗
DOE OSTI2023

Predictive Modeling of Electrodeposition in a Single Pore Flow-Through Electrode: From Electronucleation to Coating Thickness Uniformity

The emergence of advanced manufacturing methods capable of producing porous three-dimensional structures has expanded the design space for next-generation functional components. The ability to fabricate ordered 3D foams for use in electrocatalysis reactors has increased the need for controlled deposition of catalytic metals onto porous support materials, such as carbon. However, there is a lack of clear design guidelines for electrodeposition onto 3D substrates, due to the geometric complexity and multi-scale nature of the problem. Furthermore, electro-nucleation phenomena are often overlooked in macro-scale models of current distribution during deposition. Here, a graphite flow-through electrode (FTE) is used as a model system for copper deposition within a single pore. Potential distributions and electro-nucleation phenomena are coupled in a continuum level model by incorporating nucleation size and density as a function of overpotential, determined experimentally using in situ atomic force microscopy (AFM). The model predictions are validated by measuring the coating uniformity in the pore using micro-computed X-ray tomography (μCT). A scaling analysis comprising dimensionless parameters such as the Wagner number is presented. The simplified scaling relationship framework can guide the electrodeposition process and electrode design to optimize plating of porous substrates under fluid flow conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

On Relative Importance of Vehicular and Structural Motions in Defining Electrolyte Transport

Molecular motions of ionic and neutral electrolyte species determine transport properties at the continuum scale. These molecular motions can be classified as vehicular (e.g., cations moving with a solvation shell of neighboring solvent molecules) and structural (e.g., cations hopping from one solvation shell to another) motions. While literature studies have described the presence, and relative importance, of each of these motions in various electrolytes, a clear link to macroscopic transport properties has not been made. We herein establish this link by using the fluctuation-dissipation theorem to develop theoretical expressions connecting the molecular displacements to Stefan-Maxwell diffusivities. To illustrate the usefulness of the proposed equations, we study LiPF 6 in propylene carbonate as an exemplar electrolyte. We show that its transport behavior improves at all concentrations when structural diffusion of cations is promoted. On the other hand, boosting the cation vehicular diffusion negatively affects the concentrated compositions. We extend this understanding to a generalized electrolyte of a salt dissolved in a solvent. Our theory suggests that while structural diffusion influences Stefan-Maxwell diffusivities globally, vehicular diffusion is only relevant under certain conditions. Such guidelines are critical for a bottom-up design of electrolyte transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗