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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2023

Electrochemical Performance of Mixed Redox-Active Organic Molecules in Redox Flow Batteries

Designing electrolytes based on mixture of different organic redox active molecules brings the opportunity of enhancing the volumetric energy density of flow batteries and removes the requirement of high solubility for individual organic species in the mixture. Here, in the present work, we conduct computational and experimental analysis to investigate the electrochemical performance of mixed redox-active organic molecules. A zero-dimensional transient model is employed to investigate the changes in the half-cell potential and the concentrations and partial currents of individual redox reactions in a mixture of organic molecules over time. The model demonstrates the effects of individual properties of species such as kinetic rate constants, mass transfer coefficients, concentration ratios and standard redox potentials and reports the effect of energy-losing homogenous chemical redox reaction on the voltage efficiency and concentration ratios of the mixed species. Pairs of anthraquinone negolyte species were selected for an experimental case study. A mixture of 2,6-N-TSAQ and 2,6-DHAQ showed 40% increase in the volumetric energy density compared to the performance of 2,6-DHAQ alone. Based on the results of the experimental and computational analysis, we propose guidelines for the design of suitable mixed redox-active organic species.

25 ENERGY STORAGE↗
DOE OSTI2024

Low pH Titanium Electrochemistry in the Presence of Sulfuric Acid and its Implications for Redox Flow Battery Applications

Titanium (Ti) is a promising elemental redox active species for redox flow batteries (RFBs) due to its 100x availability in the Earth crust, and 10x lower cost (compared to elemental vanadium). Furthermore, Ti salts are highly soluble in water and concentrations >5 M can be easily obtained. Seeking to harness the higher solubility (and hence energy density) of the Ti electrolyte for flow battery applications, the Ti 4+ /Ti 3+ redox couple was investigated at high concentrations (up to 5 M) relevant to RFB applications. The behavior of Ti ions in H 2 SO 4 supported electrolytes was investigated by varying the ratio of Ti redox active species to counterion. The electrochemical characteristics, transport properties, and redox kinetics of the Ti 4+ /Ti 3+ redox couple were measured and the impact of the Ti x+ to solvating ligand ratio was examined. The coordination structures around solvated Ti x+ ions were spectroscopically determined and the effect of solvation structure on the Ti 3+ /Ti 4+ redox rate constants were examined and correlated to the calculated solvation energy (hence distinguishing between inner- and outer-sphere processes) and the role of catalysts was addressed. The Ti electrolyte development guidelines presented herein will advance the development of Ti-based RFBs as a promising pathway towards cost effective, grid-scale energy storage.

Electrochemistry↗
DOE OSTI2025

Impact of the LiPF6 Concentration on the Interfacial Charge Transfer and Fast-charging Capabilities of Lithium-Ion Batteries

Fast-charging lithium-ion batteries (LIB) demand optimized electrolyte formulations to balance ionic conductivity, viscosity, and interfacial charge transfer kinetics. This study examines how LiPF 6 concentration shapes solvation structure, desolvation energy, charge transfer activation energy, and solid electrolyte interphase (SEI) properties, which are critical for fast-charging performance. Using Raman spectroscopy, electrochemical cycling, X-ray photoelectron spectroscopy, and atomistic modeling, we analyze how varying LiPF 6 concentrations impact interfacial and bulk transport properties. Our findings show that increasing LiPF 6 concentration alters lithium solvation structures, reduces desolvation energy, and accelerates charge transfer at the electrode interface. Higher concentrations lower the activation energy for charge transfer and suppress excessive SEI growth, improving interfacial kinetics. However, concentrations above a certain threshold increase viscosity and reduce ionic conductivity, limiting transport efficiency. These results offer insights into electrolyte solvation and interfacial charge transfer mechanisms, providing guidelines for designing next-generation fast-charging LIB electrolytes with enhanced efficiency, stability, and longevity.

Son, Seoung-Bum [Argonne National Laboratory (ANL)↗
DOE OSTI2025

Multiscale Modeling Framework for Lithium Nucleation in 3D Porous Carbon Anodes

Porous carbon scaffolds offer a promising route for mitigating non-uniform lithium (Li) plating to enhance the safety and longevity of Li metal batteries. However, the influence of microstructural morphology on Li nucleation is not well understood. Here, we present a multiscale modeling framework to investigate how the porous microstructure of carbon materials affects Li nucleation behavior. Ab initio molecular dynamics simulations quantify the nucleation energy barriers of Li on graphene as a function of Li content, surface curvature, and applied potential, providing key parameters for a classical nucleation theory (CNT) model. From macroscale half-cell simulations, we obtained Li concentration and electrical potential profiles to define boundary conditions for mesoscopic simulations. At the mesoscale, three distinct synthetic 3D microstructures with different porosities and characteristic feature sizes are generated to resolve local distributions of Li flux, current density, and mechanical stress. These outputs are integrated into the CNT model to map spatial variation in nucleation rates. Our findings reveal trade-offs between suppressing nucleation rates and achieving spatial uniformity, offering design guidelines for optimizing porous carbon anodes to balance nucleation control and mechanical integrity.

Materials science↗
DOE OSTI2025

Bubble Transport through a Porous Lattice with an Applied Inlet Flow

Within gas-evolving electrochemical systems, bubbles negatively impact performance by covering electrode active sites for reactions, blocking electric field lines, and obstructing liquid electrolyte flow causing pressure buildup. Recent additive manufacturing advances have enabled tuned porous electrode microstructures to be created, but producing systems that maximize electrochemical throughput and minimize bubble impact remains challenging. Thus, improved physical understanding of and modeling capabilities for bubble behavior are critical to improve electrolyzer design. To address this need, this study examines rising stage bubbles within a lattice with an applied liquid flow—an underexplored regime that strongly influences an electrochemical bubble’s fate. Notably, theoretical predictions and resolved bubble simulations are complemented by experiments from a 3D-printed visualization cell that matches the simulation geometry. The minimum threshold flow rate to achieve bubble breakthrough is found to be larger for higher porosities and for smaller bubbles. Different-sized bubbles decrease expected electrochemical performance in different ways; smaller bubbles tend to stay stuck but cover less solid surface, while larger bubbles more readily break through but cover more surface while in the lattice. The bubble trajectory, deformation, and contact area provide insight into these different behaviors. These findings provide design guidelines toward creating more effective electrolyzers.

Guo, Jack [Lawrence Livermore National Laboratory ↗
DOE OSTI2026

Unraveling Grain Boundary Instability in Dense Proton-Conducting Oxides

The long-term stability of protonic ceramic electrolysis cell (PCEC) materials under high-steam operating conditions remains a critical barrier to device commercialization. Here, we investigate the fundamental degradation mechanisms of dense BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3-δ (BCZYYb) electrolytes operated at 550 °C, 50% H 2 O in air. Over 1,000 h, the total electrolyte conductivity decreases by 11.1%, driven primarily by a >130% increase in grain-boundary resistivity. Post-mortem analyses reveal that damage is localized to near-surface grain boundaries extending ∼50 μm into the dense electrolyte pellet. This surface localization indicates that degradation is likely to be severe in thin, device-level electrolytes. Degradation is primarily attributed to chemo-mechanical grain-boundary weakening arising from hydration-induced chemical expansion, culminating in the formation of intergranular cracks oriented parallel to the pellet surface. These internal cracks subsequently react with steam and/or CO 2 , leading to the formation of nanoscale insulating phases, including Ba(OH) 2 , nanocrystalline BaCO 3 , and amorphous Ce/Zr/Y/Yb-containing oxides or hydroxycarbonates. After an initial degradation period of approximately 200 h, the overall conductivity stabilizes. Incorporating NiO sintering aids reduces grain-boundary density by an order of magnitude under identical sintering conditions. Although addition of NiO increases the initial resistivity by >160% at 550 °C, it substantially suppresses grain-boundary instability and mitigates chemical degradation. These findings underscore the urgent need for chemical and/or physical stabilization of BCZYYb electrolytes and offer design guidelines to enable durable, high-performance PCECs.

08 HYDROGEN↗
DOE OSTI2021

Simulation Dataset - Input files

The input data that are required to run the model are divided into fundamental data and advanced data. The fundamental data are essential to run the model, while the advanced data allow optional model features to be activated. The names of all input data files are to be entered as ASCII characters in a tabular format. Spaces, commas, or tabs can separate numeric fields, the use of any other special visible or hidden characters must be avoided. It may be useful to note that all files are generally read in using standard free-format style FORTRAN READ statements. The input data files can be generated/modified using any standard editor, spreadsheet or word processor (in non-document mode), given that the above guidelines are complied with. However, the inclusion of special formatting characters and the insertion of blank lines must be avoided. The input data files may also be generated through the use of special purpose translation programs that convert the input data files that were initially generated for another traffic simulation or transportation planning model into an INTEGRATION format.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

CheKiPEUQ

Parameter estimation for complex physical problems often suffers from finding 'solutions' that are not physically realistic. The CheKiPEUQ software provides tools for finding physically realistic parameter estimates.and CheKiPEUQ provide tools for making graphs of the parameter positions within parameter space as well as plots of the final simulation results. The primary purpose of the CheKiPEUQ software is to enable more physically realistic parameter estimation from comparing simulations to experiments. Specifically, when prior knowledge is available about the region of parameter space which is physically realistic and when the level of uncertainty from experiment can be estimated. The software is intentionally general and can be used for almost any type of simulation. The software is made in a user friendly manner so that users can simply enter the required data and then run the program, following guidelines provided by the authors along with some trial and error. Examples are provided. Users do not need to understand the methodology that will be namedi in the following sentences. While CheKiPEUQ can be used for conventional parameter estimation and other uses, the primary uses for CheKiPEUQ are: 1) Bayesian Parameter Estimation, 2) Bayesian Model Discrimination, 3) Bayesian Design of Experiments. For more information see the project website, documentation, examples, and related publications.

Savara, Aditya [Oak Ridge National Lab. (ORNL), Oa↗
DOE OSTI2021

AADL: Anderson Accelerated Deep Learning

We propose a stable, distributed approach to perform AA that accelerates the convergence rate of stochastic first-order optimizers to train neural networks. Differently from previous works, we do not alter neither the scheme to perform AA nor the loss function minimized during the training. To improve robustness against stagnation, we customize general guidelines that suggest to relax the frequency of AA corrections by performing AA only at the end of an entire training epoch. To improve robustness of AA against the stochastic oscillations of first-order optimizers, we average the gradients computed on consecutive stochastic optimization updates. The improved regularity of the converging sequence and the reduced amplitude of stochastic oscillations across consecutive optimization steps allows AA to efficiently extrapolate an improved converging sequence, thereby overcoming limitations of existing approaches to perform AA on stochastic optimization.

Lupo Pasini, Massimiliano [Oak Ridge National Lab.↗