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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo↗
DOE OSTI2025

Hybrid renewable energy systems

In the pursuit of ecologically sustainable and resilient energy systems, increasingly more attention is being devoted to a diversity of energy generation and storage methods. As the landscape of generation technology gains nuance and complexity, a wide-ranging set of technical questions has emerged, touching on topics that range from control and optimization of hybrid systems to finance and economic viability to multi-fidelity modeling and scientific machine learning. In the context of this special issue, hybrid renewable energy systems are any systems that consider the combined dynamics of more than one form of generation, storage, or grid subsystem. Research endeavors have delved into improving the flexibility of energy systems by utilizing existing resources, introducing novel operational strategies, deploying enhanced renewable forecasts, and exploring emerging technologies. In conclusion, the interconnection among various sectors has garnered heightened attention, not only due to the provision of additional tradable energy products but also for furnishing flexible headroom to system operators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Evaluations for medium- and high-mass nuclei for FUSION applications

There is a renewed attention to nuclear fusion as a commercial source of carbon-free energy, however there are many scientific needs that must be addressed to enable the future success of fusion as an economical energy option. Among these is the proper description of the impact of radiation produced in the fusion vessel chamber and all other components of the reactor. In this work we will focus on the nuclear data needs to describe the interaction between primary and secondary neutron radiation and the medium- and high-mass nuclei commonly present in structural (such as stainless steel) and superconducting (e.g., electromagnets) materials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Laser scattering by submicron droplets formed during the electrical explosion of thin metal wires

Abstract This paper presents the results of studying dispersed media formation during the electrical explosion of thin metal wires in vacuum by using low-current generators (~1–10 kA). Particular attention is paid to the analysis of the composition and structure of the corresponding explosion products as well as to the problem of their visualization using simultaneous laser interferometry and shadow imaging at two wavelengths (1.064 µ m and 0.532 µ m). Our findings indicate the important role in the visualization of the explosion products that belongs to multiple scattering by submicron droplets of dense condensed matter, which are mixed with metal vapor. The hypothesis on the existence of submicron droplets in the products of exploding metal wires correlates with the results obtained by soft x-ray radiography combined with a laser probing technique. Taking into account the multiple scattering by submicron droplets, it is possible to significantly clarify the parameters of the explosion products visualized via laser probing techniques as well as to gain a deeper insight into the physics behind the electrical wire explosion.

Physics↗
DOE OSTI2021

Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation

Abstract Bacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor.

Wong, Gerard C. L. (ORCID:0000000308936383)↗
DOE OSTI2022

Negative hydrogen ion sources for particle accelerators: Sustainability issues and recent improvements in long-term operations

High brightness, negative hydrogen ion sources are used extensively in scientific facilities operating worldwide. Negative hydrogen beams have become the preferred means of filling circular accelerators and storage rings as well as enabling efficient extraction from cyclotrons. Several well-known facilities now have considerable experience with operating a variety of sources such as RF-, filament-, magnetron- and Penning-type H- ion sources. These facilities include the US Spallation Neutron Source (SNS), Japan Proton Accelerator Research Complex (J-PARC), Rutherford Appleton Laboratory (RAL-ISIS), Los Alamos Neutron Science Center (LANSCE), Fermi National Accelerator Laboratory (FNAL), Brookhaven National Laboratory (BNL), numerous installations of D-Pace (licenced by TRIUMF) ion sources used mainly on cyclotrons and, most recently, the CERN-LINAC-1 injector. This report first summarizes the current performance of these ion sources in routine, daily operations with attention toward source service-periods and availability metrics. Sustainability issues encountered at each facility are also reported and categorized to identify areas of common concern and key issues. Recent ion source improvements to address these issues are also discussed as well as plans for meeting future facility upgrade requirements.

Welton, Robert F.↗
DOE OSTI2026

Unsupervised atomic data mining via multi-kernel graph autoencoders for machine learning force fields

Constructing a chemically diverse dataset while avoiding sampling bias is critical to training efficient and generalizable force fields. However, in computational chemistry and materials science, many common dataset generation techniques are prone to oversampling regions of the potential energy surface. Furthermore, these regions can be difficult to identify and isolate from each other or may not align well with human intuition, making it challenging to systematically remove bias in the dataset. While traditional clustering and pruning (down-sampling) approaches can be useful for this, they can often lead to information loss or a failure to properly identify distinct regions of the potential energy surface due to difficulties associated with the high dimensionality of atomic descriptors. In this work, we introduce the Multi-kernel Edge Attention-based Graph Autoencoder (MEAGraph) model, an unsupervised approach for analyzing atomic datasets. MEAGraph combines multiple linear kernel transformations with attention-based message passing to capture geometric sensitivity and enable effective dataset pruning without relying on labels or extensive training. Demonstrated applications on niobium, tantalum, and iron datasets show that MEAGraph efficiently groups similar atomic environments, allowing for the use of basic pruning techniques for removing sampling bias. This approach provides an effective method for representation learning and clustering that can be used for data analysis, outlier detection, and dataset optimization.

Materials science↗
DOE OSTI2021

Long-term variability of root production in bioenergy crops from ingrowth core measurements

Long-term determination of root biomass production upon land-use conversion to biofuel crops is rare. To assess land-use legacy influences on belowground biomass accumulation, we converted 22-year-old Conservation Reserve Program (CRP) grasslands and 50+-year-old agricultural (AGR) lands to corn (C), switchgrass (Sw) and restored prairie (Pr) biofuel crops. We maintained one CRP grassland as a reference (Ref). We hypothesized that land-use history and crop type have significant effects on root density, with perennial crops on CRP grasslands having a higher root biomass productivity, while corn grown on former agricultural lands produce the lowest root biomass. Methods The ingrowth core method was used to determine in situ ingrowth root biomass, alongside measurements of aboveground net primary productivity (ANPP). Ancillary measurements, including air temperature, growing season length and precipitation were used to examine their influences on root biomass production. Important Findings Root biomass productivity was the highest in unconverted CRP grassland (1716 g m-2 yr-1) and lowest in corn fields (526 g m-2 yr-1). All perennial sites converted from CRP and AGR lands had lower root biomass and ANPP in the first year of planting but peaked in 2011 for switchgrass and a year later for restored prairies. Ecosystem stability was higher in restored prairies (AGR-Pr: 4.3 ± 0.11; CRP-Pr: 4.1 ± 0.10), with all monocultures exhibiting a lower stability. Root biomass production was positively related to ANPP (R2 = 0.40). Overall, attention should be given to root biomass accumulation in large-scale biofuel production as it is a major source of carbon sequestration.

Environmental Sciences & Ecology↗
DOE OSTI2025

Relationship between atomic and electronic structure in Ln-bearing oxides

Metastable states of matter are of great interest as they offer the promise of novel functionality. They are often a natural consequence of exposure to nonequilibrium environments. In oxides, metastability can take the form of new polymorphs, chemical disorder, and even amorphization. While significant attention has been given to the impact those changes have on the atomic properties of the material, the corresponding changes in the electronic structure have received less attention. Here, using density functional theory, we consider how the electronic structure varies with potential metastable structures in two classes of lanthanide-bearing oxides—pyrochlores and interlanthanide sesquioxides. We find that the changes depend strongly on both the crystal structure and crystal chemistry of the compound with, for example, disordering and amorphization either increasing or decreasing the bandgap depending on the chemistry. For the 𝐴 2 ⁢𝐵 2 ⁢O 7 pyrochlores, we find different dependencies of the bandgap on the 𝐴 = 𝐿⁢𝑛 cations as the 𝐵 cation is changed, which we relate to the nature of the density of states at the conduction band minimum for different 𝐵 chemistries. Our calculations are validated by electron energy loss spectroscopy measurements for two pyrochlore compounds in which amorphization does reduce the bandgap, consistent with our calculations on these two compounds. In conclusion, our results highlight the relationship between atomic and electronic structure and how radiation can be used to modify and potentially control the electronic properties of oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Engineering a non-Hermitian second-order topological insulator state in quasicrystals

Non-Hermitian topological phases have gained immense attention due to their potential to unlock novel features beyond Hermitian bounds. PT -symmetric (parity time-reversal symmetric) non-Hermitian models have been studied extensively over the past decade. In recent years, the topological properties of general non-Hermitian models, regardless of the balance between gains and losses, have also attracted vast attention. Here, we propose a non-Hermitian second-order topological (SOT) insulator that hosts gapless corner states on a two-dimensional quasicrystalline lattice (QL). We first construct a non-Hermitian extension of the Bernevig-Hughes-Zhang model on a QL generated by the Amman-Beenker tiling. This model has real spectra and supports helical edge states. Corner states emerge by adding a proper Wilson-mass term that gaps out the edge states. We propose two variations of the mass term that result in fascinating characteristics. In the first variation, we obtain a purely real spectra for the second-order topological phase. In the latter, we get a complex spectra with corner states localized at only two corners due to the higher-order non-Hermitian skin effect of the edge modes. Furthermore, our findings pave a path to engineering exotic SOT phases where corner states can be localized at designated corners.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Two-way coupled particle-turbulence interaction: Effect of numerics and resolution on fluid and particle statistics

Euler-Lagrange point-particle simulation has emerged as a premier methodology for studying dispersed particle-laden flows. This method's popularity stems from its ability to resolve fine-scale fluid structures while also tracking individual particles at reduced cost using an appropriate particle acceleration model. However, the point-particle model has known convergence issues in that refinement of the fluid grid can lead to changes in the predicted statistics. The reasons for non-convergence are twofold: the point-particle two-way coupling force in the Navier-Stokes equations requires a numerical regularization and, without careful implementation, yields a singular force on the fluid with grid refinement. The second factor that yields grid-dependent statistics is that the point-particle force model in general depends on the undisturbed fluid velocity. When the undisturbed fluid velocity is not robustly modeled in a grid-insensitive way, the calculated force for both particles and fluid will be grid-dependent, contaminating their respective statistics. While the first issue regarding regularizing the point-particle source term has received attention in the literature, the consequences of robustly modeling the undisturbed velocity in the context of grid refinement of turbulence has received little attention. Here, we consider decaying homogeneous isotropic turbulence laden with particles at different Stokes numbers. For a given Stokes number, we systematically refine the grid and demonstrate that explicitly modeling the undisturbed fluid velocity yields relative grid insensitivity for the energy of the particle and fluid phases, as well as acceleration of the particles. We also demonstrate that an appropriately defined dissipation rate is also grid-insensitive when an undisturbed fluid velocity correction is used. In contrast, when the undisturbed fluid velocity is modeled using the conventional approach of interpolating the local fluid velocity to the particle location, we show this procedure yields divergent statistics with grid refinement. In particular, we show that higher-order interpolation of the fluid velocity in two-way coupled problems is worse than lower-order interpolation, in the absence of a correction procedure to estimate the undisturbed fluid velocity. We also examine velocity derivative statistics of the fluid phase and demonstrate that these statistics are not in general convergent even when the undisturbed fluid velocity is explicitly modeled. Collectively, the observations in this paper are used to present a philosophy on the types of questions which are answerable with point-particle methods.

42 ENGINEERING↗
DOE OSTI2022

Thermal properties of the metallic delafossite PdCo⁢O 2 : A combined experimental and first-principles study

Metallic delafossite materials (e.g., PdCo⁢O 2 , PtCo⁢O 2 ), have attracted much recent attention due to record-high oxide conductivities, the origins of which remain unclear. Relatively little attention has been paid to their related thermal properties, however. Here, we address this via wide temperature range experimental studies of the crystal structure, thermal expansion, and specific heat of single-crystal PdCo⁢O 2 , combined with density-functional theory (DFT) calculations of the electronic and phononic densities of states, and thus thermal properties. PdCo⁢O 2 is shown to retain the $R\bar{3}m$ space group from 12 to 1000 K, exhibiting a- and c-axis thermal expansion in good quantitative agreement with DFT-based lattice dynamics calculations. The Co-O bond lengths additionally elucidate the stability of the low-spin state of the nominally Co 3+ ions, which is a notable difference between the edge-shared Co-O octahedra in PdCo⁢O 2 and the corner-shared octahedra in Co-based perovskites. Measurements of specific heat from 1.9 to 400 K provide accurate values for the Debye temperature and Sommerfeld coefficient, the phononic part being describable via a combined Debye-Einstein approach (accounting for high-frequency oxygen-related optical phonons), with excess intermediate-temperature specific heat due to a prominent low-energy peak in the phonon density of states. Most significantly, all electronic and phononic contributions to the specific heat are shown to be remarkably closely reproduced by DFT-based calculations, establishing quantitative understanding of key thermal properties of the metallic delafossite PdCo⁢O 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Planning for a Resilient Home Electricity Supply System

Resilience of power systems is already a key issue that is getting frequent attention all over the world. It is useful to analyze resilience issues not only for bulk supply, but at all levels including at a customer level. This is because distributed energy resources can play a prominent role in enhancing resilience. Although the literature on planning models, tools and data for bulk supply and distribution systems have expanded in recent years, customer-centric planning, e.g., for an individual household, is yet to receive adequate attention. Although solar PV and battery storage at a household level have been analyzed, how these resources can be optimally combined, together with grid supply, from a resilience perspective is the focus of this study. The study demonstrates how a conceptual framework can be developed to show the trade-off between system costs and resilience including its dimensions such as duration, depth and frequency of service outages. A planning model is developed that incorporates multiple facets of resilience and individual customer preferences. The model considers power system resilience explicitly as a constraint. The model is implemented for a household level case study in Miami, Florida. The results show there are complex trade-offs among different dimensions of resilience. The study demonstrates how combined resilience metrics can be formulated and evaluated using the proposed least-cost planning model at a household level to optimize grid supply together with solar, battery storage and diesel generators. The model allows a planner to directly embed a resilience standard to drive the optimal supply mix. These concepts and the modeling construct can also be applied at other levels of planning, including community level and bulk supply system planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction

Reservoir inflow prediction is crucial for water resource management, yet existing approaches mainly focus on single-reservoir models that ignore spatial dependencies among interconnected reservoirs. We introduce AdaTrip as an adaptive, time-varying graph learning framework for multi-reservoir inflow forecasting. AdaTrip constructs dynamic graphs where reservoirs are nodes with directed edges reflecting hydrological connections, employing attention mechanisms to automatically identify crucial spatial and temporal dependencies. Evaluation on thirty reservoirs in the Upper Colorado River Basin demonstrates superiority over existing baselines, with improved performance for reservoirs with limited records through parameter sharing. Additionally, AdaTrip provides interpretable attention maps at edge and time-step levels, offering insights into hydrological controls to support operational decision-making. Our code is available at https://github.com/humphreyhuu/AdaTrip.

Hu, Pengfei [ORNL] (ORCID:0009000367130950)↗
DOE OSTI2023

Reinforcement-Learning-Based Smart Water Heater Control: An Actual Deployment

Utilizing smart control algorithms for electric water heaters (EWHs) is essential for fully harnessing the demand response (DR) potential of EWHs. For this reason, the use of reinforcement learning (RL) algorithms for EWHs has received increasing attention in recent years. However, existing RL approaches are either simulation-based or use pretrained RL agents. To this end, this paper presents the real-world deployment of a set of model-free RL approaches that aim to minimize the electricity cost of a EWH under a time-of-use electricity pricing policy using standard DR commands (e.g., shed, load up). The experiment results showed that the RL agents can help save electricity cost in the range of 11% to 14% compared to the baseline operation. This study demonstrated that RL-based EWH controllers can be deployed in real world without any prior training and can still save electricity cost.

deep learning↗
DOE OSTI2024

Enhancing Network Anomaly Detection Using Graph Neural Networks

In the world of Internet of Things (IoT) networks, where devices are constantly communicating, keeping them secure from cyber threats is critical. This paper introduces a novel approach to detecting unusual and potentially harmful activities in these networks using graph neural networks (GNNs). We combine two specific types of GNNs-GraphSAGE and graph attention networks (GAT)-to create a model that understands and represents the behaviors and interactions in a network. GraphSAGE creates an embedding of network activities by examining local data interactions, while GAT directs the model's focus to the most critical interactions. By integrating these two methods in a single model that considers different types of interactions (both host and flow nodes), we aim to create a system that accurately represents the current state of a network and can also spot anomalies effectively while reducing false positives and negatives. Our innovative approach has demonstrated promising results, achieving an accuracy of 98% on the UNSW-NB15 dataset, significantly outperforming standalone GraphSAGE and GAT models. This underscores its potential as a robust framework for securing IoT networks against cyber threats and anomalies.

Marfo, William↗
DOE OSTI2023

On Distribution Grid Optimal Power Flow Development and Integration

Due to changes in electric distribution grid operation, new operation regimes have been recommended. Distribution grid optimal power flow (DOPF) has received tremendous attention in the research community, yet it has not been fully adopted across the utility industry. Our paper recognizes this problem and suggests a development and integration procedure for DOPF. We propose development of DOPF as a three step procedure of 1) processing the grid, 2) obtaining a tractable solution, and 3) implementing multiple solution algorithms and benchmarking them to improve application reliability. For the integration of DOPF, we demonstrate how a DOPF federate may be developed that can be integrated in a co-simulation environment to mimic the real-world conditions and hence improve its practicality to be deployed in the field. To demonstrate the efficacy of the proposed methods, tests on IEEE 123 bus system are performed where the usage of tractable formulation in DOPF algorithm development and its comparison to the benchmark solution are demonstrated.

Hanif, Sarmad↗
DOE OSTI2025

The Study of Microbial Physiology Under Microoxic Conditions Is Critical but Neglected

ABSTRACT During the early evolution of life on Earth, the environment was largely free of molecular oxygen, and only anaerobic life existed. With the subsequent oxidation of oceans and the atmosphere, a wide range of environmental niches, ranging from anoxic to microoxic/hypoxic and oxic, developed. Despite this broad range of natural environments, microbiology as a field has focused on the physiology, metabolism, and genetics of aerobic microorganisms, with less attention paid to anaerobes and much less attention paid to microaerophiles. The disparity in studies between aerobic and anaerobic conditions is rampant in host‐associated systems, particularly in human health, and studies of microorganisms in intermediate oxygen conditions between fully aerobic and fully anoxic conditions are exceedingly rare. Studies on the physiological behaviour, metabolism, growth response, and drug susceptibility patterns of commensal and pathogenic organisms are almost totally neglected in microoxic conditions. Furthermore, microorganisms from microaerobic and microoxic ecosystems have been less robustly explored in terms of physiology, growth, and metabolism. In this work, we highlight the importance of understanding the physiological and metabolic behaviours of microorganisms under hypoxic or microoxic conditions.

Environmental Sciences & Ecology↗