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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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This report depicts local photovoltaic components, interdependencies with the grid, and local two-way communication pathways. It identifies physical and virtual risks and delineates between photovoltaic and grid scale components. It provides readers with a fundamental overview of the most relevant and critical physical components and serves as a basic educational resource for readers.
Atomic-scale control in plasma processing is becoming increasingly critical for fabricating of advanced semiconductor devices, particularly as the industry shifts toward three-dimensional (3D) architectures and high-aspect-ratio (HAR) structures. This review presents a comprehensive overview of recent developments in atomic-scale controlled plasma processes, organized along two key directions: the hierarchical structure of plasma–surface interactions and the generational evolution of atomic layer processing (ALP) technologies. We examined the gas phase, where molecular design enables selective generation of ions and radicals; the boundary layer, where transport phenomena govern species delivery into nanoscale features, and the surface, where temperature-dependent reactions and cyclic processing determine etching selectivity and precision. Building on this foundation, we outline five generations of ALP—from thermal atomic layer deposition to transport-aware, temporally and structurally decoupled processes—highlighting the increasing sophistication of process control. The review further explores the transition from empirical recipe development to science-based, data-driven methodologies. By integrating quantum-chemical modeling, advanced diagnostics, and machine learning, we demonstrated how predictive models can link plasma species composition to process outcomes, enabling autonomous and adaptive control strategies. Finally, this review discusses the broader societal implications of plasma process innovation through the E4 quartet: energy and resource efficiency, environmental sustainability, evolutionary advancement, and educational promotion. These principles guide the development of sustainable and intelligent atomic-scale manufacturing technologies that are not only technically advanced but also socially responsible.
Research at the DIII-D National Fusion Facility in San Diego focuses on short pulse plasma discharges that specialize on various shaping profiles. High-speed data collection is a critical component for the operation of many of DIII-D’s diagnostics and is fundamental for capturing high-resolution data used in experimental data analysis. Differing techniques enable the plasma control system (PCS) to perform complex real-time feedback control on microsecond time scales. This work presents a comprehensive overview of data acquisition, focusing on the hardware and software used in reliable data acquisition at DIII-D. The robust nature of the data acquisition system allows for various techniques to coexist seamlessly. However, as modern systems capable of nanosecond resolution become more common, existing architectures will need to be modified. Here, by addressing the key challenges of high-speed data acquisition, DIII-D is able to provide real-time data used in plasma operation and has the ability to acquire high fidelity data needed for future experimental fusion reactors, such as ITER.
This final technical report summarizes the key accomplishments on the CALORIE project, a DOE Early Career award received by PI Henry Hoffmann at the University of Chicago. CALORIE’s main goal was to create principled methodologies, tools, and practices to help scientists and high-performance computing (HPC) operators maximize the performance and insights obtained from scientific computing applications in the face of exascale power constraints. The project accomplished these goals by completing the following objectives: • Designing a language for describing application goals (including constraints and objectives) and system capabilities. The application goals will include things like which simulations or simulations plus in situ analysis will be run together, what the power constraints are, and what requirements there are for in situ analysis (for example, a desired frame rate for visualization). The system capabilities include all components that can be adjusted to tradeoff power and performance. • Designing a runtime system that takes specified goals and capabilities and dynamically determines what capabilities to use to meet the goals. This runtime adapts to changes in goals, application behavior, or available capabilities to automatically maintain the goals despite unexpected disturbances. • Developing a foundational understanding of how power constraints affect the problem of scheduling applications in large-scale systems. This report provides an overview of the accomplishments related to each of these key objectives.
This presentation provides an overview of NLR's megawatt-scale controller-hardware-in-the-loop (CHIL) and power-hardware-in-the-loop (PHIL) platforms to evaluate distributed energy resource and microgrid controls for successful field deployment.
This work provides an overview and compares key operating characteristics of select energy storage technologies. This work explores how these storage technologies may be used to improve the flexibility and reliability of power systems given their technical characteristics. The report covers various electrochemical (lithium-ion, lead-acid, flow, sodium-sulfur), chemical (hydrogen), mechanical (pumped hydro storage, compressed air energy storage, flywheels, gravity) and electrical (supercapacitors) storage mediums.
An overview of NEAMS program activities to model fuel fragmentation and microstructual evolution to a group of industry attendees at a meeting hosted by EPRI. Topics include atomistic methods to determine grain boundary strength, phase-field fracture modeling to determine critical pressure at grain boundaries, and coupled phase-field-cluster dynamics to model microstructural evolution.
The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.
The electrocatalytic CO 2 reduction reaction (CO 2 RR) is a promising strategy for converting CO 2 to fuels and value-added chemicals using renewable energy sources. Molecular electrocatalysts show promise for the selective conversion of CO 2 to single products with catalytic activity that can be tuned through synthetic structure modifications. However, for the CO 2 RR by traditional molecular catalysts, beneficial decreases in overpotentials are usually correlated with detrimental decreases in catalytic activity. This correlation is sometimes referred to as a “molecular scaling relationship”. Overcoming this inverse correlation between activity and effective overpotential remains a challenge when designing new, efficient molecular catalyst systems. Here, in this perspective, we discuss some of the concepts that give rise to the molecular scaling relationships in the CO 2 RR by molecular catalysts. We then provide an overview of some reported strategies from the last decade for breaking these scaling relationships. We end by discussing strategies and progress in our own research designing efficient molecular catalysts with redox-active ligands that show high activity at low effective overpotentials for the CO 2 RR.
This report details the conceptual design overview for Department of Energy (DOE) Level 2 milestone M2FT-25IN030101021 titled “Complete conceptual design of a scaled voloxidation apparatus for testing with used nuclear fuel.” Advanced voloxidation uses high temperature nitrogen dioxide (NO2) gas to oxidize uranium dioxide (UO2) material to triuanium octoxide (U3O8) and ultimately to uranium trioxide (UO3). After consideration of multiple available options and inputs, a rotating advanced voloxidation design was determined to be the best fit for the needs of a full-scale apparatus. The system, which will be deployed in hot cell 4 of the Analytical Research Laboratory (ARL), has been designed to meet the space constraints of the facility while still accommodating at least 100g of used nuclear fuel (UNF). The apparatus consists of three main unit operations, including the gas panel, the custom furnace with reaction vessel, and the liquid scrubber.
Abstract The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.
Modelling floating offshore wind turbines (FOWTs) is challenging due to the strong coupling between the aerodynamics of the turbine and the hydrodynamics of the floating platform. Physical testing at scale is faced with the additional challenge of the scaling mismatch between Froude number and Reynolds number due to working in the two fluid domains, air and water. In the drive for cost-reduction of floating wind energy, designers may be seeking to move towards high-fidelity numerical modelling as a substitute for physical testing. However, the numerical engineering tools typically used for FOWT modelling are considered as mid-fidelity to low-fidelity tools, and currently lack the level of accuracy required to do so. Furthermore, there is a lack of operational FOWT data available for further development and validation. High-fidelity tools, such as CFD, have greater accuracy but are cumbersome tools and still require validation. Physical scale model testing therefore continues to play an essential role in the development of FOWTs both as a source of validation data for numerical models and as an important development step along the path to commercialization of all platform concepts. The aim of this paper is to provide an overview of both numerical modelling and physical FOWT scale model testing approaches and to provide guidance on the selection of the most appropriate approach (or combination of approaches). The current state-of-the-art will be discussed along with current research trends and areas for further investigation.
his playbook is an introductory guide for local governments to facilitate large-scale solar projects in Southwest Virginia. In a region that has a long history of energy production, solar technologies offer enormous potential for economic development and job growth. Large-scale solar can take many forms, including rooftop or ground-mounted installations at local corporate offices, nonprofit organizations, or schools. It can also encompass utility-scale projects over many acres on former agricultural or timberlands, mined lands, or industrial sites. Regardless of the type of project, solar is a widely popular, cost-competitive energy choice that helps create sustainable and prosperous communities. This playbook is directed to municipal and county governments that have an essential role to play in encouraging large-scale solar projects. The first section provides an overview of state and national trends, including recent state legislation that will impact local oversight of solar development. This is followed by an overview of the solar project approval process from a developer’s perspective. The next section is an overview of the state and local permitting process for solar projects, followed by other development considerations such as local tax revenue options, financing incentives, and considerations for solar on brownfields and previously mined lands. The playbook concludes with a step-by-step guide for local governments to facilitate large-scale solar development.This playbook is part of the Solar Workgroup of Southwest Virginia’s effort to bring solar energy and associated jobs to the region. Over the past few years, the workgroup has met with stakeholder groups and crafted a strategy for local solar energy development. The workgroup has collaborated with cities and counties to bring SolSmart designation to eight counties and cities, implemented group purchase campaigns for commercial solar, and led research efforts.
The addition of nanoparticles (NPs) to a polymer matrix, forming a polymer nanocomposite (PNC), is known to alter the microscopic dynamic processes of both species which leads to unique macroscopic material properties of the PNC. Because the NPs and polymers have overlapping characteristic length, time, and energy scales, the interactions within these materials are complex and the dynamics are interrelated. In this review, we present an overview of experimental, simulation, and theoretical results that probe multi-scale polymer and nanoparticle dynamics in polymer nanocomposites and navigate the dense parameter space presented by these multicomponent systems. Although a variety of PNC systems are mentioned, we focus this discussion on linear thermoplastics filled with hard spherical or cylindrical NPs in the melt state. We begin by introducing PNCs, the dynamic processes within them, and the importance of dynamics for properties and processing. At the smallest length and time scales, we discuss segmental dynamics in PNCs, including the role of polymer attributes, NP attributes, and NP-polymer interactions. Then, we present measurements of collective motions and intermediate (Rouse) dynamics in various PNC materials. At longer length and time scales, we discuss polymer center-of-mass diffusion in PNCs with either spherical or anisotropic NPs. We then explore the dynamics of the NPs in PNCs and polymer melts, including theoretical predictions, simulation results, and experimental observations. Lastly, we note some of the remaining challenges in probing dynamics in PNC materials and fundamentally studying PNCs more generally.
Abstract Large‐scale power systems exhibit more complex dynamics due to the increasing integration of inverter‐based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide‐Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large‐scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra‐high density synchrophasor and point‐on‐wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)‐based advanced applications are introduced, including AI‐based inertia estimation, AI‐based disturbance size and location estimation, AI‐based system stability assessment, and AI‐based data authentication.
Several dark matter models allow for the intriguing possibility of exotic compact object formation. These objects might have unique characteristics that set them apart from their baryonic counterparts. Furthermore, gravitational wave observations of their mergers may provide the only direct window on a potentially entirely hidden sector. Here, we discuss dark white dwarfs, starting with an overview of the microphysical model and analytic scaling relations of macroscopic properties derived from the nonrelativistic limit. We use the full relativistic formalism to confirm these scaling relations and demonstrate that dark white dwarfs, if they exist, would have masses and tidal deformabilities that are very different from those of baryonic compact objects. Further, and most importantly, we demonstrate that dark white dwarf mergers would be detectable by current or planned gravitational observatories across several orders of magnitude in the particle-mass parameter space. Lastly, we find universal relations analogous to the compactness-Love and binary Love relations in neutron star literature. Using these results, we show that gravitational wave observations would constrain the properties of the dark matter particles constituting these objects.
Residential and commercial buildings are responsible for over 30% of global final energy consumption and accounts for ~40% of annual direct and indirect greenhouse gas emissions. Energy efficient and sustainable technologies are necessary to not only lower the energy footprint but also lower the environmental burden. Many proven and emerging technologies are being pursued to meet the ever-increasing energy demand. Catalytic science has a significant new role to play in helping address sustainable energy challenges, particularly in buildings, compared to transportation and industrial sectors. Thermally driven heat pumps, dehumidification, cogeneration, thermal energy storage, carbon capture and utilization, emissions suppression, waste-to-energy conversion, and corrosion prevention technologies can tap into the advantages of catalytic science in realizing the full potential of such approaches, quickly, efficiently, and reliably. Catalysts can help increase energy conversion efficiency in building related technologies but must utilize low cost, easily available and easy-to-manufacture materials for large scale deployment. This entry presents a comprehensive overview of the impact of each building technology area on energy demand and environmental burden, state-of-the-art of catalytic solutions, research, and development opportunities for catalysis in building technologies, while identifying requirements, opportunities, and challenges.
General overview of MFIX-Exa and weak scaling data from Frontier.