SEARCH · Search NASA

Results for “Interaction integral”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Twisted Nonlinear Optics in Monolayer van der Waals Crystals

In addition to a plethora of emergent phenomena, the spatial topology of optical vortices enables an array of applications in optical communications and quantum information science. Multibeam nonlinear optical processes, augmented by optical vortices, are essential in this context, providing robust access to an infinitely large set of quantum states associated with the orbital angular momentum of light. Here, we push the boundaries of vortex nonlinear optics to the ultimate limits of material dimensionality. By exploiting multipulse difference frequency, sum frequency, and four-wave mixing in monolayer quantum materials, we demonstrate their ability to independently control the orbital angular momentum and radial distribution of vortex light-fields in addition to their wavelength. Due to the atomically thin nature of the host crystal, this control spans a broad spectral bandwidth in a highly integrable platform that is unconstrained by the traditional limits of bulk nonlinear optical materials. Our work heralds an innovative path for ultracompact and scalable hybrid nanophotonic technologies empowered by twisted nonlinear light–matter interactions in van der Waals nanomaterials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Optimal Electric Grid Black Start Restoration Subject to Intentional Threats

Efficient restoration of the electric grid from significant disruptions – both natural and manmade – that lead to the grid entering a failed state is essential to maintaining resilience under a wide range of threats. Restoration follows a set of black start plans, allowing operators to select among these plans to meet the constraints imposed on the system by the disruption. Restoration objectives aim to restore power to a maximum number of customers in the shortest time. Current state-of-the-art for restoration modeling breaks the problem into multiple parts, assuming a known network state and full observability and control by grid operators. These assumptions are not guaranteed under some threats. This paper focuses on a novel integration of modeling and analysis capabilities to aid operators during restoration activities. A power flow-informed restoration framework, comprised of a restoration mixed-integer program informed by power flow models to identify restoration alternatives, interacts with a dynamic representation of the grid through a cognitive model of operator decision-making, to identify and prove an optimal restoration path. Application of this integrated approach is illustrated on exemplar systems. Validation of the restoration is performed for one of these exemplars using commercial solvers, and comparison is made between the steps and time involved in the commercial solver, and that required by the restoration optimization in and of itself, and by the operator model in acting on the restoration optimization output. Publications and proposals developed under this work, along with a path forward for additional expansion of the work, and summary of what was achieved, are also documented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Polyethylene Glycol Surface Modification and Polythiophene Side-Chain Chemistry: A Combined Strategy toward High-Capacity Lithium-Ion Battery Anodes

In the development of high-capacity lithium-ion batteries (LIBs), the combined optimization of active material interfaces and polymer binder chemistry plays a critical role in improving electrode performance and longevity. This work explores a dual design strategy incorporating polyethylene glycol (PEG) surface modification and carboxylated polythiophene side-chain tailoring to enhance the electrochemical behavior of magnetite (Fe 3 O 4 )-based anodes. PEG is employed to improve interfacial stability, while carboxylated polythiophene binders with varying alkyl side-chain lengths─poly[3-(potassium-4-butanoate)thiophene-2,5-diyl] (P3KBT), poly[3-(potassium-5-pentanoate)thiophene-2,5-diyl] (P3KPT), and poly[3-(potassium-6-hexanoate)thiophene-2,5-diyl] (P3KHT)─are used to modulate molecular interactions and ion transport. Among these three analogs, the PEG–Fe 3 O 4 –P3KHT electrode exhibits superior ion-transfer kinetics, the highest capacity retention, and the lowest charge-transfer resistance after extended cycling. Compared to their non-PEG analogs, PEG-coated electrodes demonstrate enhanced structural integrity and electrochemical behavior, emphasizing the synergistic effects of surface modification and side-chain chemistry. These findings highlight the importance of interfacial interactions and molecular design in achieving robust and high-performance composite anodes for next-generation LIBs.

Fe3O4↗

DOE OSTI2025

Application of Artificial Intelligence/Machine Learning to Operations Research

This report examines the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on operations research, private industry, and government sectors, highlighting their applications in automating processes, enhancing decision-making, and optimizing complex systems. AI/ML technologies have revolutionized industries through predictive maintenance, supply chain optimization, and autonomous systems, while also advancing public safety and defense operations. However, challenges such as data integrity, model transparency, and the need for human oversight persist, particularly in high-consequence environments. The report emphasizes the critical role of explainable AI (XAI) and human-computer interaction models like Human-in-the-Loop (HITL) and Human-on-the-Loop (HOTL) in fostering trust and accountability. Balancing automation with ethical responsibility and transparency is essential for the continued successful integration of AI/ML into operational and strategic decision-making frameworks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Shape Persistent, Highly Conductive Ionogels from Ionic Liquids Reinforced with Cellulose Nanocrystal Network

Abstract Shape‐persistent, conductive ionogels where both mechanical strength and ionic conductivity are enhanced are developed using multiphase materials composed of cellulose nanocrystals and hyperbranched polymeric ionic liquids (PILs) as a mechanically strong supporting network matrix for ionic liquids with an interrupted ion‐conducting pathway. The integration of needlelike nanocrystals and PIL promotes the formation of multiple hydrogen bonding and electrostatic ionic interaction capacitance, resulting in the formation of interconnected networks capable of confining a high amount of ionic liquid (≈95 wt%) without losing its self‐sustained shape. The resulting nanoporous and robust ionogels possess outstanding mechanical strength with a high compressive elastic modulus (≈5.6 MPa), comparable to that of tough, rubbery materials. Surprisingly, these rigid materials preserve the high ionic conductivity of original ionic liquids (≈7.8 mS cm −1 ), which are distributed within and supported by the nanocrystal network‐like rigid frame. On the one hand, such stable materials possess superior ionic conductivities in comparison to traditional solid electrolytes; on the other hand, the high compression resistance and shape‐persistence allow for easy handling in comparison to traditional fluidic electrolytes. The synergistic enhancement in ion transport and solid‐like mechanical properties afforded by these ionogel materials make them intriguing candidates for sustainable electrodeless energy storage and harvesting matrices.

Lee, Hansol↗

DOE OSTI2024

Mechanically Reinforced Pseudosolid Polyelectrolyte Membranes via Layer-by-Layer Assembly for High-Performing Lithium-Metal Batteries

Ionogels are emerging as high-potential pseudosolid electrolytes for lithium-metal batteries (LMBs), leveraging their intrinsic high ionic conductivity from entrapped ionic liquid (IL) electrolytes. However, their practical application is hindered by poor mechanical strength stemming from the confinement of ILs within a polymer matrix. To address this challenge, the formation of conformal polyion coatings with functional groups is reported to be relevant to LMBs’ application on ionogels, utilizing a layer-by-layer (LbL) assembly strategy. Here, this approach significantly enhances the mechanical strength (Young's modulus and tensile strength) and electrochemical performance of ionogels, owing to the tailored interface modifications introduced by functional groups’ specific conformal polyion coatings. The core of this methodology leverages the inherent ionic structure of ionogels to enable facile interface modification through Coulombic interactions between polyanions and polycations. These conformally coated interface functionalized membranes show improved electrochemical performance when integrated with cathode materials such as LiFePO 4 (LFP) and LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) in an LMB configuration, underscoring their potential for robust, high-conductivity, pseudosolid membranes for LMB applications. These innovative pseudosolid membranes offer improved mechanical and electrochemical properties, leading to higher battery efficiency and safety, making them promising candidates for next-generation LMB technology.

25 ENERGY STORAGE↗

DOE OSTI2023

The importance of explicitly representing the streambed in watershed models

Abstract The streambed is the critical interface between the aquatic and terrestrial systems and hosts important biogeochemical hot spots within river corridors. Although the streambed characteristics are significantly different from those of its surrounding soil, the streambed itself has not been explicitly represented in watershed models. Here, we explicitly incorporated a streambed layer into an integrated hydrologic model through model parameterization and discretization. We examined the hydrological effects of streambed characteristics, including hydraulic conductivity ( K ), layer thickness, and resolution, on the exchange fluxes across the streambed as well as the streamflow at the watershed outlet. The numerical experiments were performed in the American River Watershed, a headwater, mountainous watershed within the Yakima River Basin in central Washington. Despite having a negligible effect on the watershed streamflow, an explicit representation of the streambed with distinctive properties dramatically changed the magnitude and variability of the exchange flux. In general, a larger streambed K along with a thicker streambed layer induced larger exchange fluxes. The exchange flux was most sensitive to the streambed resolution. A finer streambed resolution increased exchange fluxes per unit area while reducing the overall exchange volumes across the entire streambed. The amount of baseflow decreased by 6% as the streambed resolution increased from 250 to 50 m. This finding is important because these hydrological changes may, in turn, affect the exchange of nutrients and contaminants between surface water and groundwater and the associated biogeochemical processes. Our work demonstrated the importance of representing streambeds in fully distributed, process‐based watershed models to better capture the exchange flow dynamics in river corridors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Decay amplitudes to three hadrons from finite-volume matrix elements

We derive relations between finite-volume matrix elements and infinite-volume decay amplitudes, for processes with three spinless, degenerate and either identical or non-identical particles in the final state. This generalizes the Lellouch-Lüscher relation for two-particle decays and provides a strategy for extracting three-hadron decay amplitudes using lattice QCD. Unlike for two particles, even in the simplest approximation, one must solve integral equations to obtain the physical decay amplitude, a consequence of the nontrivial finite-state interactions. We first derive the result in a simplified theory with three identical particles, and then present the generalizations needed to study phenomenologically relevant three-pion decays. The specific processes we discuss are the CP-violating K → 3π weak decay, the isospin-breaking η → 3π QCD transition, and the electromagnetic γ* → 3π amplitudes that enter the calculation of the hadronic vacuum polarization contribution to muonic g - 2.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Weighted nodal domain averages of eigenstates for quantum Monte Carlo and beyond

In this report we study the nodal properties of many-body eigenstates of stationary Schrödinger equation that affect the accuracy of real-space quantum Monte Carlo calculations. In particular, we introduce weighted nodal domain averages that provide a new probe of nodal surfaces beyond the usual expectations. Particular choices for the weight function reveal, for example, that the difference between two arbitrary fermionic eigenvalues is given by the nodal hypersurface integrals normalized by overlaps with the bosonic ground state of the given Hamiltonian. Noninteracting and fully interacting Be atom with corresponding almost exact and approximate wave functions are used to illustrate several aspects of these concepts. Variational formulations that employ different weights are proposed for prospective improvement of nodes in variational and fixed-node diffusion Monte Carlo calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Enhancement of phase change material hysteresis model: A case study of modeling building envelope in EnergyPlus

Nowadays, buildings are expected to offer demand side services to the power grid to enhance the electrical load flexibility, which leads to the concepts of grid-interactive efficient buildings (GEBs). Phase change material (PCM)-based thermal energy storage has seen increasing attention in recent years for peak load shifting of grid-interactive efficient buildings (GEBs). Numerical models are critical tools for design and evaluation of PCM-integrated systems. Most industrial-grade PCMs are reported to melt/freeze over a temperature range instead of at a unique temperature. Such thermal hysteresis effect significantly affects the reliability of simulation results because not only the heat transfer process depends on melting and freezing temperatures, the PCM thermal properties change significantly during the phase change process as well. This study is aimed to develop a model for the PCMs used in the building envelope with the capability to accurately simulate hysteretic behaviors. Further, this model is based on a two-phase assumption and is implemented in a whole building energy performance simulation program (i.e., EnergyPlus). A comparison between numerical results and experimental data shows that during a complete phase transition, the two-phase model could achieve a good agreement with the experimental data. During a partial phase transition, the two-phase model could lead to significant improvements compared to other alternative PCM models, including the existing PCM model in EnergyPlus. Last, whole building simulations were performed to study this model's performance regarding heating/cooling loads and zone mean air temperature of a given building. The results show that the difference in hourly heating/cooling loads introduced by the models was less than 1% in design conditions, while significant changes were observed in both hourly heating/cooling loads and zone mean air temperature when the PCM envelope underwent partial phase transition processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Closing transdisciplinary collaboration gaps of food-energy-water nexus research

The nexus of food, energy, and water (FEW) systems is key to ensuring global sustainability in the face of climate change, population growth, and urbanization. To address FEW resources inequity among different regions and countries, transdisciplinary research networking becomes increasingly important for tackling this intractable, complex grand challenge. In contrast to interdisciplinary or multidisciplinary research, transdisciplinary research emphasizes the interactions of scientific, cognitive, and social factors from a top-down view. Intellectual and strategic integrations entail weaving scientific, socioeconomic, and political perspectives together into a new convergence model and fostering a shared vision and comparable assessment, though these goals might not be realistically achievable in the short term. This article summarizes major barriers to transdisciplinary research on FEW nexus grand challenges and possible solutions to be implemented at multiple levels of distinct social systems. Implementation of the solutions relies on not only top-down incentives of governments but also bottom-up initiatives of academic communities and individual researchers. The relevance of shared interests and visions between the research communities and the public is emphasized.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Uncertain Pathways to a Future Safe Climate

Abstract Global climate change is often thought of as a steady and approximately predictable physical response to increasing forcings, which then requires commensurate adaptation. But adaptation has practical, cultural and biological limits, and climate change may pose unanticipated global hazards, sudden changes or other surprises–as may societal adaptation and mitigation responses. These poorly known factors could substantially affect the urgency of mitigation as well as adaptation decisions. We outline a strategy for better accommodating these challenges by making climate science more integrative, in order to identify and quantify known and novel physical risks including those arising from interactions with ecosystems and society. We need to do this even–or especially–when they are highly uncertain, and to explore risks and opportunities associated with mitigation and adaptation responses by engaging across disciplines. We argue that upcoming climate assessments need to be more risk‐aware, and suggest ways of achieving this. These strategies improve the chances of anticipating potential surprises and identifying and communicating “safe landing” pathways that meet UN Sustainable Development Goals and guide humanity toward a better future.

Sherwood, S. C.↗

DOE OSTI2024

Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model

Abstract Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Hydropower expansion in eco-sensitive river basins under global energy-economic change

Vast hydropower resources remain untapped globally, the deployment of which could provide energy-economic benefits but impact riverine ecosystems. Across eco-sensitive river basins, it is unclear how drivers of hydropower expansion, such as rapid economic growth and a low-carbon energy transition, could interact with countervailing forces, such as increasingly cost-competitive variable renewable energy (VRE). Using an integrated energy-water-economy model, we explore the effects of these forces on long-term hydropower expansion in the world’s 20 most eco-sensitive basins, which have high ecological richness and untapped hydropower potential. Here, we find that a low-carbon transition exerts the strongest development pressure, causing deployment exceeding 80% of exploitable potential in more than 72% of eco-sensitive basins by 2050, most of which have limited deployment today. Rapid economic growth induces such extensive deployment in only 44% of eco-sensitive basins. Enhanced integration of VRE reduces deployment, alleviating the impacts of rapid economic growth but not the low-carbon transition.

13 HYDRO ENERGY↗

DOE OSTI2021

ADDS-EVS: An agent-based deployment decision-support system for electric vehicle services

Rapid and sustainable development of the electric vehicle (EV) industry places the requirement for the plan of EV deployment. For public EV, existing models mainly focus on the charging facility design and fail to capture the multi-modal scenarios. In this work, we develop an agent-based decision-support system for multi-modal electric transits to locate the optimal combinations of key parameters, including the fleet size, the transit schedule, the charging facility design, and the routing strategy. We demonstrate the utilities of our system by simulating public EV services deployed to serve travel needs related to a transportation hub in New York City. To support the decision of the fleet size, we summarize system-level performances including the total satisfied demand, passengers' waiting time, vehicle idling time. The spatial and temporal patterns are extracted to serve a deeper understanding of system dynamics and service quality. Finally, we investigate the interaction between the fleet size design and the routing strategy. The results suggest a necessity of integrating the operation strategies into the planning phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗

DOE OSTI2025

Radsource Mr: Mixed Reality Planning Tool For Radioactive Recovery

The RadSource MR system leverages Meta Quest 3's advanced mixed reality capabilities to create a comprehensive spatial planning platform for end-of-life sealed radioactive source recovery operations. The application utilizes the Quest 3's high-resolution passthrough cameras and spatial mapping algorithms to generate accurate 3D environmental models. Core technical components include: (1) Real-time spatial measurement algorithms calculating distances, angles, slopes, and surface areas with sub-centimeter accuracy; (2) Virtual object placement system allowing users to position digital representations of recovery equipment (trailers, containment vessels, protective barriers) within the real environment; (3) Voice recording and annotation system for hands-free documentation in protective equipment; (4) 3D mesh capture and storage capabilities for post-operation analysis and regulatory documentation. (5) Procedure documentation is available for viewing in Mixed Reality, providing an innovative and convenient way to access the information during pre-visit and inspection activities. (6) Support for screen capture for the view for real world and virtual objects together to use it later for planning. The system integrates computer vision techniques for environmental understanding, spatial mathematics for precise measurements, and human-computer interaction principles optimized for hazardous environment operations. Data persistence allows teams to save and share planning sessions across multiple stakeholders while maintaining operational security requirements.

Khadka, Rajiv [Idaho National Laboratory (INL), Id↗

DOE OSTI2026

INtegrated Fluid & paRticles simulatioN cOde (INF&RNO) v1.0

INF&RNO (INtegrated Fluid & paRticle simulation cOde) is a 2D cylindrical (r-z) code to model the interaction of short laser pulse(s) with an underdense plasma. The code is based on an envelope model for the laser field, and the action of the laser on the plasma is modeled with the time-averaged ponderomotive force approximation. The code features an improved laser envelope solver which enables an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution.

Benedetti, Carlo [Lawrence Berkeley National Labor↗