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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Designing polymeric membranes with coordination chemistry for high-precision ion separations

State-of-the-art polymeric membranes are unable to perform the high-precision ion separations needed for technologies essential to a circular economy and clean energy future. Coordinative interactions are a mechanism to increase sorption of a target species into a membrane, but the effects of these interactions on membrane permeability and selectivity are poorly understood. We use a multilayered polymer membrane to assess how ion-membrane binding energies affect membrane permeability of similarly sized cations: Cu 2+ , Ni 2+ , Zn 2+ , Co 2+ , and Mg 2+ . We report that metals with higher binding energy to iminodiacetate groups of the polymer more selectively permeate through the membrane in multisalt solutions than single-salt solutions. In contrast, weaker binding species are precluded from diffusing into the polymer membrane, which leads to passage proportional to binding energy and independent of membrane thickness. Our findings demonstrate that selectivity of polymeric membranes can markedly increase by tailoring ion-membrane binding energy and minimizing membrane thickness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tunable exciton binding energy in 2D hybrid layered perovskites through donor–acceptor interactions within the organic layer

The strength of electrostatic interactions within semiconductors strongly affects their performance in optoelectronic devices. An important target is the tuning of a material’s exciton binding energy—the energy binding an electron–hole pair through the electrostatic Coulomb force—independent of its electronic band gap. Here, we report on the doping of a family of two-dimensional hybrid perovskites, in which inorganic lead halide sheets alternate with naphthalene-based organic layers, with tetrachloro-1,2-benzoquinone (TCBQ). For four out of seven n = 1 perovskites, the incorporation of the electron-accepting TCBQ dopant into the organic sublattice containing the electron-donating naphthalene species enabled the tuning of the materials’ 1s exciton binding energy. The naphthalene–TCBQ electron donor–acceptor interactions increased the electrostatic screening of the exciton, in turn lowering its binding energy relative to the undoped perovskite—by almost 50% in one system. Structural and optical characterization showed that the inorganic lattice is not significantly perturbed even though the layer-to-layer spacing increases upon molecular dopant incorporation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Homogeneous, Micron-Scale High-Energy-Density Matter Generated by Relativistic Laser-Solid Interactions

Short-pulse, laser-solid interactions provide a unique platform for studying complex high-energy-density mat ter. We present the first demonstration of solid density, micron-scale keV plasmas uniformly heated by a high contrast, 400 nm laser at intensities up to 2×10 21 W/cm 2 . High-resolution spectral analysis of X-ray emission reveals uniform heating up to 3.0 keV over 1 µm depths. Particle-in-cell simulations indicate the production of a uniformly heated keV plasma to depths of 2 µm. The significant bulk heating and presence of highly-ionized ions deep within the target are attributed to the few MeV hot electrons that become trapped and undergo refluxing within the target sheath fields. In conclusion, these conditions enable the differentiation of atomic physics models such as ionization potential depression in high energy density environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗
DOE OSTI2022

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Interactive Gas Chemistry for Enhanced Science Capabilities of the Energy Exascale Earth System Model Version 3

Atmospheric chemistry plays a crucial role in Earth system models (ESMs), controlling atmospheric composition and radiative balance; it is highly interactive with the physical climate, biogeochemical cycles, and human systems. However, it often imposes computational challenges in an ESM. Here we develop a full troposphere‐stratosphere interactive chemistry module for the US Department of Energy's Energy Exascale Earth System Model (E3SM). We intentionally build a streamlined module based on E3SM version 2 that interacts with other components and maintains all of major chemical and chemistry‐climate feedbacks. The module incorporates a new, highly efficient tracer advection scheme; linearization of stratospheric chemistry; and abridged tropospheric chemical mechanism with 28 reactive tracers. This new model, E3SM‐chem, can readily perform century‐long climate simulations of ozone, methane, and nitrous oxide based on emission scenarios as well as provide hourly budgets for the gas‐phase radicals that drive aerosol chemistry. We evaluate E3SM‐chem with an atmosphere‐only simulation as in the recent climate model intercomparison project (CMIP6) finding results similar to the other CMIP6 models. For the present‐day, E3SM‐chem matches the standard measurement metrics for stratospheric and tropospheric ozone, surface air quality, other key reactive gases like carbon monoxide, and the methane lifetime. Overall, E3SM‐chem maintains the climate fidelity of the baseline model while adding at most 20% to the computational cost of the atmosphere model. Hence, interactive chemistry can be a default configuration for long climate simulations at resolutions of 1° or finer, which is crucial for producing self‐consistent chemistry‐climate feedbacks that alter the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Understanding the Existence of a Na 2 Dimer in a High-Spin State

The recent observation of a high-spin Na 2 dimer formed on the surface of liquid helium nanodroplets raises some fundamental questions, as the ground state of Na 2 is known to have zero spin. Is it protected against spontaneous dissociation? What is its binding energy and interatomic distance? Is it stable at a higher temperature? Using calculations based on density functional theory (with and without long-range interaction) and coupled cluster methods, CCSD(T), we show that the bonding in the high-spin Na 2 dimer is governed by van der Waals interaction with binding energy (bond length) varying between −0.030 eV (5.108 Å) and −0.192 eV (4.231 Å), depending on the computational method used. Thus, the experimental method used by Kresin and coworkers can be very useful to study larger metastable high-spin clusters such as Li 4 which was predicted in 1985 to have a tetrahedral structure carrying a magnetic moment of 2 μ B , while its ground state is planar and nonmagnetic.

Basis sets↗
DOE OSTI2021

A Donor–Acceptor [2]Catenane for Visible Light Photocatalysis

Colored charge-transfer complexes can be formed by the association between electron-rich donor and electron-deficient acceptor molecules, bringing about the narrowing of HOMO–LUMO energy gaps so that they become capable of harnessing visible light. In an effort to facilitate the use of these widespread, but nonetheless weak, interactions for visible light photocatalysis, it is important to render the interactions strong and robust. Furthermore, we employ a well-known donor–acceptor [2]catenane—formed by the mechanical interlocking of cyclobis(paraquat-p-phenylene) and 1,5-dinaphtho[38]crown-10—in which the charge-transfer interactions between two 4,4'-bipyridinium and two 1,5-dioxynaphthalene units are enhanced by mechanical bonding, leading to increased absorption of visible light, even at low concentrations in solution. As a result, since this [2]catenane can generate persistent bipyridinium radical cations under continuous visible-light irradiation without the need for additional photosensitizers, it can display good catalytic activity in both photo-reductions and -oxidations, as demonstrated by hydrogen production—in the presence of platinum nanoparticles—and aerobic oxidation of organic sulfides, such as l-methionine, respectively. This research, which highlights the usefulness of nanoconfinement present in mechanically interlocked molecules for the reinforcement of weak interactions, can not only expand the potential of charge-transfer interactions in solar energy conversion and synthetic photocatalysis but also open up new possibilities for the development of active artificial molecular shuttles, switches, and machines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Single phonon detection for dark matter via quantum evaporation and sensing of He 3

Dark matter is five times more abundant than ordinary visible matter in our Universe. While laboratory searches hunting for dark matter have traditionally focused on the electroweak scale, theories of low mass hidden sectors motivate new detection techniques. Extending these searches to lower mass ranges, well below 1 GeV / c 2 , poses new challenges as rare interactions with standard model matter transfer progressively less energy to electrons and nuclei in detectors. Here, we propose an approach based on phonon-assisted quantum evaporation combined with quantum sensors for detection of desorption events via tracking of spin coherence. The intent of our proposed dark matter sensors is to extend the parameter space to energy transfers in rare interactions to as low as a few meV for detection of dark matter particles in the keV / c 2 mass range. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Towards a numu CC exclusive cross section measurement with one proton and one muon in the final state at the NOvA near detector

NOvA is a long-baseline neutrino experiment at Fermilab that studies neutrino oscillations via electron neutrino appearance and muon neutrino disappearance. The NOvA Near Detector, located 1 km from the NuMI target, records a high rate of neutrino interactions in the energy range of 1-5 GeV. One of the limitations in precise extraction of oscillations is the large systematic uncertainty on neutrino-nucleus interactions. The high rate of neutrino interactions in the NOvA Near Detector provides the opportunity to probe various neutrino interaction processes and nuclear models, via the extraction of cross sections of particular final states. Nuclear models can be improved by measuring neutrino-nucleus cross sections with respect to kinematic variables which are known to be more sensitive to nuclear effects, such as transverse kinematic imbalance (TKI) variables. Usage of TKI variables allows for more direct constraints on models of neutrino scattering, as these variables can more directly investigate, for instance, effects of Fermi motion and final state interactions. In this work, we describe progress towards a method of identifying and reconstructing protons in the NOvA near detector to enable the cross section measurement of charged current neutrino interactions with a visible muon and a proton in the final state, reported in TKI variables.

Weber, Colin [Minnesota U.] (ORCID:000000031117067↗
DOE OSTI2024

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗
DOE OSTI2022

Phase Field Dislocation Dynamics (PFDD) version 2.x

This disclosure is for version 2.x of a mesoscale model called Phase Field Dislocation Dynamics (PFDD). PFDD is used for investigating deformation in nanoscale (grain sizes of ~300 nm and less) materials, such as metals and alloys. This approach models the motion and interaction of individual defects, namely dislocations, in the material using scalar-valued phase field variables, also called order parameters. The system is evolved through energy minimization thus the model calculates the total energy density in terms of the phase field variables. The energy minimization is completed using the Ginzburg-Landau equation, and is implemented with explicit time integration. The total system energy can be comprised of several terms, including the strain energy (which describes dislocation-dislocation interactions), the energy due to an applied stress (dislocation interactions with the applied stress), and a core/lattice (perfect dislocations) or generalized stacking fault (partial dislocations) energy (described the dislocation core structure). The latter term in particular may vary based on the crystal structure being modeled and is typically informed using lower length scale (e.g., atomistic) approaches, although no such (atomistic) calculations are completed within the PFDD algorithm. This basic formulation was previously reviewed by Los Alamos National Laboratory and released under license number C17113. This previously reviewed version we will henceforth refer to as PFDD v1.0. PFDD v1.0 consisted of 2 codes (one parallel and one serial) plus input files, all written in the C language. This new disclosure is addressing the next versions of the PFDD, versions 2.x. There have been several enhancements of PFDD v1.0, which are described here and included in the attached code, which we will refer to as PFDD v2.0. There are also several new features described here that are either planned or already in process and are expected to be subsequent releases, i.e., v2.1, v2.2, ...v2.x.

Hunter, Abigail↗
DOE OSTI2021

Electronic structure of reduced CeO 2 (111) surfaces interacting with hydrogen as revealed through electron energy loss spectroscopy in comparison with theoretical investigations

Based on both, ab-initio cluster calculations as well as periodic density functional based loss function calculations, we have assigned the origins of the valence electron excitation regime in electron energy loss spectra of well-ordered ceria films in (111) orientation at various states of reduction as well as after exposing the reduced films to hydrogen from the gas phase (Li et al, Angew. Chem. Int. Ed., 58 (2019) 14686–14693). The explicit calculation of intensity distributions using the dipole approximation allow us to draw conclusions about the nature of oxygen vacancies, which occur upon reduction and how those interact with hydrogen to form hydride species. Herein, we also reports a brief discussion of vibrational excitations of hydrogen loaded ceria and corroborates previous interpretations, based on inelastic neutron scattering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Hybrid Fuel Cell and Battery Storage Power Management for Grid-Interactive EV Charging Station

With the increasing adoption of renewable energy sources in grid-interactive Electric Vehicle (EV) charging stations, the role of energy storage systems has become critical. While large energy storage systems have mitigated the intermittency of renewable energy, integrating multi-source energy management with prioritized charging can further enhance the reliability of charging stations (CS). This paper presents a decentralized energy management (DEM) approach combining battery energy storage (BES) and fuel cell (FC) systems using a rule-based line resistance correction droop (LRCD) control technique. The proposed droop control dynamically adjusts the gain to balance the state-of-charge (SoC) of the BES, enhancing power support longevity and improving battery life under varying capacity conditions by reducing current stress. Additionally, the paper addresses the challenges of using fuel cells in linear regions to optimize efficiency and manage various charging scenarios. The CS integrates unity power factor grid interaction, and power support for auxiliary loads, maintaining harmonic distortion within 5% during grid islanding. The approach evaluates DC bus voltage regulation under various scenarios of PV array power fluctuations and dynamic load variations, in both grid-connected and standalone operations. In conclusion, the proposed control strategy is validated on a laboratory prototype through various dynamic load variation and grid islanding scenarios.

Khalid, Mohd [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2021

ACCELERATOR CHALLENGES OF THE LHeC PROJECT

The LHeC project studies the design of a future electron-proton collider at CERN that will run in parallel to the standard LHC operation. For this purpose, the existing LHC storage ring will be combined with an Energy Recovery Linac (ERL), to accelerate electrons up to kinetic energy of 50 GeV. This concept - also applicable to the FCC-eh collider and studied at the PERLE project as prototype version - allows a peak luminosity of 10³⁴ cm⁻² s⁻¹. A sophisticated design of the RF structures, linacs, arcs, and interaction region is required. The electrons are accelerated and, after the interaction point, their energy is recovered through the same RF structures. While this energy recovery concept is a very promising approach, severe challenges are set by the layout of the interaction region, the beam separation concept and the design of the linac and arc lattice for the highest possible momentum acceptance. Emittance control and beam-beam effect of both, electron and proton beams, have been studied in front-to-end simulations and will be presented. We summarise the design principles of the ERL, the optimization of the arc lattice, and the main parameters of the project.

Holzer, B. J.↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Progress toward double-differential cross-section measurements of single charged-pion production in charged current muon neutrino interactions on argon with SBND

Resonant neutrino–nucleus processes constitute a significant portion of neutrino interactions in the few-GeV energy region. Charged-current interactions with a muon and one single charged pion in the final state (CC1$\pi$) are primarily sensitive to resonant processes, while also receiving contributions from non-resonant processes and being strongly affected by nuclear effects and final-state interactions. A precise understanding of this channel is essential for improving neutrino interaction models and reducing systematic uncertainties in oscillation measurements. The Short-Baseline Near Detector (SBND) at Fermilab has collected the largest neutrino–argon dataset to date, providing an excellent opportunity to study CC1$\pi$ interactions on argon. This analysis aims to improve existing single-differential cross-section measurements by reporting results in a variety of kinematic variables and to perform the first double-differential CC1$\pi$ cross-section measurement on argon, using novel techniques for pion energy reconstruction.

Pelegrina-Gutiérrez, Luis [Granada U.] (ORCID:0000↗
DOE OSTI2025

Mott transition and correlation effects on strictly localized states in an octagonal quasicrystal

Flat-band systems have attracted significant attention as platforms for studying strongly correlated electron physics, where the dominance of electron-electron interactions over kinetic energy gives rise to a variety of emergent phenomena. Quasicrystals are compelling systems for studying these phenomena as they host degenerate strictly localized states at zero energy due to perfect destructive interference patterns. In this study, we use the slave-rotor mean-field approach to investigate the effects of electron interactions within the Hubbard model on the Ammann-Beenker quasicrystal. The phase diagram characterizing metallic and Mott insulator regions indicates a first-order phase transition. Our analysis shows that the local coordination number affects the local quasiparticle weight, displaying varying metallicity across the sites. Furthermore, we focus on the strictly localized states that arise in the noninteracting limit. We find that interactions and deviation from particle-hole symmetry induce spectral splitting, broadening, and partial delocalization of the localized states, depending on the local environment. In particular, certain localized states with higher coordination numbers remain more robust compared to others. Finally, our results highlight the critical role of local geometry in shaping correlation effects in flat-band quasicrystals.

Mott insulators↗