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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Platform for Remote Deployment and Training for Enhanced Building Operation Practices (Building Re-Tuning and On-going Commissioning)

While a building’s energy usage is driven largely by its design and use, building operator behavior has a strong influence on its energy consumption. This project developed and piloted a specific, data-driven coaching methodology to help operators understand how they can adjust operations and/or affect no/low-cost repairs or upgrades to their specific building HVAC systems to reduce energy consumption. Named BuildingCoach, the operational optimization method used is based on the Building Re-tuning approach developed by the Pacific Northwest National Laboratory. A building operations analytics market has matured over the past decade, though its potential to affect energy-saving changes has not been fully realized. Training operators to understand the methods for operational optimization with the explicit approach of using building-system performance data is hypothesized to create a more effective, longer lasting result in building energy efficiency, and this strategy is the fundamental premise of this project. With the support of an Industry Advisory Board, the project succeeded in developing materials and recruiting for and delivering three pilot cohorts. Deliverables included twenty-two self-paced training modules (accessed via a Learning Management System) and a web-based platform that includes access to real-time building system data and a repository for building system documentation. The project set out to have 100 participants from 50 buildings in three pilot cohorts. In the end, there were 28 participants from 17 buildings, i.e., a significant shortfall. The first two pilot cohorts had only two buildings in each, and this was partially due to difficulties in deploying the Building Operator Coaching Solution (“the BOCS”), which is technology that extracts the data from the controls network and presents it as prescribed for coaching. In the third cohort, the project team deployed the BOCS successfully to 13 buildings, the methodology was piloted as intended, and numerous opportunities for optimization were identified. The BuildingCoach business plan charts a path to an economically sustainable effort. However, even with a licensing model captured in the final version of the business plan, the scalability is still limited to keeping less than 1,000 buildings affected by 2033. Even so, there are unexplored paths to greater scalability that are being considered. CUNY BPL is working to perpetuate and grow the use of BuildingCoach. As of this writing, about twenty buildings have either been connected or will be connected with operators coached / to be coached in the NYC municipal portfolio, twelve buildings across four campuses in NY State will use BuildingCoach, a NY upstate county wishes for six or seven buildings to participate with the support of funding from NYSERDA, and others have also expressed interest. In the decades to come, there will be an increasing percentage of large and mid-sized buildings that incorporate automated system optimization (ASO), and the building operators’ role will shift to spend more time on maintenance and monitoring. Meanwhile, programs such as BuildingCoach will play a critical role in optimizing operations. And, regardless of the emergence of ASO, operators will still need to understand how their systems operate so that they can monitor them properly. Within that context, BuildingCoach is an important step towards operators’ understanding of efficient building system operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Mapping the N = 40 island of inversion: Precision mass measurements of neutron-rich Fe isotopes

Nuclear properties across the chart of nuclides are key to improving and validating our understanding of the strong interaction in nuclear physics. Here we present high-precision mass measurements of neutron-rich Fe isotopes performed at the TITAN facility. The multiple-reflection time-of-flight mass spectrometer (MR-ToF-MS), achieving a resolving power greater than 600000 for the first time, enabled the measurement of 63–70 Fe, including first-time high-precision direct measurements (δm/m ≈ 10 -7 ) of 68–70 Fe, as well as the discovery of a long-lived isomeric state in 69 Fe. These measurements are accompanied by both mean-field and ab initio calculations using the most recent realizations which enable theoretical assignment of the spin-parities of the 69 Fe ground and isomeric states. Together with mean-field calculations of quadrupole deformation parameters for the Fe isotope chain, these results benchmark a maximum of deformation in the N = 40 island of inversion in Fe and shed light on trends in level densities indicated in the newly refined mass surface.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

REDESIGNING A PERFORMANCE MONITORING SOFTWARE FOR SUPERCOMPUTERS

The objective of this project was to improve upon the existing Watchr software that charts performance test metrics from the Trilinos project run on supercomputers at Sandia and elsewhere across the DOE complex. Software was iteratively designed and developed using Python Pandas and Dash data visualization to improve the extensibility and user experience of Watchr. Documentation is being maintained for future developers who want to extend the application.

Camacho, Dane Joseph [Sandia National Laboratories↗
DOE OSTI2025

Mapping the Outcomes of Stellar Evolution in the Disks of Active Galactic Nuclei

The disks of active galactic nuclei (AGNs) are expected to be populated by numerous stars, either formed in the outer regions of the disk via gravitational instability or captured from the nearby nuclear star cluster. Regardless of their formation mechanism, these stars experience altered evolutionary paths, mostly shaped by the accretion of dense disk material. In this study, through the comparison of different timescales, we chart the evolutionary outcomes of these AGN stars as a function of disk radius and across a range of supermassive black hole masses, spanning from 10 6 to 10 9 M ⊙ , for two popular AGN disk models. We find that in the outer regions of the disk, stars evolve similarly to those in the interstellar medium, but in the inner and denser regions, accretion quickly turns low-mass stars into massive stars, and their fate depends on just how quickly they accrete. If accretion occurs at a faster rate than nuclear burning, they can reach a quasi-steady "immortal" state. If stars accrete faster than they can thermally adjust, runaway accretion occurs, potentially preventing a quasi-steady state and altering the disk structure. During the AGN lifetime, in the regions of the disk that produce massive stars, supernovae (SNe) and gamma-ray bursts (GRBs) may occur within the disk over a wide range of optical depths and ambient densities. Subsequently, in the final phase of the AGN, as the disk becomes depleted, formerly immortal stars will be unable to replenish their fuel, leading to additional SNe and GRBs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Electron capture of superheavy nuclei with realistic lepton wave functions

The superheavy nuclei push the periodic table of the elements and the chart of the nuclides to their limits, providing a unique laboratory for studies of the electron-nucleus interactions. The most important weak decay mode in known superheavy nuclei is electron capture (EC). In the standard calculations of EC, the lepton wave functions are usually considered in the lowest-order approximation. In this work, we investigate the sensitivity of EC rates on the choice of the electron wave functions by (i) assuming the single-particle approximation for the electron wave functions, and (ii) carrying out Dirac-Hartree-Fock (DHF) calculations. The nuclear response is generated based on the state-of-the-art quasiparticle random phase approximation employing relativistic nuclear energy density functional theory. Here, we show that using the improved lepton wave functions reduces the EC rates up to 40% in the superheavy nucleus oganesson (𝑍=118). Interestingly, because of screening effects, the difference between the EC rates obtained with the DHF and single-particle calculations is fairly small.

Atomic orbital↗
DOE OSTI2025

Learning nuclear cross sections across the chart of nuclides with graph neural networks

We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.

Machine learning↗
DOE OSTI2026

Municipal Fleet Action Plan Guide

This action plan template and guide have been designed to support light-duty or medium-duty municipal fleet managers as they plan to adopt electric vehicles. The resource is an adaptation of content created by the National Laboratory of the Rockies (NLR), with support from World Resources Institute (WRI), for participants in the U.S. Department of Energy's Energy to Communities peer-learning cohort, Charting a Path to Municipal Fleet Electrification. Fifteen participating municipalities joined monthly cohort workshops from July through December 2024 to learn and plan for their own fleet electrification. Clean Cities and Communities coalitions supported participating municipalities throughout the cohort series by conducting fleet analysis and planning activities on their behalf. This template is an adapted version of cohort activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Direct identification of Ac and No molecules with an atom-at-a-time technique

The periodic table provides an intuitive framework for understanding chemical properties. However, its traditional patterns may break down for the heaviest elements occupying the bottom of the chart. Here, the large nuclei of actinides (Z > 88) and superheavy elements (Z ≥ 104) give rise to relativistic effects that are expected to substantially alter their chemical behaviours, potentially indicating that we have reached the end of a predictive periodic table. Relativistic effects have already been cited for the unusual chemistry of the actinides compared with those of their lanthanide counterparts. Unfortunately, it is difficult to understand the full impact of relativistic effects, as research on the later actinides and superheavy elements is scarce. Beyond fermium (Z = 100), elements need to be produced and studied one atom at a time, using accelerated ion beams and state-of-the-art experimental approaches. So far, no experiments have been capable of directly identifying produced molecular species. Here ions of actinium (Ac, Z = 89) and nobelium (No, Z = 102) were synthesized through nuclear reactions at the 88-Inch Cyclotron facility at Lawrence Berkeley National Laboratory and then exposed to trace amounts of H 2 O and N 2 . The produced molecular species were directly identified by measuring their mass-to-charge ratios using FIONA (For the Identification Of Nuclide A). These results mark the first, to our knowledge, direct identification of heavy-element molecular species using an atom-at-a-time technique and highlight the importance of such identifications in future superheavy-element chemistry experiments to deepen understanding of their chemical properties.

Pore, Jennifer L. [Lawrence Berkeley National Labo↗
DOE OSTI2024

Assessment of Training Performance, Degradation and Robustness of Paraffin-Wax Impregnated Nb 3 Sn Demonstrator Under High Magnetic Field

In the context of high-energy physics, the use of Nb 3 Sn superconducting magnets as a cost-effective and reliable technology depends on improvements in the following areas: long development and manufacturing cycles, conductor degradation after thermal cycling, long training, as well as a demonstration in accelerator magnets with a beam aperture of the full potential of modern Nb 3 Sn conductors. In short, performance, robustness, and cost are the three issues to be addressed. The Magnet Development project (MagDev) of the Swiss Accelerator Research and Technology initiative (CHART) at the Paul Scherrer Institute (PSI) aims to contribute to the solutions to each of these issues, re-thinking the manufacturing and design process. Here in our program, every innovation is to be validated by means of a panoply of fast-turnaround tools: from non-powered and powered samples and coils, tested under background field, to low-field subscale magnets and high field short prototypes. This work presents one element in this panoply of R&D vehicles: a stress-managed Nb 3 Sn coil called BigBOX, impregnated with paraffin wax, and tested, through a collaboration with the Magnet Development Program of the United States (US-MDP), in the background field of Brookhaven National Laboratory (BNL)’s common coils dipole DCC17.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Perception Testing in Fog for Autonomous Flight

As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). Here, this paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.

aeronautics↗
DOE OSTI2024

Rh → Sb Interactions Supported by Tris(8-quinolyl)antimony Ligands

The study of ambiphilic systems combining L-type and Z-type ligands within the same construct has emerged as a field of active investigation, especially in the cases of ligands containing a group 13 element as a σ-acceptor for transition metals. (1) Parallel to these developments, several groups have investigated more atypical systems in which the Z-type ligand is a group 15 element. (2) Our contributions to this area have focused on the use of phosphinostibine ligands for the generation of transition metal complexes in which the antimony moiety acts as a Z-type ligand. (1d,3) We have shown that the magnitude of the resulting M → Sb interaction can be readily modulated by the oxidation state of the antimony atom (4) as well as its charge which can be manipulated by abstraction of anionic ligands. (5) Our work has also shown that these effects can be leveraged to enhance the catalytic properties of the transition metal center. (4,5) Some of the simplest systems that we have investigated are those resulting from the reaction of platinum dichloride with the bis- or tris-phosphinostibines ClSb(o-dppp) 2 and Sb(o-dppp) 3 , respectively (o-dppp = o-(Ph 2 P)C 6 H 4 ). These reactions proceed by oxidative insertion of the stibine into a Pt- Cl bond to produce complexes A and B, (6) respectively (Chart 1). Reasoning that the properties of these complexes may also be influenced by the nature of the L-type buttresses, we have now questioned whether stibines featuring nitrogen donor ligands could also display the redox noninnocence of their phosphine counterparts and support the formation of such complexes. Following up on some of our work with ambiphilic tellurium-quinoline ligands, (7) we now report on the reaction of tris-(8-quinolyl)stibines (8) toward (MeCN) 3 RhCl 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Abrasion-fission reactions at intermediate energies

The availability of high-intensity, heavy-ion beams coupled to sensitive, large solid-angle acceptance spectrometers has enabled a detailed examination of the fission fragments produced in induced-fission reactions. The abrasion fission process involves the formation of projectile-like prefragments in violent nuclear collisions at relative energies in excess of 100 MeV/u. At intermediate energies below this threshold, experiments suggest a change in the prefragment kinematic qualities. Information regarding the influence of this transitional phase upon the evolution of nuclei approaching the point of scission is scarce. In this article, data are presented for over 200 nuclei from nickel to palladium produced in abrasion-fission reactions of a 80 MeV/u 238 U beam. Cross sections were obtained following yield measurements performed for the principal charge states of the identified fission fragments and a detailed analysis of the ion transmission. A full kinematic analysis of the fission fragments has been performed using the LISE ++ software package, where the trajectory of an ion passing through a spectrometer can be reconstructed based upon measurements at the focal plane. Furthermore, the results obtained at the S800 spectrograph are compared with predictions obtained with a three-fission progenitor (3EER) model. Systematic studies of fission-fragment properties continue to provide a valuable experimental benchmark for theoretical efforts directed toward describing this complex decay channel, that is important in the context of planning experiments to explore the neutron-rich region of the nuclear chart at rare-isotope beam facilities.

59 ≤ A ≤ 8990 ≤ A ≤ 149↗
DOE OSTI2025

The Unitarity-Limit Expansion for Two Nucleons with Perturbative Pions: Digest and Ideas

Theorists love nontrivial fixed points. In the Unitarity Limit, the NN 𝑆-wave binding energies are zero, the scattering lengths infinite, Physics is universal, i.e. insensitive to details of the interactions, and observables display richer symmetries, namely invariance under both scaling and Wigner’s combined SU(4) transformation of spin and isospin. In “Pionless” EFT, both are explicitly but weakly broken and hence perturbative in the Unitarity Window (phase shifts 45° ≲ δ(k) ≲ 135°, i.e. momenta k≈mπ). This Unitarity Expansion provides strong hints that Nuclear Physics resides indeed in a sweet spot: bound weakly enough to be insensitive to the details of the nuclear interaction; and therefore interacting strongly enough that the NN scattering lengths are perturbatively close to the Unitarity Limit. In this paradigm change, NN details are less important than NNN interactions to explain the complexity and patterns of the nuclear chart. This presentation is a digest of the first quantitative exploration of corrections to this picture when pions are included [1] (see there for a more comprehensive list of references). Since the pion mass and decay constant introduce dimensionful scales in the NN system, they explicitly break the symmetries of the Unitarity fixed point. In χEFT, these symmetries must therefore be hidden and instead be classified as emergent.

Griesshammer, Harald W. [The George Washington Uni↗
DOE OSTI2024

Nuclear Integrated Hydrogen Production Analysis Tool

This is an Excel-based time-independent discount cash flow calculator for LWR-HTSE systems. The tool incorporates (1) discounted cash flow and levelized cost of hydrogen (LCOH) analysis, (2) sensitivity analysis with respect to select financial performance metrics with output ‘tornado’ charts, (3) profitability analysis represented by heat maps using the two most sensitive parameters, (4) electricity versus hydrogen production preference analysis by comparing change in net present value (?NPV) between NPP-HTSE and business-as-usual electricity production for the grid, and (5) competitiveness analysis by comparing the calculated LCOH for NPP-HTSE with that of steam methane reforming, which is the conventional process to produce hydrogen.

Cheng, WenChi [Idaho National Laboratory (INL), Id↗
DOE OSTI2022

Persona of Transition Metal Ions in Solids: A Statistical Learning on Local Structures of Transition Metal Oxides

Abstract The local structure of a transition metal (TM) ion is a function of cation elements and valence states. More than that, in this work, by employing a trove of first‐principles data of TM oxides, the local structures of TM cations are statistically analyzed to extract detailed information about cation site preference, bond length, site structural distortion, and cation magnetization. It is found that cation radius alone poorly describes the local structure of a transition metal oxide, while the statistics of coordination number as well as the TMO bond length distribution, especially that of the 3d TMs, can provide comprehensive knowledge for understanding the behavior of TM elements. Based on these statistics, the interplay of site distortion due to the Jahn–Teller effect, cation site similarity, and a new set of ionic radii are all obtained to chart the “persona” of transition metal ions in solids.

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

Discovering nuclear models from symbolic machine learning

Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an open challenge. Here, we explore whether symbolic Machine Learning (ML) can rediscover traditional nuclear physics models or identify alternatives with improved simplicity, fidelity, and predictive power. To address this challenge, we developed a Multi-objective Iterated Symbolic Regression approach that handles symbolic regressions over multiple target observables, accounts for experimental uncertainties and is robust against high-dimensional problems. As a proof of principle, we applied this method to describe the nuclear binding energies and charge radii of light and medium mass nuclei. Our approach identified simple analytical relationships based on the number of protons and neutrons, providing interpretable models with precision comparable to state-of-the-art nuclear models. Additionally, we integrated this ML-discovered model with an existing complementary model to estimate the limits of nuclear stability. These results highlight the potential of symbolic ML to develop accurate nuclear models and guide our description of complex many-body problems.

Nuclear structure↗
DOE OSTI2025

Advancing the Representation of Human Actions in Large‐Scale Hydrological Models: Challenges and Future Research Directions

Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.

catchment hydrology↗