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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The End of Galaxy Surveys

For nearly a century, imaging and spectroscopic surveys of galaxies have given us information about the contents of the universe. We attempt to define the logical end point of such surveys by defining not the next galaxy survey but rather the final galaxy survey at near-infrared wavelengths; this would be the galaxy survey that exhausts the information content useful for addressing extant questions. Such a survey would require incredible advances in a number of technologies, and the survey details will depend on the as yet poorly constrained properties of the earliest galaxies. Using an exposure time calculator, we define nominal surveys for extracting the useful information for three science cases: dark energy cosmology, galaxy evolution, and supernovae (SN). We define scaling relations that trade off sky background, telescope aperture, and focal plane size to allow for a survey of a given depth over a given area. For optimistic assumptions, a 280 m telescope with a marginally resolved focal plane of 20 deg 2 operating at L2 could potentially exhaust the cosmological information content of galaxies in a 10 yr survey. For galaxy evolution (making use of gravitational lensing to magnify the earliest galaxies) and SN, the same telescope would suffice. We discuss the technological advances needed to complete the last galaxy survey. While the final galaxy survey remains well outside of our technical reach today, we present scaling relations that show how we can progress toward the goal of exhausting the information content encoded in the shapes, positions, and colors of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

GenASiS Mathematics: Object-oriented manifolds, operations, and solvers for large-scale physics simulations (version 2)

We report GenASiS Mathematics provides modern Fortran classes furnishing extensible object-oriented functionality for the solution of fields governed by selected partial differential equations. The initial release included extensible object-oriented implementations of simple meshes and the evolution of generic conserved currents thereon. This revision - Version 2 of Mathematics - includes significant reorganization and streamlining of these classes, higher-order reconstruction by a different method, a Poisson solver, coarsening to avoid Courant time step limitations near coordinate singularities, and the offloading of computational kernels to GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Numerical heating in particle-in-cell simulations with Monte Carlo binary collisions

The binary Monte Carlo (MC) collision algorithm is a standard and robust method to include binary Coulomb collision effects in particle-in-cell (PIC) simulations of plasmas. Here we show that the coupling between PIC and MC algorithms can give rise to (nonphysical) numerical heating of the system that significantly exceeds that observed when these algorithms operate independently. We argue that this deleterious effect results from an inconsistency between the particle motion associated with MC collisions and the work performed by the collective electromagnetic field on the PIC grid. This inconsistency manifests as the (artificial) stochastic production of electromagnetic energy, which ultimately heats the plasma particles. Here, the MC-induced numerical heating can significantly impact the evolution of the simulated system for long simulation times (≳10 3 collision periods, for typical numerical parameters). We describe the source of the MC-induced numerical heating analytically and discuss strategies to minimize it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Forecasting the Decay of Hybrid Perovskite Performance Using Optical Transmittance or Reflected Dark-Field Imaging

The practicality and economic viability of hybrid perovskite solar cells hinge on their operational lifetime, and methods for forecasting the performance of perovskites under different operational stresses are urgently needed. Here, we explore the evolution of material-level optoelectronic properties as MAPbI 3 degrades and discover universal behaviors where the carrier diffusion length (L D ) decays before quasi-Fermi-level splitting (ΔE F ), regardless of the specific stress protocol (oxygen, humidity, thermal stress, or a combination). We employ a machine learning greedy feature selection model that uses initially measured properties to predict the time it takes L D to decrease to 85% of its initial value with a prediction accuracy of 12.8%. This model reveals a strong correlation between the initial rate of transmittance change and the time until loss of transport. We translate this material-level finding to photovoltaic device-level forecasting by demonstrating that the rate of change of transmittance is equivalent to the rate of change of the spatial standard deviation of dark-field image intensity (i.e., scattered light intensity) collected in reflection mode (and thus applicable to devices with opaque contacts). Furthermore, this work demonstrates that transmittance and scattering methods are highly effective for accelerated material (and device) stability evaluation and forecasting.

14 SOLAR ENERGY↗
DOE OSTI2026

Supramolecular Metal‐Organic Framework Electrocatalysts With Hydration‐Adaptive Gallery Expansion and Linker‐Mediated Distal Ni‐Co Cooperation Enable Framework‐Retentive Oxygen Evolution

Atomic‑level tailoring of electronic communication between spatially separated metal sites offers a route to accelerate multielectron electrocatalysis. We report Ni-TPTC, Co-TPTC, and heterobimetallic Ni-Co-TPTC supramolecular metal-organic frameworks (SMOFs) for the oxygen evolution reaction (OER) built from a terphenyl‑tetracarboxylate (TPTC) linker. Single-crystal X-ray diffraction of heterobimetallic Ni–Co–TPTC reveals trans-bis-aqua octahedral chains assembled into a π-stacked, hydrogen-bonded lattice and confirms retention of the parent architecture, while powder X-ray diffraction supports an isostructural Co analog. In 1.0 M KOH, Ni-Co-TPTC reaches 20 mA cm −2 at 350 mV and maintains operation at ∼60 mA cm −2 for 45 h with modest decay of the initial current. Time‑dependent ex situ diffraction shows dominant framework reflections with low‑angle shifts consistent with gallery dilation (d‑spacing ∼7.7 → ∼9.2 Å) during early operation, while Co K‑edge X‑ray absorption and microscopy reveal Co‑rich oxide/oxyhydroxide‑like domains at longer times that correlate with decay. X‑ray photoelectron spectroscopy, quantified by the Remote Binding‑Energy Differential, tracks composition‑dependent Ni-Co polarization, and DFT free‑energy analysis suggests that a model Ni-Co environment lowers the Co‑centered potential‑limiting step by ∼0.24 eV relative to the Co‑only framework. Furthermore, these results suggest that framework‑retentive expansion and distal Ni-Co coupling can drive OER activity before gradual deligation and oxide formation mark longer‑time degradation.

Supramolecular metal-organic frameworks (SMOFs)↗
DOE OSTI2024

Autoencoder-Based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter

The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Gate-Based Quantum Simulation of Gaussian Bosonic Circuits on Exponentially Many Modes

We introduce a framework for simulating, on an ( n + 1 )-qubit quantum computer, the action of a Gaussian bosonic (GB) circuit on a state over 2 n modes. Specifically, we encode the initial bosonic state’s expectation values over quadrature operators (and their covariance matrix) as an input qubit state. This is then evolved by a quantum circuit that effectively implements the symplectic propagators induced by the GB gates. We find families of GB circuits and initial states leading to efficient quantum simulations. For this purpose, we introduce a dictionary that maps between GB and qubit gates such that particle- (non-particle-) preserving GB gates lead to real- (imaginary-) time evolutions at the qubit level. For the special case of particle-preserving circuits, we present a bounded-error-quantum-polynomial time (BQP)-complete GB decision problem, indicating that GB evolutions of Gaussian states on exponentially many modes are as powerful as universal quantum computers. We also perform numerical simulations of an interferometer on ∼ 8 × 10 9 modes, illustrating the power of our framework. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Evolution of Intent and Social Influence Networks and Their Significance in Detecting COVID-19 Disinformation Actors on Social Media

Online disinformation actors are those individuals or bots who disseminate false or misleading information over social media, with the intent to sway public opinion in the information domain towards harmful social outcomes. Quantification of the degree to which users post or respond intentionally versus under social influence, remains a challenge, as individuals or organizations operating the profile are foreshadowed by their online persona. However, social influence has been shown to be measurable in the paradigm of information theory. In this paper, we introduce an information theoretic measure to quantify social media user intent, and then investigate the corroboration of intent with evolution of the social network and detection of disinformation actors related to COVID-19 discussions on Twitter. Our measurement of user intent utilizes an existing time series analysis technique for estimation of social influence using transfer entropy among the considered users. We have analyzed 4.7 million tweets originating from several countries of interest, during a 5 month period when the arrival of the first dose of COVID vaccinations were announced. Our key findings include evidence that: (i) a significant correspondence between intent and social influence; (ii) ranking over users by intent and social influence is unstable over time with evidence of shifts in the hierarchical structure; and (iii) both user intent and social influence are important when distinguishing disinformation actors from non-disinformation actors.

Gunaratne, Chathika↗
DOE OSTI2019

Insights into operational stability and processing of halide perovskite active layers

Rapid improvement of the stability of metal halide perovskite materials is required to enable their adoption for energy production at Terawatt scale. To understand the role of the active layer stability in these devices we use operando x-ray diffraction to observe the evolution in structural stability across APbI3 alloys where A is a combination of formamidinium, Cs, and/or methylammonium. During device operation we observe spatial de-alloying and phase segregation into the alloy’s constituent phases. Using complementary first-principles calculations of halide perovskite alloys a hypothesized framework explaining the experimentally observed mixing and demixing of these systems is presented and then validated using in-situ X-ray diffraction and time of flight secondary ion mass spectrometry. Taken together these results indicate that stability is not only a function of device architecture or chemical formulation, but that the processing strategy is critically important in synthesizing the most energetically favorable state and therefore the most stable device systems. This study reconciles disparate reports within the literature and also highlights the limitations of shelf life studies to ascertain stability as well as the importance of testing devices under operational conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Universal time scalings of sensitivity in Markovian quantum metrology

Assuming Markovian time evolution of a quantum sensing system, we study the general characterization of the optimal sensitivity scalings with time, under most general quantum control protocols. We allow the estimated parameter to influence both the Hamiltonian as well as the dissipative part of the quantum master equation and focus on the asymptotic-time along with the short-time sensitivity scalings. We find that via simple algebraic conditions (in terms of the Hamiltonian, the jump operators as well as their parameter derivatives), one can characterize the four classes of metrological models that represent: quadratic-linear, quadratic-quadratic, linear-linear, and linear-quadratic time scalings. We also investigate the relevant time scales on which the transition between the two regimes appears. Additionally, we provide universal numerical methods to obtain quantitative bounds on sensitivity that are the tightest that exist in the literature. Simplicity and universality of our results make it suitable for diverse applications in quantum metrology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Modeling of flash sintering of ionic ceramics

A fundamental understanding of the influence of defects in ionic ceramics at the atomic, microstructural, and macroscopic levels, before, during, and after the flash sintering event is key to the development of ceramic processing operations that lead to fast, low cost, and environmentally safe fabrication of materials. The observed phenomenology of the flash process encompasses multiple time and length scales and have resulted on a wide variety of what sometimes appears to be contradictory explanations. Here, this article summarizes the latest developments on the modeling and simulation of flash sintering, specifically those related to the understanding of the equilibrium and kinetic properties and the corresponding microstructural evolution of ionic ceramics. Challenges and opportunities in the development of theoretical analyses that include unidentified multiphysical effects are discussed, as they pertain to the processing of technologically relevant ceramic materials for advanced structures and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unraveling nonperturbative QCD with transverse momentum hadronic structures

The main purpose of this thesis is to investigate the theoretical foundations of the factorization theorems that involve transverse quark and gluon momentum distributions, and to better understand the interface between foundational questions and phenomenological applications. Many of these applications involve using transverse parton momentum dependent (TMD) correlation functions as tools for probing the complex nonperturbative structures of the hadrons. We first introduce the concepts of collinear and TMD factorization in a toy-model theory and, by leveraging the comparative simplicity of such a model, we test the range of validity and limitations of the factorization approach. At the same time, we introduce the conventional approaches that are adopted for the phenomenological extractions of the TMD distributions, and catalog the advantages and disadvantages. Following the general theoretical framework of factorization, we then develop a different approach to TMD phenomenology that is able to systematically integrate the perturbative and non perturbative information in parametrizations of TMD distributions, while being completely consistent with their operator definitions and the predictions of QCD, including their nontrivial evolution. The name Hadron Structure Oriented approach, or HSO, is coined in order to emphasize the central role of the nonperturbative nature of QCD and its relation to the partonic structure of hadrons. Finally, we provide a first phenomenological implementation of the HSO approach by extracting TMD distributions relying on low-to-moderate energy Drell-Yan data. The quality and robustness of the results are then compared against higher energy processes like high-Q2 Z0 boson production. Our analysis demonstrates the feasibility of this novel approach and points the way toward the improvements it can achieve in future applications.

Rainaldi, Tommaso [Old Dominion Univ., Norfolk, VA↗
DOE OSTI2021

Real Time Observation of Lithium Insertion into Pre-Cycled Conversion-Type Materials

Conversion-type electrode materials for lithium-ion batteries experience significant structural changes during the first discharge–charge cycle, where a single particle is taken apart into a number of nanoparticles. This structural evolution may affect the following lithium insertion reactions; however, how lithiation occurs in pre-cycled electrode materials is elusive. In this work, in situ transmission electron microscopy was employed to see the lithium-induced structural and chemical evolutions in pre-cycled nickel oxide as a model system. The introduction of lithium ions induced the evolution of metallic nickel, with volume expansion as a result of a conversion reaction. After pre-cycling, the phase evolutions occurred in two separate areas almost at the same time. This is different from the first lithiation, where the phase change takes place successively, with a boundary dividing the reacted and unreacted areas. Structural changes were restricted at the areas having large amount of fluorine, implying the residuals from the decomposition of electrolytes may have hindered the electrochemical reactions. This work provides insights into phase and chemical evolutions in pre-cycled conversion-type materials, which govern electrochemical properties during operation.

25 ENERGY STORAGE↗
DOE OSTI2025

Voltage Probability Density Function Shaping Control Strategy Considering Grid Operational Uncertainties

It is well-known that power systems operation always affected by various uncertainties which make the bus voltage a random process that can be characterized by its probability density function (PDF) at any time instant. In this context, this paper presents a novel PDF-based voltage control framework for power systems. By modeling voltage as a stochastic process, we formulate a stochastic differential equationthat captures grid uncertainties. The associated Fokker-Planck-Kolmogorov equation is derived to describe the evolution of the voltage PDF, which enables the formulation of a PDF-shaping control strategy. To simplify the PDF control formulation, a B-spline neural network is introduced for real-time estimation and regulation of the voltage distribution. The proposed PDF control law updates voltage references for energy storage systems and synchronous generators using real-time PDF measurements and feedback signals. The proposed method is validated on a modified Kundur’s two-area system. Simulation results demonstrate that the controller can significantly improve the voltage stability under stochastic conditions, highlighting its effectiveness in modern inverter-rich grids.

Gui, Yonghao [ORNL] (ORCID:0000000250435534)↗
DOE OSTI2026

Three-dimensional simulation of the University of Hawai‘i FEL oscillator with cavity desynchronization

In this paper, we present three-dimensional, time-dependent simulations of the University of Hawai‘i (UH) at Mānoa free-electron laser (FEL) oscillator. Using beam parameters from the UH facility, we study the pass-by-pass evolution of the radiation field, including its temporal, spectral, and transverse properties. At nominal bunch length, the radiation pulse develops temporal spiking near saturation, together with sideband formation and increased sensitivity to machine timing jitter. Our results show that modest cavity desynchronization can enhance the radiation energy by 63%. Large cavity desynchronization, on the other hand, can effectively suppress the spiking instabilities and improve robustness to timing fluctuations. Finally, we simulate a short-bunch operational mode with a bunch length comparable to the slippage length, which accelerates saturation and further amplifies the FEL power. Overall, these results provide a quantitative foundation for pulse control studies in the UH FEL oscillator and a critical benchmark for future experimental validation and machine optimization.

free-electron lasers↗
DOE OSTI2026

Uncertainty guided online ensemble for non-stationary data streams in fusion science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior with distribution drifts, resulted by both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with such non-stationary data streams. Online learning techniques have been leveraged in other domains, however it has been largely unexplored for fusion applications. In this paper, we investigate online learning for continuous adaptation to drifting data streams in the prediction of Toroidal Field (TF) coils deflection at the DIII-D fusion facility. We further address the short-term performance degradation inherent to standard online learning, which arises because ground truth is unavailable at prediction time. To mitigate this issue, we propose an uncertainty-guided online ensemble framework. The method leverages the Deep Gaussian Process Approximation (DGPA) for calibrated uncertainty estimation and uses these uncertainty measures to guide a meta-algorithm that aggregates predictions from learners trained over different historical horizons. Our results show that online learning reduces prediction error by 80% compared to a static model. The online ensemble and the proposed uncertainty-guided ensemble further reduce error by approximately 6%, and 10% respectively, relative to standard single-model online learning, while also providing calibrated uncertainty estimates to support operational decision-making.

AI↗
DOE OSTI2017

The Apache Point Observatory Galactic Evolution Experiment (APOGEE)

The Apache Point Observatory Galactic Evolution Experiment (APOGEE), one of the programs in the Sloan Digital Sky Survey III (SDSS-III), has now completed its systematic, homogeneous spectroscopic survey sampling all major populations of the Milky Way. After a three-year observing campaign on the Sloan 2.5 m Telescope, APOGEE has collected a half million high-resolution ( R ∼ 22,500), high signal-to-noise ratio (>100), infrared (1.51–1.70 μ m) spectra for 146,000 stars, with time series information via repeat visits to most of these stars. This paper describes the motivations for the survey and its overall design—hardware, field placement, target selection, operations—and gives an overview of these aspects as well as the data reduction, analysis, and products. An index is also given to the complement of technical papers that describe various critical survey components in detail. Finally, we discuss the achieved survey performance and illustrate the variety of potential uses of the data products by way of a number of science demonstrations, which span from time series analysis of stellar spectral variations and radial velocity variations from stellar companions, to spatial maps of kinematics, metallicity, and abundance patterns across the Galaxy and as a function of age, to new views of the interstellar medium, the chemistry of star clusters, and the discovery of rare stellar species. As part of SDSS-III Data Release 12 and later releases, all of the APOGEE data products are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dislocation-Activated Low Platinum-Loaded PtCu Nanoparticles Welded onto the Substrate for Practical Acidic Hydrogen Generation

Although transition metal (M) alloying with platinum (Pt) is a promising approach to reduce the Pt dosage required in the hydrogen evolution reaction (HER), the catalytic activity and durability of PtM alloy are often unsatisfactory for acidic HER, especially at high currents, due to a reduced number of highly active sites (Pt) at the atomic level and challenges in stabilizing them to prevent detachment and aggregation. Herein, we report a robust functional structure integrated electrode (D-PtCu/CF) with abundant edge dislocations and very low platinum content (0.1 mg cm -2 ) to achieve high activity and stability in acidic HER within a proton exchange membrane water electrolysis cell (PEMWE). D-PtCu/CF exhibits high Pt mass activity (10.28 A mg Pt -1 ) and excellent operational stability (negligible decay after 200 h). X-ray absorption spectroscopy and in situ electrochemical experiments reveal that the lattice distortion caused by edge dislocations in PtCu mainly affects Pt atoms by compressing strain, reducing their ability to adsorb H. At the same time, Cu atoms are subjected to tensile strain, enhancing the bonding between Cu and H. Therefore, edge dislocations not only improve the intrinsic catalytic activity of Pt atoms but also increase the number of active sites (Cu) available for hydrogen adsorption, which synergistically accelerates the kinetics of the HER reaction. Finally, the PEMWE employing the D-PtCu/CF catalytic electrode can operate stably for 100 h at an industrial-level current density of 500 mA cm -2 with 1.63 V.

30 DIRECT ENERGY CONVERSION↗