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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Interplay between Mixed and Pure Exciton States Controls Singlet Fission in Rubrene Single Crystals

Singlet fission (SF) is a multielectron process in which one singlet exciton S converts into a pair of separated triplet excitons T. SF is widely studied as it may help overcome the Shockley−Queisser efficiency limit for semiconductor photovoltaic cells. To elucidate and control the SF mechanism, great attention has been given to the identification of intermediate states in SF materials, which often appear elusive due to the complexity and fast time scales of the SF process. Here, we apply 14 fs-1 ms transient absorption techniques to high-purity rubrene single crystals to disentangle the intrinsic fission dynamics from the effects of defects and grain boundaries and to identify reliably the fission intermediates. Our data demonstrates that above-gap excitation directly generates a hybrid vibronically assisted mixture of singlet state and triplet-pair multiexciton [S/TT], which rapidly (<100 fs) and coherently branches into pure singlet or triplet excitations. The relaxation of [S/TT] to S is followed by a relatively slow and temperature-activated (48 meV activation energy) incoherent fission process. The SF competing pathways and intermediates revealed here unify the observations and models presented in previous studies of SF in rubrene and offer alternative strategies for the development of SF-enhanced photovoltaic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Lightweight jet reconstruction and identification as an object detection task

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN large hadron collider (LHC). Collision events produced at the LHC and represented as an image composed of calorimeter and tracker cells are given as an input to a Single Shot Detection network. The algorithm, named PFJet-SSD performs simultaneous localization, classification and regression tasks to cluster jets and reconstruct their features. This all-in-one single feed-forward pass gives advantages in terms of execution time and an improved accuracy w.r.t. traditional rule-based methods. A further gain is obtained from network slimming, homogeneous quantization, and optimized runtime for meeting memory and latency constraints of a typical real-time processing environment. We experiment with 8-bit and ternary quantization, benchmarking their accuracy and inference latency against a single-precision floating-point. We show that the ternary network closely matches the performance of its full-precision equivalent and outperforms the state-of-the-art rule-based algorithm. Finally, we report the inference latency on different hardware platforms and discuss future applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.

Kulkarni, Shruti↗
DOE OSTI2023

Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation

This paper introduces a Generative Adversarial Nets (GAN) based, Load Profile Inpainting Network (Load-PIN) for restoring missing load data segments and estimating the baseline for a demand response event. The inputs are time series load data before and after the inpainting period together with explanatory variables (e.g., weather data). Here, we propose a Generator structure consisting of a coarse network and a fine-tuning network. The coarse network provides an initial estimation of the data segment in the inpainting period. The fine-tuning network consists of self-attention blocks and gated convolution layers for adjusting the initial estimations. Loss functions are specially designed for the fine-tuning and the discriminator networks to enhance both the point-to-point accuracy and realisticness of the results. We test the Load-PIN on three real-world data sets for two applications: patching missing data and deriving baselines of conservation voltage reduction (CVR) events. We benchmark the performance of Load-PIN with five existing deep-learning methods. Our simulation results show that, compared with the state-of-the-art methods, Load-PIN can handle varying-length missing data events and achieve 15-30% accuracy improvement.

14 SOLAR ENERGY↗
DOE OSTI2021

pnnl/SLiCE

Subgraph Based Learning of Contextual Embedding a framework bridging static representation learning methods using global information from the entire graph with localized attention driven mechanisms to learn contextual node representations.

Ham, Colby↗
DOE OSTI2025

Review of Layered Transition Metal Oxide Materials for Cathodes in Sodium-Ion Batteries

The growing interest in sodium-ion batteries (SIBs) is driven by scarcity and the rising costs of lithium, coupled with the urgent need for scalable and sustainable energy storage solutions. Among various cathode materials, layered transition metal oxides have emerged as promising candidates due to their structural similarity to lithium-ion battery (LIB) counterparts and their potential to deliver high energy density at reduced costs. However, significant challenges remain, including limited capacity at high charge/discharge rates and structural instability during extended cycling. Addressing these issues is critical for advancing SIB technology toward industrial applications, particularly for large-scale energy storage systems. This review provides a comprehensive analysis of layered sodium transition metal oxides, focusing on their structural properties, electrochemical performance, and degradation mechanisms. Special attention is given to the intrinsic and extrinsic factors contributing to their instability, such as structural phase transitions, and cationic/anionic redox behavior. Additionally, recent advancements in material design strategies, including doping, surface modifications, and composite formation, are discussed to highlight the progress toward enhancing the stability and performance of these materials. This work aims to bridge the knowledge gaps and inspire further innovations in the development of high-performance cathodes for sodium-ion batteries.

Ahangari, Mehdi (ORCID:0000000345803969)↗
NASA NTRS1991

Precautions toward XTEM of Si3N4/SiO2

Severe difficulties are encountered in the preparation of oxidized Si3N4 specimens for XTEM transmission electromicroscopic inspection, in virtue of the extreme difference between Si3N4 and SiO2 mechanical properties. Attention is presently given to a preparation method in which an overlayer of the nitride is always occluded; this protects the oxide through most of the thinning that specimen preparation entails. An XTEM image of the oxide/nitride interface is presented.

Ogbuji, Linus U. J. T.↗
DOE OSTI2026

LAF-Net: A Deep Residual and Cross-Attention Framework for Day-Ahead Load Forecasting: Preprint

Accurate day-ahead load forecasting is essential for reliable power system operations and market efficiency. System operators such as the Midcontinent Independent System Operator (MISO) rely on forecasts from multiple vendors, yet combining them effectively remains a persistent challenge due to vendor-specific biases. This paper presents a novel LSTM-Attention Fusion Network with Error Representation (LAF-Net) that enhances day-ahead hourly load forecasting through deep residual learning and multi-modal cross-attention. The proposed model builds a historical error memory from past vendor performance and dynamically queries it with future hour context to generate adaptive, hour-specific trust weights for each vendor. A bounded residual correction further refines forecasts by mitigating systematic and temporally localized errors. Tested on real MISO LBA data with multi-vendor forecasts, LAF-Net consistently outperforms the best vendor baseline across all 38 LBAs, achieving more than a 40% reduction in system-level mean absolute error (MAE) during peak load hours relative to the best vendor baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

Attention in aviation

The relevance of four principles or mechanisms of human attention to the design of aviation systems and the performance of pilots in multitask environments, including workload prediction and measurement, control-display integration, and the use of voice and head-up displays is discussed. The principles are: the mental energy that supplies task performance (resources), the resulting cross-talk between tasks as they are made more similar (confusion), the combination of different task elements (integration), and the way in which one task is processed and another is ignored (selection or tunneling). The introduction of greater levels of complexity into the validation of attentional theories in order to approach the demands of the cockpit or ATC console is proposed.

Wickens, Christopher D.↗
DOE OSTI2026

Attention-based explainability for structure–property relationships

Machine learning methods are emerging as a universal paradigm for constructing correlative structure–property relationships in materials science based on multimodal characterization. However, this necessitates the development of methods for the physical interpretability of the resulting correlative models. Here, we demonstrate the potential of attention-based neural networks for revealing structure–property relationships and the underlying physical mechanisms, using the ferroelectric properties of PbTiO3 thin films as a case study. Through the analysis of attention scores, we disentangle the influence of distinct domain patterns on the polarization switching process. The attention-based Transformer model is explored both as a direct interpretability tool and as a surrogate for explaining representations learned via unsupervised machine learning, enabling the identification of physically grounded correlations. We compare attention-derived interpretability scores with classical SHapley Additive exPlanations analysis and show that, in contrast to applications in natural language processing, attention mechanisms in materials science exhibit high efficiency in highlighting meaningful structural features.

Slautin, Boris [Independent Researcher]↗
NASA NTRS1976

Hot environment effects on alloy mechanical properties

Prolonged high temperature performance of structural alloys requires joint attention to both corrosion and mechanical properties, and to their possible interactions. In this interpretive review paper, we provide a systematic compaction of theories and key observations on corrosion-mechanical properties interactions, from early single crystal work in the 1930s to recent studies on superalloys in nonoxidizing, oxidizing and hot corrosive environments. Particular attention is paid to environmental effects on creep, stress rupture and fatigue properties.

Davidson, J. M.↗
DOE OSTI2020

Thermal characterization of the build chamber in electron beam melting

Electron beam powder bed fusion, commonly termed electron beam melting (EBM), offers great versatility in multiple-part processes and can produce high quality as-built components due to low residual stresses. The EBM process is complex and requires careful thermal management, including uniform and consistent preheating of the powder bed, in order to ensure quality and consistency of the product. However, most of the simulations in the literature focus on the selective melting stage of the process. As of today, optimal conditions for initial pre-heating temperatures are only available for specific materials. Thus, in order to extend the EBM technology to other desired build materials, a much better understanding of the pre-heating stages is required. In this work, numerical and experimental approaches are combined in order to investigate the effects and sensitivities of heat removal from the build plate during EBM pre-heating stages. For this purpose, a carefully reconstructed numerical model of the build chamber of an ARCAM Q20 + machine is developed. It includes all main parts of the chamber and all relevant heat transfer mechanisms, whereas special attention is paid to radiation heat exchange between various bodies. In order to validate the model, dedicated experiments are performed, in which a system of thermocouples is installed in the build chamber, allowing direct measurement of the local temperatures of the start-plate and heat shields. A good agreement between the simulation and experimental findings is achieved, leading to a better understanding of the thermal processes characteristic to the pre-heating stages. This basic analysis is followed by a representative pre-heating case, where a powder bed is also considered. The energy required to obtain the desired pre-heating temperatures is evaluated, and the role of the powder bed in heat transfer within the chamber is assessed. The pre-heating stage, simulated in the present work, is supposed to create proper conditions for sintering and consequent melting of the powder, which are highly dependent on the local temperatures and heat transfer features. Thus, the findings of the reported work present a step towards a better understanding of the thermal processes that characterize EBM. The reported model can be further used to provide realistic boundary condition inputs for other meso- or macro-scale models as a function of time and geometry. The model can serve also for verification of machine settings, i.e., jump-safe and melt-safe ones which actually provide desired preheat, and for development of settings for new powders.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Heat pipe stability. 1: A preliminary investigation into thermally assisted cavitation

The notion is introduced of thermally assisted cavitation by localized fluctuations in capillary forces. Because cavitation in liquids can be closely approximated by an isothermal process, only momentum and mass balances are used to introduce the notion for liquids under mechanical tension. Brief attention is given to developing a stability theory in terms of the stiffness and compliance coefficients for a working fluid. Interestingly, the particular thermodynamic approach taken can be used to suggest experiments relating working fluid performance to meniscus behavior. A correction to the liquid flow equation is suggested.

Source record↗
NASA NTRS1973

Diffuse X and gamma radiation.

The most reliable measurements in the energy range from 0.1 MeV to 100 MeV are presented in graphs. Studies in the region from 1 keV to 100 keV are discussed, giving attention to nonthermal mechanisms, thermal emission from a uniform intergalactic medium, the contribution of discrete extragalactic sources to the isotropic X-ray background, discrete diffuse X-ray sources in galaxy clusters, the contribution of galaxy clusters to the isotropic X-ray background, and fluctuations in the X-ray background. Diffuse X rays below 1 keV are also considered together with diffuse galactic X and gamma rays above 1 keV and the significance of diffuse X and gamma radiation for astronomy.

Silk, J.↗
NASA NTRS1973

Introduction to gasdynamics of explosions

Questions concerning the genesis and sustenance of an explosion are investigated, giving attention to the mechanics of explosions, the gasdynamics of explosions, aspects of technological significance, and future prospects. The dynamics of exothermic processes is discussed together with the most prominent effects of explosions. Blast waves are considered, taking into account conservation principles, blast wave transformation, conservative equations in nondimensional form, the equation of state, Eulerian space profiles, Eulerian time profiles, Lagrangian time profiles, boundary conditions and integral relations, and self-similar flow fields.

Oppenheim, A. K.↗
NASA NTRS1981

Interpretations and implications of gamma-ray lines from solar flares, the galactic centre and gamma-ray transients

Gamma-ray line emission from the Sun results from the nuclear interactions of energetic protons and nuclei with the solar atmosphere. These interactions produce gamma-ray lines from neutron capture, positron annihilation, and nuclear deexcitation. Observation of such gamma-rays can provide unique information on high energy processes at the Sun. Details of solar gamma-ray spectroscopy are discussed along with the galactic center 0.511 MeV line. The richness of astronomy at 0.511 MeV is indicated by the great variety of astrophysical positron production mechanisms and by the many astrophysical sites where such mechanisms could operate. Attention is also given to lines from gamma-ray transients, and the prospects for gamma-ray line detections, taking into account gamma-ray lines from processes of nucleosynthesis and lines from low-energy cosmic ray interactions.

Ramaty, R.↗
NASA NTRS1985

Plasma waves and instabilities

An account is given of the waves and instabilities occurring at collisionless shocks, with attention to the mechanisms responsible for the generation of these waves. The transition region of the shock usually involves an abrupt broadband burst of electrostatic noise that extends from below the lower hybrid resonance to near the electron plasma frequency, and by a broadband burst of whistler mode EM noise below the electron cyclotron frequency. Electrostatic lower hybrid waves are also noted. Upstream of the shock, electron plasma oscillations, ion acoustic waves, and intense ULF MHD waves are often observed. The region downstream of the shock is usually very chaotic; electrostatic waves often extend long distances into the downstream region, together with whistler mode emissions.

Gurnett, Donald A.↗