Search NASA⌕ Search

SEARCH · Search NASA

Results for “electrical and electronic engineering”

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.

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

3,234 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Coordinated Natural Gas and Electric Planning: Case Studies of Current Approaches and Practices

This paper examines how natural gas and electric utilities across eight U.S. states and two Canadian provinces are beginning to coordinate historically separate planning processes in response to growing system interdependencies, policy mandates, aging infrastructure, and changing customer energy choices. Electricity planning has long relied on robust integrated resource planning frameworks that weigh numerous objectives, risks, and costs. Natural gas planning, on the other hand, is typically less transparent and more narrowly focused on safety and system integrity. As economic, reliability, and policy drivers place new and shared demands on both systems, jurisdictions and utilities are experimenting with approaches such as coordinated forecasting, non pipeline alternatives, and combined planning pilots. A few have issued regulatory or statutory directives for greater data sharing and methodological alignment. Case studies from British Columbia, California, Colorado, Illinois, Massachusetts, Minnesota, New York, Québec, Rhode Island, and Washington illustrate a wide range of approaches to rethinking siloed planning. The paper identifies several common themes across the jurisdictions examined. It provides observations on the methods, processes, and organizational steps that may be needed in the future to address the challenges being faced by states and utilities. Lastly, it identifies some initial steps that states and utilities can consider if they would like to pursue more integrated, cost-effective, policy-aligned energy system planning.

03 NATURAL GAS↗
DOE OSTI2026

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi↗
DOE OSTI2026

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2016

International Space Station Lithium-Ion Battery

The International Space Station (ISS) Electric Power System (EPS) currently uses Nickel-Hydrogen (Ni-H2) batteries to store electrical energy. The batteries are charged during insolation and discharged during eclipse. The Ni-H2 batteries are designed to operate at a 35 depth of discharge (DOD) maximum during normal operation in a Low Earth Orbit. Since the oldest of the 48 Ni-H2 battery Orbital Replacement Units (ORUs) has been cycling since September 2006, these batteries are now approaching their end of useful life. In 2010, the ISS Program began the development of Lithium-Ion (Li-ion) batteries to replace the Ni-H2 batteries and concurrently funded a Li-ion cell life testing project. This paper will include an overview of the ISS Li-Ion battery system architecture and the progress of the Li-ion battery design and development.

Battery↗
DOE OSTI2026

CO2 Handling & Electrolyzer Efficiency Scaling Evaluator

CHEESE is an interactive dashboard tool for estimating the performance and material requirements of carbon dioxide electrolysis systems. It helps users evaluate how electrode area, current density, product selectivity, gas flow, cell voltage, and the number of cells in a stack affect system operation. The dashboard provides simple and advanced modes so it can be used for both quick estimates and more detailed engineering analysis. Users can estimate product output, carbon dioxide use, electrical power, electrode area, gas and liquid flow rates, energy efficiency, material cost per test, and the effect of scaling from a single cell to a multi cell stack. It also includes tools for examining carbon balance, equipment durability, component replacement, and changes in performance over time. This is intended to help both academia and industry researchers who are either getting into CO2 electrolysis on lab-scale or are trying to establish a larger footprint. CHEESE presents results through tables, charts, and simplified cell and stack diagrams. It is intended to support research planning, experimental design, comparison of operating conditions, and early stage scale up studies.

Prajapati, Aditya [Lawrence Livermore National Lab↗
NASA NTRSDate not supplied

Conclusions of a Cryogenic Motor Configuration Study for Aircraft Propulsion

Cryogenic electric machines are a promising technology for multi megawatt electric aircraft drivetrains. Superconducting stators that make use of low AC loss superconducting wires are considered to be a key component for these cryogenic machines. This paper shares the lessons learned from a design study that evaluated several configurations of a 5 MW cryogenic motor for this application. The lessons are drawn from a qualitative study of 16 configurations and a quantitative study of 8 down selected configurations. The quantitative study involved using analytical calculations (electromagnetic, thermofluid, mechanical, and motor sizing) to determine each configuration’s Pareto front of total efficiency and total specific power. The conclusions from a preliminary assessment of different stator conductors (superconductors and cryogenic metals) are also presented. One motor configuration is down selected for future detailed design and demonstration at the multi megawatt level.

Electrified aircraft propulsion↗
DOE OSTI2024

From wide to ultrawide-bandgap semiconductors for high power and high frequency electronic devices

Abstract Wide and ultrawide-bandgap (U/WBG) materials have garnered significant attention within the semiconductor device community due to their potential to enhance device performance through their substantial bandgap properties. These exceptional material characteristics can enable more robust and efficient devices, particularly in scenarios involving high power, high frequency, and extreme environmental conditions. Despite the promising outlook, the physics of UWBG materials remains inadequately understood, leading to a notable gap between theoretical predictions and experimental device behavior. To address this knowledge gap and pinpoint areas where further research can have the most significant impact, this review provides an overview of the progress and limitations in U/WBG materials. The review commences by discussing Gallium Nitride, a more mature WBG material that serves as a foundation for establishing fundamental concepts and addressing associated challenges. Subsequently, the focus shifts to the examination of various UWBG materials, including AlGaN/AlN, Diamond, and Ga 2 O 3 . For each of these materials, the review delves into their unique properties, growth methods, and current state-of-the-art devices, with a primary emphasis on their applications in power and radio-frequency electronics.

Materials Science↗
NASA NTRS2016

International Space Station Lithium-Ion Battery

The International Space Station (ISS) primary Electric Power System (EPS) currently uses Nickel-Hydrogen (Ni-H2) batteries to store electrical energy. The electricity for the space station is generated by its solar arrays, which charge batteries during insolation for subsequent discharge during eclipse. The Ni-H2 batteries are designed to operate at a 35 depth of discharge (DOD) maximum during normal operation in a Low Earth Orbit. Since the oldest of the 48 Ni-H2 battery Orbital Replacement Units (ORUs) has been cycling since September 2006, these batteries are now approaching their end of useful life. In 2010, the ISS Program began the development of Lithium-Ion (Li-Ion) batteries to replace the Ni-H2 batteries and concurrently funded a Li-Ion ORU and cell life testing project. When deployed, they will be the largest Li-Ion batteries ever utilized for a human-rated spacecraft. This paper will include an overview of the ISS Li-Ion battery system architecture, the Li-Ion battery design and development, controls to limit potential hazards from the batteries, and the status of the Li-Ion cell and ORU life cycle testing.

battery↗
NASA NTRS2017

International Space Station Lithium-Ion Battery Start-Up

International Space Station Lithium-Ion Battery Start-Up.The International Space Station (ISS) primary Electric Power System (EPS) was originally designed to use Nickel-Hydrogen (Ni-H2) batteries to store electrical energy. The electricity for the space station is generated by its solar arrays, which charge batteries during insolation for subsequent discharge during eclipse. The Ni-H2 batteries are designed to operate at a 35 depth of discharge (DOD) maximum during normal operation in a Low Earth Orbit. As the oldest of the 48 Ni-H2 battery Orbital Replacement Units (ORUs) has been cycling since September 2006, these batteries are now approaching their end of useful life. In 2010, the ISS Program began the development of Lithium-Ion (Li-ion) batteries to replace the Ni-H2 batteries and concurrently funded a Li-Ion ORU and cell life testing project. The first set of 6 Li-ion battery replacements were launched in December 2016 and deployed in January 2017. This paper will discuss the Li-ion battery on-orbit start-up and the status of the Li-Ion cell and ORU life cycle testing.

Lithium-Ion↗
NASA NTRS2017

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics↗
DOE OSTI2025

Electronic structure prediction of medium and high entropy alloys across composition space

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries while keeping descriptor-vector size nearly constant as alloy complexity increases. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

materials science↗
DOE OSTI2026

Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen↗
DOE OSTI2026

Quantifying the dislocation content of atomically resolved grain boundary line defects using the Nye tensor

The Nye tensor, which quantifies the density of Burgers vector for a given dislocation line direction, can be effectively used to characterize dislocation content in bulk crystals from atomic-resolution transmission electron microscopy images. The Nye tensor can be calculated from these images, in part because the reference state is simply defined by the lattice of the perfect crystal. The application of the Nye tensor to interfacial line defects, for which the natural reference state is the dichromatic pattern of the two grains in their reference orientation, poses additional challenges. In this work, we present a method that employs the Nye tensor to characterize the edge dislocation content of line defects at grain boundaries from atomic-resolution images. This approach enables us to rapidly characterize all edge dislocation content along a grain boundary. Additionally, the Nye tensor provides information about line defect core structure. Finally, we demonstrate this method on two exemplar defects: a twin boundary disconnection and a facet junction in face-centered cubic Au.

Crystallographic defects↗
DOE OSTI2021

Design and Realization of Ohmic and Schottky Interfaces for Oxide Electronics

Understanding band alignment and charge transfer at complex oxide interfaces is critical to tailoring and utilizing their diverse functionality. Toward this goal, both Ohmic- and Schottky-like charge transfers at oxide/oxide semiconductor/metal interfaces are designed and experimentally validated. A method for predicting band alignment and charge transfer in ABO 3 perovskites is utilized, where previously established rules for simple semiconductors fail. The prototypical systems chosen are the rare class of oxide metals, SrBO 3 with B = V–Ta, when interfaced with the multifaceted semiconducting oxide, SrTiO 3 . For B = Nb and Ta, it is confirmed that a large accumulation of charge occurs in SrTiO 3 due to the higher energy Nb and Ta states relative to Ti. Furthermore, this gives rise to a high mobility metallic interface, which is an ideal epitaxial oxide/oxide Ohmic contact. On the contrary, for B = V, there is no charge transfer into the SrTiO 3 interface, which serves as a highly conductive epitaxial gate metal. Going beyond these specific cases, this work opens the door to integrating the vast phenomena of ABO 3 perovskites into a wide range of practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Direct comparison of gamma, electron beam and X-ray radiation effects on the polymers of a pulsed lavage device

Gamma radiation used for sterilization of medical devices is challenged by cobalt-60 supply and commercial capacity. To maintain a robust radiation sterilization marketplace for the rapidly growing single-use medical device industry, investigation of potential alternatives to gamma technology, such as electron beam (e-beam) and X-ray technology, is critical. In this work, we directly compare the effects of radiation source and absorbed dose level on the polymeric materials and function of a commercial pulsed lavage device used for wound care. Product functionality, polymer mechanical, and polymer optical properties were evaluated using standard methods and input from the device manufacturer. Test results show that functionality of the product was not inhibited by radiation although the battery in the device exposed to X-ray exhibited greater voltage loss compared to batteries in products exposed to gamma or e-beam. Statistically significant differences between gamma and e-beam exposure and between gamma and X-ray exposure were also observed for product appearance in terms of yellowness index of several of the polymers considered. Overall, the results of this study support the viability of e-beam and X-ray radiation technologies as alternatives to cobalt-60 gamma technology for sterilization of the single-use pulsed lavage medical device investigated.

Electron beam↗
NASA NTRS2026

A Modular Conjugate Heat Transfer Optimization Framework for Thermal Management of Electric Aircraft

Conjugate heat transfer (CHT) analysis and optimization is a powerful method for improving thermal management, as it simultaneously resolves the temperature distribution in both fluid and solid domains. This paper presents a modular, discrete adjoint-based CHT optimization capability integrated within the OpenMDAO/MPhys framework. A unique feature of the proposed framework is its flexibility to extend to multidisciplinary optimization, including aero-structural-thermal applications. The fluid domain is modeled using a finite-volume Computational Fluid Dynamics (CFD) solver, and the solid domain with a conduction heat transfer solver. A mixed Neumann-Dirichlet boundary condition is developed to enable full submersion of the solid geometry within the fluid domain, while ensuring consistent temperature and heat flux coupling at the CHT interface. Gradient-based optimization is performed; the gradients are efficiently computed using the discrete adjoint solvers implemented in DAFoam. To demonstrate the method, this paper considers two cases related to electric aircraft thermal management: a U-bend heat exchanger and an actively cooled battery pack. The U-bend case aims to minimize pressure loss while maximizing heat flux by changing the pipe geometry. The optimized design reduces pressure loss by 52.7% and increases total heat flux by 2.3%. In the battery pack case, a 3-by-3 cell configuration is cooled by ambient airflow, with constant heat generation prescribed in the cells. The battery casing shape serves as the design variable, and the objective function is a weighted sum of pressure loss and pack weight, subject to a maximum temperature constraint. The optimized design achieves a 44.6% reduction in pressure loss and a 1.5% reduction in weight, while satisfying the thermal constraint. To ensure the reliability of the optimized designs, this study validates coarse-mesh, steady-state predictions against fine-mesh unsteady simulations, demonstrating consistency within acceptable errors. This work demonstrates the potential of the developed framework to enable rapid, high-fidelity design of thermal management systems for electric aircraft.

heat transfer↗
DOE OSTI2026

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat↗
DOE OSTI2026

Electron-Deficient Phenazines: Synthesis, Structures, Redox, and Optoelectronic Properties in the Gas Phase, in Solution, and in the Solid State

High-temperature gas-phase reactions of 1,4-C4F8I2 with phenazine (PHNZ) afforded new thermally- and air-stable derivatives with cyclo-C4F8 substituents, viz. 1,2-PHNZ(C4F8), 2,3-PHNZ(C4F8), 1,2:6,7-PHNZ(C4F8)2, 1,2:7,8-PHNZ(C4F8)2, and 1,2:8,9-PHNZ(C4F8)2. Reactions in the presence of Cu powder resulted in reductive-defluorination/aromatization of some of the cyclo-C4F8 substituents to produce 2,3-PHNZ(C4F4), 2,3-PHNZ(C4HF3), and 1,2:6,7-PHNZ(C4F8)(C4F4), which are formally tri- or tetrafluoro derivatives of benzo[a]phenazine. Single-crystal X-ray diffraction structures of these compounds demonstrate the planarity of 2,3-PHNZ(C4F4) and 2,3-PHNZ(C4HF3) and ordered p-stacking in 1,2-PHNZ(C4HF3), 1,2-PHNZ(C4F4), 1,2-PHNZ(C4F8), and 2,3-PHNZ(C4F8). Low-temperature gas-phase photoelectron spectra of the PHNZ(C4F8)1,2 compounds show that they are strong electron acceptors, with the three PHNZ(C4F8)2 isomers having electron affinities exceeding that of C60. Cyclic voltammetry in acetonitrile show that the five PHNZ(C4F8)1,2 compounds exhibit reversible one-electron reductions with large positive shifts in their reduction potentials relative to unsubstituted PHNZ. Spectroelectrochemical absorption and EPR spectra of PHNZ(C4F8)1,2- • anion radicals and extensive DFT calculations revealed the significant role that the different substitution patterns have on determining the optoelectronic properties of the PHNZ(C4F8)1,2 derivatives and PHNZ(C4F8)1,2- • anion radicals. Time-resolved microwave conductivity measurements and photoluminescence spectra of blends of the PHNZ(C4F8)1,2 derivatives with the donor poly(3-hexylthiophene) (P3HT) were recorded to assess the possible use of the new compounds in optoelectronic devices.

Balser, Sebastian↗