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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)↗
DOE OSTI2025

Patchy nanoparticles by atomic stencilling

Stencilling, in which patterns are created by painting over masks, has ubiquitous applications in art, architecture and manufacturing. Modern, top-down microfabrication methods have succeeded in reducing mask sizes to under 10 nm, enabling ever smaller microdevices as today’s fastest computer chips. Meanwhile, bottom-up masking using chemical bonds or physical interactions has remained largely unexplored, despite its advantages of low cost, solution-processability, scalability and high compatibility with complex, curved and three-dimensional (3D) surfaces. Here we report atomic stencilling to make patchy nanoparticles (NPs), using surface-adsorbed iodide submonolayers to create the mask and ligand-mediated grafted polymers onto unmasked regions as ‘paint’. We use this approach to synthesize more than 20 different types of NP coated with polymer patches in high yield. Polymer scaling theory and molecular dynamics (MD) simulation show that stencilling, along with the interplay of enthalpic and entropic effects of polymers, generates patchy particle morphologies not reported previously. These polymer-patched NPs self-assemble into extended crystals owing to highly uniform patches, including different non-closely packed superlattices. We propose that atomic stencilling opens new avenues in patterning NPs and other substrates at the nanometre length scale, leading to precise control of their chemistry, reactivity and interactions for a wide range of applications, such as targeted delivery, catalysis, microelectronics, integrated metamaterials and tissue engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Field Validation of a Grid-Interactive Efficient Building Software Solution

The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Quantifying Primary Arc-Induced Degradation of Perovskite Solar Cells

Primary arcing induced by spacecraft charging presents a significant hazard to thin film solar cells if left unchecked. Here, we present the results of a preliminary effort to quantify the impacts of primary arcing to perovskite solar cells. Solar cells operating in a charged environment are susceptible to electrostatic discharges known as arcing. While primary arcs are not generally considered a major concern for traditional space PV, for thin film cells, these can induce significant heating and subsequent damage. We conducted ESD testing in a LEO-like plasma in the National Plasma Interaction Facility at NASA Glenn Research Center to quantify impacts to cell performance by arcing. The perovskites tested saw a decrease of short circuit current with an increased number of arcs, averaging a relative change of 73.89 ± 15.90% after 60 total arcs supplied a cumulative energy dose of 76.12 mJ to the string. Ongoing work entails testing with larger perovskite data sets and expanding to include additional thin film cell technologies to demonstrate the risk unmitigated primary arcing presents.

primary arcing↗
NASA NTRSDate not supplied

Comparison and Application of Battery Modeling Methods for Conceptual Electric Aircraft

Growing interest in design and optimization of electrified aircraft propulsion concepts prompts the need for accurate, flexible, and efficient methods to model battery systems. Presented in this paper are three battery modeling methods that have been used at NASA’s Glenn Research Center, each representing different mathematical or electrical approaches. Thévenin equivalent circuit, normalization, and curve-fitting methods are compared against battery cell test data for the X-57 Maxwell electric aircraft technology demonstrator. The methods are then applied in a simple multidisciplinary optimization context using NASA’s Six-Passenger Electric Quadrotor concept to determine their applicability and performance. The normalization method achieves the highest accuracy for steady and unsteady discharge rates with a voltage mean error percentage of 0.423% and 1.186%, respectively. Optimal quadrotor mission range between the models varies up to 0.5 nmi, identifying current battery modeling methods as a potentially significant contributor to mission analysis error. A set of relevant tools and techniques for conceptual battery modeling are identified in this paper, with conclusions made on the utility of each modeling approach for various design challenges.

power↗
NASA NTRS1970

Adventures in Research: A History of Ames Research Center, 1940-1965

The present document, which I have called a history-though it certainly was not written for historians-was prepared for and at the request of the NASA Ames Research Center which, in sponsoring the project, acted with the encouragement of NASA Headquarters. It is an account of the establishment, evolutionary development, and activities of the Ames Research Center covering a period characterized by unprecedented scientific and technological revolution. The writing of this book about the Ames Research Center was undertaken with considerable pleasure by one who for many years was employed by the Center’s parent organization NASA and, before that, NACA; who had closely followed the Center’s growth from the beginning; and who was personally acquainted with, and who held in some affection, the members of its founding staff. These facts are given to alert readers to the presence of bias and the inaccuracies stemming therefrom. It should be emphasized that this work is a history only of the Ames Research Center. It is not a history of the U.S. Government, of NACA or NASA, of other research centers, of the military services, of industry, or of world events. Information on these peripheral subjects is introduced merely to provide the reader with a generalized feeling for the local and world environment in which the formation and subsequent activities of the Ames Research Center took place. The background material provided is notably incomplete and in some instances reveals the bias of the NACA/NASA community at the time the events took place. Frequently, also, it reflects the personalized viewpoint of the author who was a close observer of many of these events.

NASA Center History Series↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler [National Renewable Energy Lab. (NR↗
NASA NTRS1991

Preparation of the Ice Certification of the Dornier 328 Regional Airliner By Numerical Simulation and By Ground Test

The Dornier 328, a new regional airliner, is to be qualified to FAR25/JAR25 requirements for operation into known icing conditions. All lifting surfaces are pneumatically deiced. Impingement limits were determined using a validated computational fluid dynamic (CFD) code. Wind tunnel tests with a model of the whole aircraft and the isolated empennage equipped with artificial ice shapes showed a degradation of handling characteristics due to ice accretion. Extensive two and three dimensional CFD calculations evaluated ice accretion at the deflection elevator horn. Icing tunnel tests were performed with a model of the horizontal tail with icing similitude fulfilled. The Dornier Do328 powerplant air induction system has successfully completed a program of icing tests in support of aircraft certification for operation into known icing conditions. Potential flight icing conditions were extensively analyzed using a CFD potential flow code and 3-D particle tracking routine to identify critical flight icing conditions. The tunnel test program verified the analytically predicted critical ice accretion surfaces of the air induction system, the adequacy of the ice protection provisions and demonstrated compliance with the applicable (JAR25) regulatory material.

D Welte↗
DOE OSTI2026

Are CO2 batteries ready for the grid? A cross-cutting deployment checklist

Metal-CO2 batteries have attracted considerable research interest in the past decade due to the utilization of the greenhouse CO2 gas. The low cost and abundance of CO2 feedstocks, together with high specific capacity metal anodes, make this technology a promising candidate for electricity-demanding data centers and grids. However, nonstandard data reporting, ambiguous hardware designs, and questionable cycling parameters have emerged as the field has grown. A clear checklist and standardized reporting format for research and development are urgently needed. Here, after carefully re-analyzing 15 Na-CO2 and 9 Li-CO2 studies, we propose a general checklist and a flowchart for CO2 batteries and related gas conversion systems. Specific performance values from a deployment-oriented perspective, based on commercial lithium iron phosphate batteries, are integrated into the list. We frame research and development efforts around grid-relevant outputs, including areal rate and capacity, cyclability, gas utilization, and safety. While illustrated for Na- and Li-CO2 cells, this framework is directly transferable to other CO2 batteries and air/oxygen batteries, helping align benchtop demonstrations with systematic metrics that ultimately govern future deployment.

Wu, Wenda [ORNL] (ORCID:000900033307687X)↗
DOE OSTI2023

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry↗
DOE OSTI2025

pi-Extended Porphyrins: The Impact of Aromatic Heterocycles on the Properties of the Largely pi-Extended Structures (Final Report_UNT_SC0016766)

Largely π-extended carbon-rich materials represent fascinating yet challenging frontiers in chemistry and materials science as it offers numerous opportunities in molecular electronics. pi-Extended porphyrins possess unique set of electronic and photophysical properties and are very attractive for a wide range of applications. However, the synthesis and functionalization of pi-extended porphyrins had been very challenging. To explore and expand this intriguing research field, it is essential to develop synthetic tools to make them accessible. Funded by the Department of Energy Basic Energy Science, my laboratory addressed these synthetic challenges by developing concise and versatile methods for pi-extended porphyrins. Significant progress has been made in multiple directions, including fusing Polycyclic Aromatic Hydrocarbons (PAH), aromatic heterocycles, antiaromatic component, and cross-conjugated component to porphyrins as well as push-pull porphyrins. The availability of these methods has made it possible to rationally design and synthesize functionalized pi-extended porphyrins. Unprecedented electronic and photophysical properties have been discovered for these pi-extended porphyrins.

36 MATERIALS SCIENCE↗
NASA NTRS2026

A Study of Space Environment Effect on Highly Thermally Conductive Hybrid Carbon Fiber Polymer Composites

A set of novel highly thermally conductive hybrid carbon fiber (CF) polymer composites has been developed for lightweight thermal radiator applications in space missions. This study investigates the effects of the space environment on these materials following exposure in low-Earth orbit (LEO) during the Materials International Space Station Experiment (MISSE)-17 flight mission, where samples experienced 159 days of combined atomic oxygen (AO), ultraviolet (UV) radiation, high vacuum, space radiation and thermal cycling. Post-flight characterization included weight loss, surface morphology, thermo-optical properties, molecular structures, glass transition temperature, thermal degradation and thermal conductivity analyses. The pyrolytic graphite sheet (PGS) samples exhibited negligible weight loss, stable thermo-optical property, and only minor oxidation signature on the exposed surface. Although AO erosion of the epoxy polymer matrix was evident, carbon nanotube (CNT)-infused PGS/CF epoxy composites retained high thermal emissivity and preserved their high thermal conductivities. These results demonstrate that the novel highly thermally conductive hybrid CF composites possess strong environmental resilience and are promising candidates for lightweight thermal radiators and thermal management components in future space exploration missions.

Space Environment↗
DOE OSTI2024

Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst

Tomographic imaging of time-evolving samples is a challenging yet important task for various research fields. At the nanoscale, current approaches face limitations of measurement speed or resolution due to lengthy acquisitions. We developed a dynamic nanotomography technique based on sparse dynamic imaging and 4D tomography modeling. We demonstrated the technique, using ptychographic x-ray computed tomography as its imaging modality, on resolving the in situ hydration process of polymer electrolyte fuel cell (PEFC) catalyst. The technique provides a 40-time increase in temporal resolution compared to conventional approaches, yielding 28 nm half-period spatial and 12 min temporal resolution. The results allow a quantitative characterization of the water intake process inside PEFC catalysts with nanoscale resolution, which is crucial for understanding their electrochemical mechanisms and optimizing their performance. Our technique enables high-speed operando nanotomography studies and paves the way for wider application of dynamic tomography at the nanoscale.

Science & Technology - Other Topics↗
NASA NTRSDate not supplied

Experimental Studies of Open Rotor Installation Effects

Open rotor propulsion technologies offer an opportunity for reducing fuel burn. At the same time, great challenges arise from this radically different engine architecture in terms of aircraft system integration. The aeroacoustic effects of integration are one of those key challenges and, furthermore, can offer the possibility for total aircraft system noise reduction. The inter-relationship of the aerodynamic and aeroacoustic system integration effects is particularly important to enable future application. An extensive model scale test campaign was conducted to investigate a broad range of these open rotor installation effects for both a conventional and an unconventional airframe. The experimental campaign was conducted in the Boeing Low Speed Aeroacoustic Facility with specially designed modifications for efficient positioning of the open rotor rig relative to the airframe. The airframe was traversed remotely relative to the fixed open rotor rig providing for the investigation of a large number of installation positions. Eight positions around the main wing of the conventional airframe and eleven positions above the hybrid wing body airframe were documented. Other parameters investigated in the test campaign included forward flight simulation Mach number, angle of attack, rotor speed, and airframe control surface deployment. In addition, both airframes were modified for alternate configurations. The conventional airframe was configured with both a T and a U tail while the unconventional hybrid wing body airframe was configured with different vertical control surfaces. An extensive instrumentation package was deployed. The acoustics were documented with a fixed array of far field microphones, a traversing array of in-flow microphones, an out-of-flow traversing phased array, and unsteady pressure transducers mounted flush on the surface of the airframes. In addition, mean flow surveys were measured with an articulating arm traversing system. The flow field surveys were particularly valuable in documenting flow distortion effects for the various installation positions and those created by angle of attack. This presentation will report the key results obtained for open rotor installation effects and discuss future prospects with the perspective of these results.

Michael J Czech↗
DOE OSTI2024

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry↗
DOE OSTI2025

Imprints of High-Density Nuclear Symmetry Energy on Crustal Fraction of Neutron Star Moment of Inertia

The density dependence of nuclear symmetry energy E sym (ρ) remains the most uncertain aspect of the equation of state (EOS) of supradense neutron-rich nucleonic matter. Utilizing an isospin-dependent parameterization of the nuclear EOS, we investigate the implications of the observational crustal fraction of the neutron star (NS) moment of inertia ΔI/I for the E sym (ρ). We find that symmetry energy parameters significantly influence the ΔI/I, while the EOS of symmetric nuclear matter has a negligible effect. In particular, an increase in the slope L and skewness J sym of symmetry energy results in a larger ΔI/I, whereas an increase in the curvature K sym leads to a reduction in ΔI/I. Moreover, the ΔI/I is shown to have the potential for setting a lower limit of symmetry energy at densities exceeding 3 ρ 0 , particularly when L is constrained to values less than 60 MeV, thereby enhancing our understanding of supradense NS matter.

equation of state↗
DOE OSTI2026

The Future Polarized Target Program at Jefferson Lab

Polarized targets have played a crucial role in Jefferson Lab's exploration of nuclear structure over the past four decades. The three original experimental halls have seen 19 separate installations of polarized solid or gas targets for use in the particle physics scattering experiments, and this trend will continue in the next decade. Five polarized target systems are in preparation for use at JLab in the coming years. Hall B will see the use of two solid polarized targets, one longitudinally polarized to the beam, the other transversely, as well as a novel 3He gas polarized target. In Hall C, new experiments will augment the tensor polarization in dynamically polarized solids. Plans are under development to bring a polarized solid target to Jefferson Lab's photon beam hall, Hall D, for the first time. To support these efforts, the JLab polarized target group is building a test laboratory to develop dynamic nuclear polarization techniques, as well as an apparatus to irradiate target material using electrons from JLab's injector test facility. In this talk, we will explore the development progress and plans for each of these efforts.

Maxwell, James [Thomas Jefferson National Accelera↗
DOE OSTI2026

A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty

Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.

Ham, S W↗