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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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349 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Bipolar Nickel-Metal Hydride Battery Development Project

This paper reviews the development of the Electro Energy, Inc.'s bipolar nickel metal hydride battery. The advantages of the design are that each cell is individually sealed, and that there are no external cell terminals, no electrode current collectors, it is compatible with plastic bonded electrodes, adaptable to heat transfer fins, scalable to large area, capacity and high voltage. The design will allow for automated flexible manufacturing, improved energy and power density and lower cost. The development and testing of the battery's component are described. Graphic presentation of the results of many of the tests are included.

Cole, John H.↗
NASA NTRSDate not supplied

Enabling Mission Flexibility to Battery Driven Deep Space Endeavors With Generalized Battery-Health-Monitoring Using Physics-Based and Data-Driven Reduced-Order Models

The needs and requirements for an electrochemical energy storage for deep space exploration is well explored. It is often understood that different mission sites and environmental conditions require different battery chemistries or technologies. Additionally, various engineering solutions are deployed to overcome specific chemical challenges. One often overlooked need is the “health” monitoring of an electrochemical storage system. The term generalized health monitoring, as envisioned in this work, refers to the monitoring of various aspects such as electrode health, electrolyte health, reaction pathway health, cooling system health, sensor health, and BMS health [1]. Generalized health monitoring allows mission leads, engineers, and scientists to incorporate flexibility in mission designs, make on-the-fly mission changes, and extend the duration of science missions. Moreover, it enables automation and data-driven decision-making without compromising safety and performance. Recently, our group developed a hierarchy of thermal reduced-order models (TROM) by combining a physics-based modeling approach and data-driven model reduction techniques applied to flight data [2]. The resulting TROMs were found to be not only accurate but also identifiable from the flight data. Consequently, the coefficient of variance of the model parameters is small over the course of hundreds of flights, allowing for monitoring the parameter evolution trajectories as the battery ages and degrades. These parameters constitute the metrics of the generalized health of a battery. Monitoring their evolution allows such models to be used for anomaly detection and prognostics, improving early detection of abnormal behavior and thus enabling timely maintenance, longer battery life, and enhanced battery safety. For this presentation, the practicality of the thermal model will be validated on a pack of 14cells under various topology configurations such as 1S14P, 2P7S, 7S2P, and 1P14S. It is well known that manufacturing and non-uniform aging lead to variability in the performance of a cell, which is exacerbated by cell balancing during active load. Additionally, in extreme scenarios, the paramount objective is to complete the mission, regardless of the stresses on the battery. Topology-induced balancing issues further stress the battery. The goal of this study is to determine if the noise (identifiability) in the reduced-order thermal model parameters is sensitive to topology, cell spacing, cooling strategy, and manufacturing or age variability. The variability in cells is considered by assuming a multimodal distribution for microscopic parameters of a cell (such as porosity, tortuosity, reaction kinetics, volumetric thermal conductivity, and volumetric heat capacity). The compounded effect of manufacturing variability, topological selection, cooling strategies, and cell balancing ages each cell in a battery differently. The study aims to clarify whether the challenge in extracting maximum information depends on the minimum number of sensors or models used for data extraction.

Automation↗
NASA NTRSDate not supplied

3D Woven Mid-Density Carbon Phenolic (3MDCP) Full-Scale Heatshield Development for Mars Sample Return (MSR) Earth Entry System (EES)

The Mars Sample Return (MSR) mission will be returning samples of Martian soil to Earth. The samples will be returned in the Earth Entry System (EES). The EES capsule is protected by a new thermal protection system; the 3-Dimensionally Woven, Mid-Density, Carbon Phenolic (3MDCP) material which is derived from the Heatshield for Extreme Entry Environment Technology (HEEET). The baseline 3MDCP design is a single piece thermal protection system that avoids the manufacturing and certification challenges associated with a tiled configuration. A 3MDCP heatshield begins as a flat woven preform that is formed to the final heatshield shape and then infused with phenolic resin. A NASA Ames lead team, in collaboration with Spirit Textiles (formerly TEAM Inc.), Fiber Materials Inc. (FMI, a Spirit AeroSystems Company), and Kratos SRE, has been developing and demonstrating the processes to fabricate the 3MDCP heatshield and characterize the resulting properties. The process of forming the flat woven preform into the final heatshield shape, a sphere-cone geometry with a 52.5° cone angle, involves local but substantial movement of the yarns in the weave. This results in continuous fibers across the single piece heatshield, albeit with property variations between different regions of the heatshield. This presentation will provide a high-level status of 3MDCP development for the MSR EES heatshield. This will include an overview of the manufacturing processes with an emphasis on the impact of forming on fiber orientation, material properties, and performance. Results comparing preliminary formed and flat materials will be shown. Additionally, the presentation will layout the broader plan for property testing and tie-in to aerothermal performance.

Peter Edward Marshall↗
DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
NASA NTRS1985

Nondestructive Evaluation of Composites By Optical Time Domain Reflectometry

Results in the measurement of slowly varying mechanical loading functions on composites using optical time domain reflectometry (OTDR) in imbedded optical fiber during both simulated manufacture and use are reviewed. First, the basic theoretical and experimental principles of the OTDR system are described. Next, the mechanical system of the composite and the imbedded fiber is analyzed. Results of measurement obtained for various loading functions applied to material specimens are then described and system limitations on spatial resolution, strain amplitude sensitivity, and frequency response are explained in terms of the range and resolution limits of the OTDR system.

R O Claus↗
DOE OSTI2023

Spatiotemporal Studies of Soluble Inorganic Nanostructures with X‐rays and Neutrons

This Review addresses the use of X-ray and neutron scattering as well as X-ray absorption to describe how inorganic nanostructured materials assemble, evolve, and function in solution. We first provide an overview of techniques and instrumentation (both large user facilities and benchtop). We review recent studies of soluble inorganic nanostructure assembly, covering the disciplines of materials synthesis, processes in nature, nuclear materials, and the widely applicable fundamental processes of hydrophobic interactions and ion pairing. Reviewed studies cover size regimes and length scales ranging from sub-Ångström (coordination chemistry and ion pairing) to several nanometers (molecular clusters, i.e. polyoxometalates, polyoxocations, and metal-organic polyhedra), to the mesoscale (supramolecular assembly processes). Reviewed studies predominantly exploit 1) SAXS/WAXS/SANS (small- and wide-angle X-ray or neutron scattering), 2) PDF (pair-distribution function analysis of X-ray total scattering), and 3) XANES and EXAFS (X-ray absorption near-edge structure and extended X-ray absorption fine structure, respectively). While the scattering techniques provide structural information, X-ray absorption yields the oxidation state in addition to the local coordination. Our goal for this Review is to provide information and inspiration for the inorganic/materials science communities that may benefit from elucidating the role of solution speciation in natural and synthetic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials↗
DOE OSTI2026

Improving Marine Energy Production Through Commercialization of a Low Cost, Drag-Reducing Slippery Coating (CRADA 679 Abstract)

Marine energy capture systems offer great promise for providing clean energy, but they operate in a challenging and dynamic environment and must be optimized to the highest extent possible. Computational studies predict that drag reduction on marine energy and blue economy systems will result in meaningful improvements in energy efficiency. Based on extensive coating experience, PNNL is proposing to bring to market a new drag-reducing coating called Superhydrophobic Lubricant-Infused Drag-Efficient Coating – SLIDE-Coat. PNNL has a deep knowledge base regarding this class of slippery coatings, and we have a group of enthusiastic industry partners who have committed to partnering, conducting field testing, and providing well over 50% cost share. In addition to validating the technology, the team will create a commercialization roadmap to ensure the commercial success of the technology after the government-sponsored two-year program is complete. The main technical goal is to design, manufacture, and experimentally validate a new coating that can reduce hydrodynamic skin friction drag by 20%. The main commercialization goal is to develop a roadmap that identifies activities needed to complete SLIDE-Coat’s development after the conclusion of this project. Year 1 will focus on adaptation and modification of the existing SLIC coating system to optimize drag reduction and assessment and quantification of drag reduction on relevant materials in a laboratory setting. Year 2 will focus on optimizing and demonstrating drag reduction with preferred coatings. The manufacturability, ease of application, adhesion to relevant surfaces, and consistency will be assessed. Quantification of drag reduction on prototype materials in a relevant marine field setting will be executed.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Evaluation of U10Mo Fuel Plate Performance Modeling Over Hot Isostatic Press and Hydraulic Bending for MURR DDE Plates

The United States High Performance Research Reactor Program’s objective is to reduce the amount of highly enriched uranium currently implemented in research reactors. The conversion of these research reactors requires designing a monolithic U10Mo plate fuel, with the fuel plate geometry being dependent on each research reactor. The process of forming the plates includes a hot isostatic pressing (HIP) to manufacture a prototypic plate. In the case of the Missouri University Research Reactor (MURR) design demonstration element (DDE) plate manufacture, plates that have been through HIP are then curved using dies and a hydraulic press to impart the desired curvature. Both fabrication processes impart residual stresses into each fuel plate region, with the curvature of the plates taking some regions of the fuel plate up to their material yield stresses, accompanied by plastic strain. The amount of plastic strain and stress imparted onto each MURR DDE plate is determined by the radius of curvature, thickness of each region, and overall width of the fuel plates. Furthermore, this work aims to predict the yield stresses and strain using ABAQUS to simulate the proposed fabrication process of the MURR DDE plates, accompanied by discussion over the stresses and strains as to their relation to nuclear fuel performance and the impact they will have during early irradiation.

ABAQUS↗
NASA NTRS1983

Battery charge control with temperature compensated voltage limit

Battery charge control for orbiting spacecraft with mission durations from three to ten years, is a critical design feature that is discussed. Starting in 1974, the General Electric Space Systems Division designed, manufactured and tested battery systems for six different space programs. Three of these are geosynchronous missions, two are medium altitude missions and one is a near-earth mission. All six power subsystems contain nickel cadmium batteries which are charged using a temperature compensated voltage limit. This charging method was found to be successful in extending the life of nickel cadmium batteries in all three types of earth orbits. Test data and flight data are presented for each type of orbit.

Thierfelder, H. E.↗
NASA NTRS1989

NASA aerospace battery systems program update

An overview of a battery systems program designed to enhance the safety, reliability, and performance of NASA's aerospace primary and secondary batteries as well as battery power systems is presented. The status of research in all three areas is reviewed. The approach to achieving the program objectives involves increasing the fundamental understanding of primary and secondary cells; providing for improved nickel-cadmium manufacturing process control; providing for the establishment of a NASA standard nickel-hydrogen cell design; establishing specifications, design and operational guidelines for both primary and secondary cells and batteries; providing training relating to the above areas; and opening and maintaining communication lines within NASA and the aerospace battery community.

Manzo, Michelle A.↗
DOE OSTI2026

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
NASA NTRSDate not supplied

Technology Assessment and Modelling of Three Terminal Tandem Solar Cells for In-Space Utilization

NASA seeks a sustained human presence on the lunar surface. High-efficiency and resilient energy systems are critical to supporting habitats, scientific outposts, and lunar surface operations. Photovoltaics have long been the backbone of space power systems, transitioning from silicon solar cells to multi-junction III-V solar cells, which now dominate state-of-the-art (SOA) technology. Multi-junction cells achieve high efficiency by layering semiconductors, each absorbing a specific portion of the solar spectrum. However, efficiency gains are increasingly constrained by device physics and manufacturing complexity. Additionally, higher-order junctions pose challenges for accurate modelling and performance characterization due to difficulties in replicating the AM0 spectrum.

solar cells↗
DOE OSTI2026

Directing Assembly of Mesoscale Multi‐Shell Morphologies of DNA Origami Crystals

Nature builds hierarchically ordered materials, such as seashells, wood, and bones, through spatially and temporally regulated growth. Mimicking such a level of control in synthetic systems remains challenging, particularly in achieving multiscale organizations with prescribed nanoscale arrangements and desired material morphologies. In this study, we introduce a DNA-based self-assembly strategy for constructing diverse multi-shell mesoscale morphologies from nanoscale lattices, enabling prescribed structural, and compositional 3D material patterns. Using DNA origami frames as modular monomers, we direct anisotropic epitaxial growth through addressable DNA frame binding motifs and encapsulate nanoparticles (NPs) in desired 3D patterns. Sequential monomer addition under thermodynamically favorable conditions enables shell growth through heterogeneous nucleation while minimizing unwanted homogeneous nucleation. Here, we demonstrate that DNA-encoded addressability enables epitaxial shell growth along specific lattice directions, yielding crystals with multilayered mesoscale organization, including tube-like (sushi roll) and plate-like (macaron) morphologies. Shell-specific NP configurations and compositions are achieved through addressable and differentiated placement of NPs within each shell, as validated by small-angle x-ray scattering and cross-sectional scanning transmission electron microscopy. We further demonstrate addressable NP release and reveal that shells modulate release kinetics. Together, these findings establish a platform for fabricating DNA origami crystals with programmable mesoscale morphologies, nanoscale structure, composition, and transport properties.

3D patterning↗
NASA NTRS1995

A review of nickel hydrogen battery technology

This paper on nickel hydrogen batteries is an overview of the various nickel hydrogen battery design options, technical accomplishments, validation test results and trends. There is more than one nickel hydrogen battery design, each having its advantage for specific applications. The major battery designs are individual pressure vessel (IPV), common pressure vessel (CPV), bipolar and low pressure metal hydride. State-of-the-art (SOA) nickel hydrogen batteries are replacing nickel cadmium batteries in almost all geosynchronous orbit (GEO) applications requiring power above 1 kW. However, for the more severe low earth orbit (LEO) applications (greater than 30,000 cycles), the current cycle life of 4000 to 10,000 cycles at 60 percent DOD should be improved. A NASA Lewis Research Center innovative advanced design IPV nickel hydrogen cell led to a breakthrough in cycle life enabling LEO applications at deep depths of discharge (DOD). A trend for some future satellites is to increase the power level to greater than 6 kW. Another trend is to decrease the power to less than 1 kW for small low cost satellites. Hence, the challenge is to reduce battery mass, volume and cost. A key is to develop a light weight nickel electrode and alternate battery designs. A common pressure vessel (CPV) nickel hydrogen battery is emerging as a viable alternative to the IPV design. It has the advantage of reduced mass, volume and manufacturing costs. A 10 Ah CPV battery has successfully provided power on the relatively short lived Clementine Spacecraft. A bipolar nickel hydrogen battery design has been demonstrated (15,000 LEO cycles, 40 percent DOD). The advantage is also a significant reduction in volume, a modest reduction in mass, and like most bipolar designs, features a high pulse power capability. A low pressure aerospace nickel metal hydride battery cell has been developed and is on the market. It is a prismatic design which has the advantage of a significant reduction in volume and a reduction in manufacturing cost.

Smithrick, John J.↗
DOE OSTI2025

3D-Printed mmWave Quasi-Holographic Antenna for 2-D Beamforming

This paper presents the design and manufacturing of a novel 2D-scanning antenna that integrates a 3D-printed Rotman lens with a quasi-holographic leaky-wave antenna (HLWA). The proposed design achieved beam-scanning capabilities by leveraging the beamforming of the Rotman lens and the high-gain directive properties of the quasi-HLWA. The Rotman lens (RL) enables beam steering in the elevation plane by switching between input ports. The quasi-HLWA, designed using holographic principles, achieves frequency-controlled beam scanning in the azimuth plane. The entire antenna structure was fabricated using additive manufacturing with an Ink1092 substrate and silver ink for the conductive traces. This approach provides greater control over material placement and design freedom compared to traditional methods. A 25° transmission linear substrate taper was used to ensure good impedance matching between the Rotman lens and the quasi-HLWA, allowing greater gain while maintaining a good scanning range. The experimental results validate the 2D scanning capability of the proposed antenna. The antenna system provides coverage from −54° to 54° in the elevation θ plane and −28° to 28° in the azimuth plane ϕ , with a maximum measured gain of 21.3 dBi at 28 GHz with an average radiation efficiency η=60 %. The fabricated prototype was tested, and the performance was in good agreement with the simulated performance.

Rotman lens↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗