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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High Throughput Computational Framework of Materials Properties for Extreme Environments

This project aims to establish a framework capable of efficiently predicting the properties of structural materials for service in harsh environments over a wide range of temperatures and over long periods of time. The approach is to develop and integrate high throughput first-principles calculations in combination with machine learning (ML) methods, perform high throughput CALPHAD (calculations of phase diagrams) modeling, and carry out finite element method (FEM) simulations. Relevant to high temperature service in fossil power system, nickel-based superalloys such as Inconel 740 and Haynes 282 as well as the associated (Ni-Cr-Co)-Al-C-Fe-Mn-Mo-Nb-Si-Ti system, were investigated. The present framework was built on the concept of phase-based property data, in which properties of individual phases are modeled as a function of internal and external independent variables. This project established an open-source infrastructure with the following capabilities: (1) High throughput implementation of first-principles calculations at finite temperatures and variable compositions using both accurate phonon calculations and the efficient Debye model for thermodynamic properties, elastic constants, diffusion coefficients, vacancy formation, stacking and twin faults, and dislocation mobility; i.e., using the developed code DFTTK; (2) Machine learning capabilities to predict the above properties so that the number of first-principles calculations can be significantly reduced; e.g., using the developed code SIPFENN; (3) High throughput CALPHAD modeling of the above properties as a function of temperature and composition using our unique capability based on ESPEI and PyCalphad; (4) New capabilities to predict the stress-strain behavior of individual phases; and (5) New models for tensile strength prediction in common FEM software with the crystal plasticity finite element simulations (CPFEM).

, Ni-based superalloys↗
DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗
NASA NTRS1990

Statistically based material properties: A military handbook-17 perspective

This paper describes statistical procedures and their importance in obtaining composite material property values in designing structures for aircraft and military combat systems. The property value is such that the strength exceeds this value with a prescribed probability with 95% confidence in the assertion. The survival probabilities are the 99th percentile and 90th percentile for the A and B basis values respectively. The basis values for strain to failure measurements are defined in a similar manner. The B value is the primary concern of this paper.

Donald M. Neal↗
NASA NTRS1984

RIM as the data base management system for a material properties data base

Relational Information Management (RIM) was selected as the data base management system for a prototype engineering materials data base. The data base provides a central repository for engineering material properties data, which facilitates their control. Numerous RIM capabilities are exploited to satisfy prototype data base requirements. Numerical, text, tabular, and graphical data and references are being stored for five material types. Data retrieval will be accomplished both interactively and through a FORTRAN interface. The experience gained in creating and exercising the prototype will be used in specifying requirements for a production system.

Karr, P. H.↗
NASA NTRS1985

Investigation of test methods, material properties, and processes for solar cell encapsulants

Progress in solar energy technology is reported in the following areas: aging and life prediction methodology and devices for solar cell encapsulation; the function of adhesion chemistry, primers, and a new diagnostic technique for estimations of bond durability; a study of fire retardant formulations for decreasing the potential flammability of solar modules; initial studies of the electrical insulating properties of encapsulation materials and measurement of the intrinsic dielectric strength; antisoiling compounds for the prevention of soil build-up on the outer surface of the module; and low temperature processing encapsulants that permit module fabrication at temperatures less than 100 C. Another area of study has been added to determine the degree to which formulation and processes affect the module quality and manufacturing yield.

Willis, P. B.↗
NASA NTRS1986

Spacecraft dielectric material properties and spacecraft charging

The physics of spacecraft charging is reviewed, and criteria for selecting and testing semiinsulating polymers (SIPs) to avoid charging are discussed and illustrated. Chapters are devoted to the required properties of dielectric materials, the charging process, discharge-pulse phenomena, design for minimum pulse size, design to prevent pulses, conduction in polymers, evaluation of SIPs that might prevent spacecraft charging, and the general response of dielectrics to space radiation. SIPs characterized include polyimides, fluorocarbons, thermoplastic polyesters, poly(alkanes), vinyl polymers and acrylates, polymers containing phthalocyanine, polyacene quinones, coordination polymers containing metal ions, conjugated-backbone polymers, and 'metallic' conducting polymers. Tables summarizing the results of SIP radiation tests (such as those performed for the NASA Galileo Project) are included.

Frederickson, A. R.↗
DOE OSTI2024

Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks

With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty quantification (UQ) of the predicted variables for informed decision-making cannot be overstated. UQ in material property prediction poses unique challenges, including multi-scale and multi-physics nature of materials, intricate interactions between numerous factors, limited availability of large curated datasets, etc. In this work, we introduce a physics-informed Bayesian Neural Networks (BNNs) approach for UQ, which integrates knowledge from governing laws in materials to guide the models toward physically consistent predictions. To evaluate the approach, we present case studies for predicting the creep rupture life of steel alloys. Experimental validation with three datasets of creep tests demonstrates that this method produces point predictions and uncertainty estimations that are competitive or exceed the performance of conventional UQ methods such as Gaussian Process Regression. Additionally, we evaluate the suitability of employing UQ in an active learning scenario and report competitive performance. The most promising framework for creep life prediction is BNNs based on Markov Chain Monte Carlo approximation of the posterior distribution of network parameters, as it provided more reliable results in comparison to BNNs based on variational inference approximation or related NNs with probabilistic outputs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluation of Material Properties for Flexible Coatings

In this study, different ratios and combinations of common epoxies, curing agents, and flexibilizers were used to find a material with desirable properties. Analysis of several material properties was conducted including glass transition temperature of each cured material which ensures high flexibility at a wide range of temperatures.

Strauss, Mariah Jasmine↗
DOE OSTI2023

Overview of a Versatile Loading System for Anisotropic Material Property Characterization

Additive manufacturing, cold rolling, and other thermomechanical treatments on metals, especially HCP, can cause texture and oriented grain structures resulting in anisotropic mechanical properties. This can lead to macroscopic response that significantly deviates from isotropic assumptions which motivates studying mechanical properties in multiple directions. In addition, multiaxial loading and complex stress states overlapping the above mentioned material anisotropy can lead to unexpected outcomes. Idaho National Laboratory developed an advanced mechanical testing system to study a range of uniaxial to multiaxial stress states while measuring the anisotropic response bringing insight into the overlap between material properties and stress states. High-temperature capability and stress- or strain-controlled loading is available to enable a variety of experiment types and conditions to measure elastic, plastic, and viscoplastic properties. This poster presents the design and capabilities of this system with preliminary results highlighting the benefits of multiaxial loading and anisotropic analysis in an integrated system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Polyurethanes Based on Unmodified and Refined Technical Lignins: Correlation between Molecular Structure and Material Properties

The structural complexity and robust intermolecular interactions have challenged the incorporation of technical lignin into value-added polymeric materials for decades. To study the correlation between lignin molecular structure and material properties of lignin-based polyurethanes, we applied co-solvent enhanced lignocellulosic fractionation pretreatment followed by sequential precipitation to produce three distinct lignin preparations with narrowly distributed (molecular weight dispersity <2) and comparatively low molecular weight (<1500 g/mol) from poplar biomass. Structural characterization indicated that these lignin preparations differed in average molecular chain length and stiffness as well as hydroxyl group distribution. Secondary hydroxyl group providers such as aliphatic diols and polyethers were incorporated as building blocks into the lignin-based polyurethanes to provide additional hydrogen capacity to improve the dispersion of lignin in the polyurethane network. The selected aliphatic diols and polyethers interacted with lignin molecules at different levels of strength depending on their molecular structure, and their impacts were ultimately reflected in the mechanical and thermal properties of the resulting lignin-based polyurethanes. The copolymerization of technical lignin with tailored structure and secondary hydroxyl providers could provide new strategies in formulating lignin-based/containing polyurethanes for various functional applications.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Composite Material Property Nondestructive Characterization Using Obliquely Insonified Ultrasonic Waves

The analysis of reflected ultrasonic waves induced by oblique insonification of composite materials is a powerful tool for providing informations about defects and material properties. A device was developed to manipulate a pair of transmitting and receiving transducers at vrious angles of wave incidence and propagation with the fiber orientation.

Non-Destructive Evaluation Composites Mechanical P↗
DOE OSTI2025

SA-GAT-SR: self-adaptable graph attention networks with symbolic regression for high-fidelity material property prediction

Recent advances in machine learning have demonstrated an enormous utility of deep learning approaches, particularly Graph Neural Networks (GNNs) for materials science. These methods have emerged as powerful tools for high-throughput prediction of material properties, offering a compelling enhancement and alternative to traditional first-principles calculations. While the community has predominantly focused on developing increasingly complex and universal models to enhance predictive accuracy, such approaches often lack physical interpretability and insights into materials behavior. Here, we introduce a novel computational paradigm—Self-Adaptable Graph Attention Networks integrated with Symbolic Regression (SA-GAT-SR)—that synergistically combines the predictive capability of GNNs with the interpretative power of symbolic regression. Our framework employs a self-adaptable encoding algorithm that automatically identifies and adjust attention weights so as to screen critical features from an expansive 180-dimensional feature space while maintaining O(n) computational scaling. The integrated SR module subsequently distills these features into compact analytical expressions that explicitly reveal quantum-mechanically meaningful relationships, achieving 23 × acceleration compared to conventional SR implementations that heavily rely on first-principle calculations-derived features as input. This work suggests a new framework in computational materials science, bridging the gap between predictive accuracy and physical interpretability, offering valuable physical insights into material behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ultrasonic Fiber Waveguides for Measuring Spatially Distributed Environmental and Material Properties

We report using carbon fibers (<100 μm in diameter) as ultrasonic waveguides to measure spatial changes in the environment and material properties. We connected carbon fibers of different lengths to an ultrasonic transducer and measured changes in the times of flight in a pulse-echo mode in response to elevated temperatures. By simultaneously interrogating multiple fibers of different lengths and collectively analyzing the time of flight in each fiber, we demonstrated dynamic measurements of the temperature distribution along the fiber bundle during their heating.

Walton, Kenneth↗
DOE OSTI2022

Laser ablation for structuring Li-ion electrodes for fast charging and its impact on material properties, rate capability, Li plating, and wetting

Laser ablation is a scalable technique for decreasing the effective tortuosity of electrodes by selectively removing material with high precision. Applied to ≈ 110 um thick electrode coatings, this work focuses on understanding the impact of laser ablation on electrode material properties at the beginning of life and synergistic impacts of ablated channels on cell performance throughout their cycle life. Post laser ablation, local changes in chemistry, crystallography, and morphology of the laser-impacted electrode regions are investigated. It is shown that femtosecond pulsed laser ablation can achieve high-rate material removal with minor material damage locally at the interface of the impacted zones. The capacity achieved during a 6C (10 min) constant-current constant-voltage charge to 4.2 V improved from 1 mAh cm -2 for the non-ablated electrodes to almost 2 mAh cm -2 for the ablated electrodes. This benefit is attributed to a synergistic effect of enhanced wetting and decreased electrode tortuosity. The benefit was maintained for over 120 cycles, and upon disassembly decreased Li-plating on the graphite anode was observed. Finally, multi-physics modeling in conjunction with wetting analyses showed that laser ablating either one of the electrodes led to substantial improvements in wetting and rate capability, indicating that substantial performance benefits can be achieved by ablating only the graphite anode as apposed to both electrodes.

25 ENERGY STORAGE↗
NASA NTRS1983

Study of relationships of material properties and high efficiency solar cell performance on material composition

The performance improvements obtainable from extending the traditionally thin back-surface-field (BSF) layer deep into the base of silicon solar cells under terrestrial solar illumination (AM1) are analyzed. This extended BSF cell is also known as the back-drift-field cell. About 100 silicon cells were analyzed, each with a different emitter or base dopant impurity distribution whose selection was based on physically anticipated improvements. The four principal performance parameters (the open-circuit voltage, the short-circuit current, the fill factor, and the maximum efficiency) are computed using a FORTRAN program, called Circuit Technique for Semiconductor-device Analysis, CTSA, which numerically solves the six Shockley Equations under AM1 solar illumination at 88.92 mW/cm, at an optimum cell thickness of 50 um. The results show that very significant performance improvements can be realized by extending the BSF layer thickness from 2 um (18% efficiency) to 40 um (20% efficiency).

Sah, C. T.↗
NASA NTRS2003

Material Properties Analysis of Structural Members in Pumpkin Balloons

The efficient design, service-life qualification, and reliability predictions for lightweight aerospace structures require careful mechanical properties analysis of candidate structural materials. The demand for high-quality laboratory data is particularly acute when the candidate material or the structural design has little history. The pumpkin-shaped super-pressure balloon presents both challenges. Its design utilizes load members (tendons) extending from apex to base around the gas envelope to achieve a lightweight structure. The candidate tendon material is highly weight-efficient braided HM cord. Previous mechanical properties studies of Zylon have focused on fiber and yarn, and industrial use of the material in tensile applications is limited. For high-performance polymers, a carefully plamed and executed properties analysis scheme is required to ensure the data are relevant to the desired application. Because no directly-applicable testing standard was available, a protocol was developed based on guidelines fiom professional and industry organizations. Due to the liquid-crystalline nature of the polymer, the cord is very stiff, creeps very little, and does not yield. Therefore, the key material property for this application is the breaking strength. The pretension load and gauge length were found to have negligible effect on the measured breaking strength over the ranges investigated. Strain rate was found to have no effect on breaking strength, within the range of rates suggested by the standards organizations. However, at the lower rate more similar to ULDB operations, the strength was reduced. The breaking strength increased when the experiment temperature was decreased from ambient to 183K which is the lowest temperature ULDB is expected to experience. The measured strength under all test conditions was well below that resulting from direct scale-up of fiber strength based on the manufacturers data. This expected result is due to the effects of the braiding process and material ageing.

Sterling, W. J.↗
DOE OSTI2023

Renewable Energy Materials Properties Database: Summary

Renewable energy is providing a growing share of electricity generation in the United States, with generation from utility scale wind and solar increasing by 12% and 29%, respectively, in 2020 (EIA 2021). Installation of new renewable energy facilities requires material inputs that range from common construction materials to specialized, high-performance materials that may have limited availability. This report summarizes the Department of Energy (DOE) Wind Energy Technologies Office (WETO) and DOE Solar Energy Technologies Office (SETO) database of materials used in domestic wind and solar installations. The Energy Act of 2020 directs WETO and SETO to deliver a "comprehensive physical property database of materials for use in [wind and solar] energy technologies, which shall identify the type, quantity, country of origin, source, significant uses, projected availability, and physical properties of materials used in [wind and solar] energy technologies" by no later than September 1, 2022. This report is the summary and directions for use of the Renewable Energy Materials Property Database (REMPD), in response to that direction. The related full text of the Energy Act of 2020 is provided in Appendix A. The focus of the REMPD and this accompanying report is on quantifying the raw and processed materials used in renewable energy technologies. The database contains information on the amount of each material that goes into wind and solar power plants, descriptions of the relevant material properties, and the primary countries of origin for each material. Some materials go through several stages of processing and/or are incorporated into subcomponents that make up the completed energy generation facilities. This report does not analyze supply chains for the production of renewable energy plant components. The Department of Energy has carried out related analysis in response to Executive Order 14017, which directed production of "America's Supply Chains" reports for Wind and Solar. The supply chain reports can be found at https://www.energy.gov/sites/default/files/2022-02/Wind%20Supply%20Chain%20Report%20-%20Final%202.25.22.pdf (Wind) and https://www.energy.gov/sites/default/files/2022-02/Solar%20Energy%20Supply%20Chain%20Report%20-%20Final.pdf (Solar). Additional reports in this series that are relevant to wind, solar and hybrid plants include: Energy Storage at https://www.energy.gov/sites/default/files/2022-02/Energy%20Storage%20Supply%20Chain%20Report%20-%20final.pdf and Neodymium Magnets at https://www.energy.gov/sites/default/files/2022-02/Neodymium%20Magnets%20Supply%20Chain%20Report%20-%20Final.pdf.

14 SOLAR ENERGY↗