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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Si-based materials for lithium-ion batteries III: Surface-modified Si/C/polyvinylidine difluoride powder

X-ray photoelectron spectroscopy was used to analyze Si/C/polyvinylidine difluoride powder obtained from Paraclete Energy Inc. The spectra were obtained using incident monochromatic Al K α radiation at 1486.6 eV (0.834 01 nm). An initial survey spectrum together with F 1s, O 1s, C 1s, and Si 2p are presented. A final survey spectrum was collected to ascertain the amount of beam-induced damage, which appears to be minimal. Finally, the spectra indicate the principal core level photoelectron and Auger electron signals with only minor nitrogen signal and show the expected silicon-carbon and silicon-fluorine species related to the surface modification process in addition to oxidized carbon and silicon due to atmospheric exposure.

25 ENERGY STORAGE↗
DOE OSTI2020

Si-based materials for lithium-ion batteries IV: Surface-modified Si/C/perfluorooctene powder

X-ray photoelectron spectroscopy was used to analyze nano-Si/C/perfluorooctene powder obtained from Paraclete Energy Inc. The spectra were obtained using incident monochromatic Al K α radiation at 1486.6 eV (0.834 01 nm). An initial survey spectrum together with F 1s, O 1s, C 1s, and Si 2p are presented. A final survey spectrum was collected to ascertain the amount of beam-induced damage, which appears to be minimal. Finally, the spectra indicate the principal core level photoelectron and Auger electron signals with only minor nitrogen signal and show the expected silicon-carbon, carbon-fluorine, and silicon-fluorine species related to the surface modification process in addition to oxidized carbon and silicon due to atmospheric exposure.

25 ENERGY STORAGE↗
DOE OSTI2020

Si-based materials for lithium-ion batteries V. n-SiO powder

X-ray photoelectron spectroscopy was used to analyze Si powders that have a native oxide surface, obtained from Paraclete Energy, Inc. The spectra were obtained using incident monochromatic Al K α radiation at 1486.6 eV (0.834 01 nm). An initial survey spectrum together with O 1s, C 1s, and Si 2p are presented. A final survey spectrum was collected to ascertain the amount of beam-induced damage, which appears to be minimal. Finally, the spectra indicate the principal core level photoelectron and Auger electron signals with only minor nitrogen signal and show the expected oxidized carbon and silicon species related to atmospheric exposure.

25 ENERGY STORAGE↗
DOE OSTI2024

Deriving the Infrared Complex Refractive Indices of Organic Powders for Optical Modeling: Comparison of Methods

Identification of solids via infrared reflection spectroscopy requires a spectral library of all solids likely to be encountered. A confounding factor in populating such a spectral library is that the reflectance spectra of solids vary with their form, including particle size, film thickness, and substrate. To reduce the efforts of experimentally constructing such a library, an alternate strategy is to use the wavelength-dependent optical constants, n and k, of a solid to calculate a series of reflectance spectra corresponding to each scenario or morphology. Because most n/k measurements are best performed on mm-sized crystals, however, the challenge of determining the optical constants increases when a solid is only readily available as a powder, as is often the case. Some organic solids, such as caffeine, are both unavailable in large crystals and difficult to press into pellets. In this study, the infrared optical constants, or complex refractive indices, of caffeine were determined using three different methods: single-angle reflectance, infrared spectroscopic ellipsometry, and quantitative absorbance measurements of KBr pellets. The n and k values derived through each method were used to model the hyperspectral imaging reflectance spectrum of a caffeine film on a steel planchet. Over 1,110 – 870 cm-1, the single-angle reflectance-derived n and k had the best correlation with the experimental spectrum. These results suggest different organic solids may require different methods to determine the most accurate infrared complex refractive indices for synthetic spectral libraries.

FTIR, hyperspectral imaging, infrared, infrared (I↗
DOE OSTI2023

In-process volumetric sensing of defects in multiple parts during powder bed fusion using ultrasound

This letter reports on the integration of eight ultrasonic transducers into a build substrate for individual in-process monitoring of eight parts fabricated using powder bed fusion additive manufacturing. Ultrasound is shown to be able to sense poor fusion of parts to the substrate and also sensitivity to porosity. This technique demonstrates the utility of ultrasound as one of a few techniques able to interrogate the volume of additively manufactured parts during the process. Additionally, the ability to measure several parts during a single build can be used for efficient process parameter development studies, as the ultrasonic measurements can offer rapid information about part quality and integrity.

Kizer, Nathan J.↗
DOE OSTI2023

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. Finally, the highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems.

42 ENGINEERING↗
DOE OSTI2023

Machine Learning Based System for Automated Estimation of Crystal Unit Cell Parameters from X-ray Diffraction Powder Patterns (MLCell) v0.1

This software uses machine learning models to perform inference on X-ray diffraction powder patterns, output from a diffractometer, to estimate all 6 unit cell parameters of crystalline lattices. Novel aspects of this software originated from the incorporation of concepts from crystallography to an ML-based approach; The resulting method achieves new performance capabilities without significant loss of accuracy and with less computationally intensive models.

Oklejas, Vanessa↗
DOE OSTI2025

Laser Powder Bed Fusion Microstructure Surrogate Model

SAND2025-11467O The Laser Powder Bed Fusion (LPBF) Microstructure Surrogate Model is a machine-learning-based tool. It predicts statistics of microstructures that are produced by the LPBF additive manufacturing process. It includes a series of codes for training, testing, and analyzing the model as well as utility scripts for handling data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Moser, Daniel [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2024

ExaCA grain structure predictions for laser powder bed fusion processing

This dataset contains simulated cross-sections of laser powder bed fusion grain structures produced using the microstructure model ExaCA, in turn using time-temperature history data produced using the heat transport model AdditiveFOAM. These predictions show the grain structure using various permutations of hatch spacing and nucleation density. Also contained in the dataset are the input files necessary to reproduce the results. AdditiveFOAM (https://github.com/ORNL/AdditiveFOAM) and ExaCA (https://github.com/LLNL/ExaCA), both open source software, are required to reproduce the results in this dataset using the given input files. This DOI was updated 12/09/2025.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In situ Visible Light and Thermal Imaging Data from a Laser Powder Bed Fusion Additive Manufacturing Process Co-Registered to X-ray Computed Tomography and Fatigue Data

This dataset is comprised of in situ sensing data collected during a laser-based powder bed fusion additive manufacturing process, as well as rasterized scan path information, post-build X-ray computed tomography (XCT), and fatigue test results. A total of 64 cylinders, approximately 15 mm in diameter and 102 mm tall, were printed out of stainless steel 316H on a Colibrium Additive Concept Laser M2 Series 5 machine. Parameters known to produce dense material were used to construct 56 of these cylinders, while the remaining 8 cylinders were printed with relatively high energy density parameters prone to producing keyhole pores. In addition, two spatter generation blocks were constructed upstream of the 64 cylinders such that ejecta produced during the melting of the spatter generators were stochastically seeded onto the 64 cylinders. Based on previous experiments, these spatter particles were theorized to produce stochastic lack-of-fusion pores. During the construction of the build, high-resolution images of reflected light in the visible spectrum were captured both before and after recoating for each print layer. Additionally, temporally integrated thermal imaging in the near infrared spectrum produced integrated sum and max images on a layerwise basis. The multimodal in situ data has been co-registered to the build plate coordinate system, allowing for identification of process anomalies (e.g., spatter particles) apparent in the two sensors. Following construction of the build, the cylinders were subjected to XCT to identify internal flaws, and the resulting data have also been registered to the build plate coordinate system. Finally, 60 of the 64 cylinders were machined into fatigue coupons conforming to ASTM E466 and subsequently subjected to either high- or -low-cycle fatigue testing. The results of the fatigue tests have also been included in the dataset, and the XCT data corresponded to the approximate location of the gauge sections of the machine fatigue specimen geometry.

42 ENGINEERING↗
DOE OSTI2024

Height-resolved emission spectroscopy and high-speed imaging of the TiAl6V4 vapor plume under laser powder bed fusion conditions

Optical emission spectroscopy is increasingly used as an in situ monitoring technique during laser powder bed fusion (LPBF) because plume emission holds elemental information not found in other in situ sensing techniques. This work explores the shape, stability, and temperature of the emission plume above the melt pool of Ti6Al4 V undergoing laser scans under LPBF-like processing conditions, using high-speed video and height-resolved spectroscopy to study the details of plume dynamics. Optical emission spectroscopy is conducted in the 480 nm to 525 nm region, where Ti emission is strong, with 0.3 mm vertical resolution above the baseplate. The Boltzmann plot method is used to determine temperature at each probed elevation, which indicates that the hottest location of the plume is occasionally elevated 0.3 mm to 0.6 mm above the scanning surface. The results show that the plume shape, stability, temperature, and spectra are highly dependent on the processing conditions. We highlight some of the complexities of optical emission spectroscopy and discuss potential challenges for implementing optical emission spectroscopy across an entire build.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Neutron powder diffraction, Mossbauer Spectroscopy and Optical Spectroscopy to study magnetic and nuclear lattices in Fe-based oxychlorides Ca2FeO3Cl, Sr2FeO3Cl and Sr3Fe2O5Cl2

Data for Neutron Diffraction, Mossbauer Spectoscopy and Optical Spectroscopy are contained on all three samples (Ca2FeO3Cl, Sr2FeO3Cl, and Sr3Fe2O5Cl2). Mossbauer data are in the folder "MossbauerSpectroscopy". This contains details of files and examples to read the data. The Optical Spectroscopy are in the folder "AbsorptionData", this contains one file with explanatory headers. The neutron diffraction data are in the "NeutronDiffractionData" folder. The data was collected on the HB-2A powder diffractometer at HFIR. The autoreduced files are corrected using a vanadium standard and are in arbitrary intensity units. The RawData folder contains the uncorrected data with metadata for motor positions and temperature. All measurements were collected with a constant neuton wavelength of 2.41 Angstrom. An excel spreadsheet "NeutronDiffractionData_IPTS-29118_summary" contains details for each scan. Sr3Fe2O5Cl2 data were collected at only room temperature. Ca2FeO3Cl and Sr2FeO3Cl data were collected at 4K and room temperature. The autoreduced .dat fileformat is three columns corresponding to: Two-theta, Intensity and Intensity_error.

fe-based oxychlorides↗
DOE OSTI2025

Raw data for KCoAsO4 powder

Contains neutron powder data on nuclear and magnetic diffraction as well as low and high energy inelastic neutron scattering for KCoAsO4

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Simulating Properties of Metal Powder Beds Used for Additive Manufacturing of Parts in Semiconductor, Solar and Display Equipment. Final CRADA Report

Final Report CRADA No. TC02261 Date Technical Work Ended: 7/31/19. This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Applied Materials, Inc. to adapt and utilize LLNL-developed particle-scale simulation models to investigate and improve powder-bed formation for additive manufacturing of parts of interest to Participant in semiconductor, solar and display equipment. The original term of the CRADA was one (1) year. A No-Cost Time Extension extended the CRADA for two months through July 31, 2019.

14 SOLAR ENERGY↗
DOE OSTI2021

Multi-fidelity thermal modeling of laser powder bed additive manufacturing

Laser powder bed fusion (LPBF) Additive manufacturing (AM) has attracted interest as an agile method of building production metal parts to reduce design-build-test cycle times for systems. However, predicting part performance is difficult due to inherent process variabilities. This makes qualification challenging. Computational process models have attempted to address some of these challenges, including mesoscale, full physics models and reduced fidelity conduction models. The goal of this work is credible multi-fidelity modeling of the LPBF process by investigating methods for estimating the error between models of two different fidelities. Two methods of error estimation are investigated, adjoint-based error estimation and Bayesian calibration. Adjoint-based error estimation is found to effectively bounding the error between the two models, but with very conservative bounds, making predictions highly uncertain. Bayesian parameter calibration applied to conduction model heat source parameters is found to effectively bound the observed error between the models for melt pool morphology quantities of interest. However, the calibrations do not effectively bound the error in heat distribution.

36 MATERIALS SCIENCE↗