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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cost of Using Laser Powder Bed Fusion to Fabricate a Molten Salt-to-Supercritial Carbon Dioxide Heat Exchanger for Concentrating Solar Power

Advances in manufacturing technologies and materials are crucial to the commercial deployment of energy technologies. We present the case of concentrating solar power (CSP) with molten salt (MS) thermal storage, where low-cost, high-efficiency heat exchangers (HXs) are needed to achieve cost competitiveness. Here, the materials required to tolerate the extreme operating conditions in CSP systems make it difficult or infeasible to produce them using conventional manufacturing processes. Although it is technically possible to produce HXs with adequate performance using additive manufacturing, specifically laser powder bed fusion (LPBF), here we assess whether doing so is cost-effective. We describe a process-based cost model (PBCM) to estimate the cost of fabricating a MS-to-supercritical carbon dioxide HX using LPBF. The PBCM is designed to identify modifications to designs, process choices, and manufacturing innovations that have the greatest effect on manufacturing cost. Our PBCM identified HX design and LPBF process modifications that reduced projected HX cost from $\$750$ per kilo-Watt thermal (kW-th) ($\$8$ /cm 3 ) to $\$350$ /kW-th ($\$6/$ cm 3 ) using currently available LPBF technology, and down to $\$220$ /kW-th ($\$4$ /cm 3 ) with improvements in LPBF technology that are likely to be achieved in the near term. The PBCM also informed a redesign of the HX design that reduced projected costs to $\$140$ –160/kW-th ($\$3$ /cm 3 ).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Laser melting modes in metal powder bed fusion additive manufacturing

In laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures and hence the properties of the build. To date, no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. Here, we distinguish process-based definitions of different melting modes from those based on postmortem evidence. The latter are mainly derived from the transverse cross-sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. Further, we highlight the significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Alumina-based filters made via binder jet 3D printing of alumina powder, colloidal silica infiltration, and sintering

Alumina-based, porous filter media was made via a binder jet 3D printing process consisting of an alumina powder printing step with subsequent heating, colloidal silica infiltration, drying, and sintering to consolidate particles yet retain a net open porous microstructure. The composites made were alumina-silica or alumina-mullite, where the silica sintering aid was used to densify and join the alumina particles. The resulting composite structures had open porosities in the 25–31 vol% range as measured by Archimedes density. Pressure drops were measured across the filter media at constant flow rates to compare disc shapes and complex, 3D printed filters based on the N95 design requirements. Complex, 3D-printed alumina composites were produced with acceptable pressure drops for N95 implementation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Properties of SiC-Si made via binder jet 3D printing of SiC powder, carbon addition, and silicon melt infiltration

In this work, we report the physical and mechanical properties of ceramic composite materials fabricated by binder jet 3D printing (BJ3DP) with silicon carbide (SiC) powders, followed by phenolic resin infiltration and pyrolysis (IP) to generate carbon, and a final reactive silicon melt infiltration step. After two phenolic resin infiltration and pyrolysis cycles; porosity was less than 2%, Young's modulus was close to 300 GPa, and the flexural strength was 517.6 ± 24.8 MPa. However, diminishing returns were obtained after more than two phenolic resin infiltration and pyrolysis cycles as surface pores in carbon were closed upon the formation of SiC, resulting in reaction choking and residual-free carbon and porosity. The instantaneous coefficient of thermal expansion of the composite was found to be independent of the number of phenolic IP cycles and had values of between 4.2 and 5.0 ppm/°C between 300 and 100°C, whereas the thermal conductivity was found to have a weak dependence on the number of phenolic IP cycles. While the manufacturing procedures described here yielded highly dense, gas impermeable, siliconized SiC composites with properties comparable to those of bulk siliconized silicon carbide processed according to conventional techniques, BJ3DP enables the manufacture of objects with complex shape, unlike conventional techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tailoring Thermal and Mechanical Performance Through Multimaterial Laser Powder Directed Energy Deposition of Copper and 17-4PH Stainless Steel

This study investigates the additive manufacturing (AM) processing, microstructural evolution, and resulting mechanical and thermal properties of multimaterial components combining 17-4PH stainless steel and pure copper (Cu) fabricated via laser powder directed energy deposition (LP-DED). Conventional tooling steels exhibit limited thermal conductivity, significantly constraining production throughput in high-volume processes. Incorporating Cu, with its superior thermal conductivity, could significantly enhance tool performance, though Cu and steel present metallurgical incompatibilities when processed via AM. A systematic investigation was conducted across compositions ranging from 0 to 100 wt% Cu, revealing critical thresholds influencing solidification behavior, defect formation, microstructure, hardness, and thermal transport. Optical microscopy, electron backscatter diffraction (EBSD), hardness testing, and thermal conductivity measurements provided comprehensive process–structure–property correlations. Severe hot cracking occurred at low-Cu contents (6–25 wt%), aligning generally well with crack susceptibility modeling, with an unexpected discrepancy at 25 wt%. Porosity remained low (≥99% dense) throughout the compositional spectrum. EBSD analysis revealed a transformation from columnar martensitic structures at low-Cu contents to equiaxed FCC Cu-dominated structures at higher Cu concentrations, highlighting the complex microstructural transitions driven by Cu-induced changes in solidification and phase stability. Hardness decreased from 330 HV (pure 17-4PH) to 62 HV (pure Cu), consistent with microstructural changes. Concurrently, thermal conductivity improved substantially from 13.5 W/m K to 367.9 W/m K, emphasizing Cu’s dominant role in thermal transport. The findings highlight the feasibility of leveraging compositional gradients between 17-4PH and Cu to achieve tailored tooling with optimized thermal and mechanical performance.

17-4PH↗
DOE OSTI2020

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

X-ray photoelectron spectroscopy was used to analyze Si/C 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 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 and show the expected silicon-carbon 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 II. Surface-modified Si/C/polyethylene glycol powder

X-ray photoelectron spectroscopy was used to analyze Si/C/polyethylene glycol 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 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 calcium and nitrogen signal, and show the expected silicon-carbon 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 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↗