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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Future MAUS payload and the TWIN-MAUS configuration

The German MAUS project (materials science autonomous experiments in weightlessness) was initiated in 1979 for optimum utilization of NASA's Get Away Special (GAS) program. The standard MAUS system was developed to meet GAS requirements and can accommodate a wide variety of GAS-type experiments. The system offers a range of services to experimenters within the framework of standardized interfaces. Four MAUS payloads being prepared for future space shuttle flight opportunities are described. The experiments include critical Marangoni convection, oscillatory Marangoni convection, pool boiling, and gas bubbles in glass melts. Scientific objectives as well as equipment hardware are presented together with recent improvements to the MAUS standard system, e.g., a new experiment control and data management unit and a semiconductor memory. A promising means of increasing resources in the field of GAS experiments is the interconnection of GAS containers. This important feature has been studied to meet the challenge of future advanced payloads. In the TWIN-MAUS configuration, electrical power and data will be transferred between two containers mounted adjacent to each other.

Staniek, S.↗
DOE OSTI2025

Harnessing on-machine metrology data for prints with a surrogate model for laser powder directed energy deposition

In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive surrogate model of the 3D printing process. By employing Dynamic Mode Decomposition with Control (DMDc), a data-driven technique, we capture the complex physics inherent in this extensive dataset. This physics-based surrogate model emphasizes thermodynamically significant quantities, enabling us to accurately predict key process outcomes. The model ingests 21 process parameters, including laser power, scan rate, and position, while providing outputs such as melt pool temperature, melt pool size, and other essential observables. Furthermore, it incorporates uncertainty quantification to provide bounds on these predictions, enhancing reliability and confidence in the results. We then deploy the surrogate model on a new, unseen part and monitor the printing process as validation of the method. Our experimental results demonstrate that the predictions align with actual measurements with high accuracy, confirming the effectiveness of our approach. Furthermore, this methodology not only facilitates real-time predictions but also operates at process-relevant speeds, establishing a basis for implementing feedback control in LP-DED.

Digital twins↗
NASA NTRS1986

Acoustic-Emission Weld-Penetration Monitor

Weld penetration monitored by detection of high-frequency acoustic emissions produced by advancing weld pool as it melts and solidifies in workpiece. Acoustic emission from TIG butt weld measured with 300-kHz resonant transducer. Rise in emission level coincides with cessation of weld penetration due to sudden reduction in welding current. Such monitoring applied to control of automated and robotic welders.

Maram, J.↗
DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗
DOE OSTI2025

Effects of shielding gas and spot reduction on humping suppression in high-speed laser welding

High-speed laser welding is a crucial process to enhance the production rate of fuel cell fabrication. However, exceeding a critical welding speed leads to defect formation such as humps and root concavities, which degrade weld quality and mechanical performance. This study employed shielding gas and spot reduction approaches to suppress these defects. The relationships between individual defect types and their influence on weld strength were systematically examined. Moreover, in situ high-speed synchrotron X-ray imaging was employed to comprehend the mechanisms of humping mitigation by shielding gas through analysis of instantaneous keyhole and melt pool dynamics. The observations reveal that shielding gas mitigates humping by shortening the molten pool through enhanced surface heat convection and by altering surface tension to prevent melt flow collisions. The effects of shielding gas and spot reduction were further incorporated into the dimensionless humping index (π h ) that describes the humping formation tendency. These findings provide mechanistic insights and quantitative guidance for defect control strategies in high-speed laser welding.

08 HYDROGEN↗
DOE OSTI2025

Effect of Zr and Sc additions on coarsening- and creep resistance of AlSi10Mg fabricated by laser powder bed fusion

Microstructure and creep properties are studied in a eutectic AlSi10Mg alloy modified with Zr and Sc additions (Al-9.8Si-0.32Mg-0.70Zr-0.23Sc, wt%) manufactured through laser powder-bed fusion (L-PBF). Three types of Zr/Sc-bearing powders - elemental, master-alloy, and pre-alloyed - are employed in the fabrication process, with the pre-alloyed powders providing the highest incorporation of Zr and Sc in the Al matrix. Here, the as-printed alloy exhibits a fine cellular Al-Si eutectic structure which fragments and coarsens into micron-sized Si particles during aging at 300 ºC, leading to a steady drop in alloy microhardness between 0.1 and 1000 h. Coarsening of the eutectic Si phase during aging is not measurably affected by Zr and Sc in solid solution, which precipitate during aging and increases strength, compensating weakening from Si coarsening between 1 and 200 h at 300 ºC. Atom-probe analysis in the peak-aged condition (96 h/300 °C) confirms the presence of Al 3 (Sc,Zr) secondary nano-precipitates with an average radius of 1.0 nm and some Si solubility. Micron-sized grains are present throughout the alloy, with ultra-fine-grained regions at the melt pool boundaries, neither of which coarsen during long-term aging at 300 ºC. Under creep conditions at 300 °C, the Zr/Sc-bearing alloy with Al 3 (Sc,Zr) nano-precipitates exhibits power-law behavior, with a high apparent stress exponent (n a = 9) and a high threshold stress (σ th = 43 MPa), exhibiting nearly double the strength of a Zr/Sc-free AlSi10Mg control alloy (σ th = 22 MPa).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of laser melt schedule on the microstructure of additively manufactured IN718 Superalloy

Laser powder bed fusion (L-PBF) has enabled the fabrication of geometrically complex metallic structures and components that are challenging to producing using conventional manufacturing approaches. The site-specific and far from equilibrium thermal conditions of L-PBF offer the potential to facilitate multi-length scale design of structure and properties across the atomic-through macro-levels. However, L-PBF systems face scalability challenges due to throughput constraints. Laser rotary powder bed fusion (L-RPBF) systems are being investigated as a solution to enhance the deposition rates compared to conventional L-PBF. Rotary systems also offer additional flexibility for controlling the time structure of melting through laser interleaving on alternating layers. Here, in this study, IN718 test samples were printed using single-laser or interleaved dual-laser configuration in a L-RPBF system to investigates the effect of process settings and melt-interleaving on as-fabricated microstructure. The microstructural evolution, such as grain size and crystallographic texture, was assessed by determining variations in the melt-pool shapes. Laser interleaving leads to a reduction in average grain size compared to single laser by ∼ 40 % at high power (400 W) and by ∼36 % at medium power (370 W). Results presented here identify key challenge for obtaining uniform microstructures and barriers for the broader adoption of high-deposition rate L-RPBF.

Dual-laser↗
DOE OSTI2025

Real-time single-element-detection structured illumination optical metrology for laser powder bed fusion

Laser powder bed fusion (LPBF) is a type of metal additive manufacturing which could benefit from improved process monitoring to improve quality control. We demonstrate, for the first time to our knowledge, the coaxial monitoring of melt track formation in steel powder with spatial frequency modulation imaging (SPIFI), an enhanced-resolution imaging technique which uses a photodiode to record one-dimensional images. Using a custom live-display software and a high-speed SPIFI geometry, we offset the SPIFI field of view from the fusing beam to monitor different regions of the LPBF melt pool and surrounding area. This demonstrates the potential of SPIFI to monitor spatial features within the melt pool in real-time with increased data efficiency.

Hunter, Scott (ORCID:0009000886150312)↗
DOE OSTI2025

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Controlling mechanical properties of laser powder bed fused AlSi10Mg through manipulation of laser scan rotation

The microstructure and mechanical properties of laser powder bed fused (LPBF) AlSi10Mg alloys can be controlled by many processing parameters. This study focuses on the scan rotation angle, α, between adjacent layers, and establishes the relationship between α and tensile behavior of the as-built LPBF-processed AlSi10Mg alloy. Near-full density cubic coupons were manufactured using the same processing parameters but with systematic variation of α from 0° to 90°. Microscopic observations and X-ray diffraction analysis showed that differences among various coupons mainly include orientations of the melt pools with respect to the build direction and development of the crystallographic texture. The α=0° coupon and α=30° coupon showed the highest and lowest texture index, although the overall crystallographic texture was mild. Tensile specimens were manufactured horizontally and vertically using either α=0° or α=30°, but with various first layer laser direction with respect to the build plate. Notably, the α=0° specimen that was tested along the laser scan direction showed the largest yield strength (283 MPa) and highest tensile ductility (10.1 %). Quantitative image analysis and fractography were performed on all specimens. Results showed that the melt pool orientation with respect to the tensile direction affected the tensile behavior across the different specimens. This was closely related to the localized strain distribution within the melt pool and along the melt pool boundary for the different melt pool orientations observed. Further, these results demonstrate that the laser scan rotation angle between layers can be used to fine tune the mechanical properties of LPBF AlSi10Mg alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The influence of laser power modulation on melt pool dynamics in laser powder bed fusion

While the majority of laser powder bed fusion (LPBF) metal additive manufacturing uses a continuous wave (CW) laser heat source, some commercial applications of LPBF additive manufacturing instead involve the modulation of the laser power on tens-of-microsecond timescales as an adjustable process variable. This article reports the use of in situ, high speed x-ray and optical imaging to probe melt pool fluid flow, defect formation, and nearby powder motion during LPBF with both modulated and CW laser heat sources. We observe melt pool dynamics unique to modulated laser melting even at very high duty cycles that are related to fluctuations in vapor depression depth, complex pore formation mechanisms, and changes to denudation physics when compared to CW melting. These behaviors are present in Ti–6Al–4V, 316L stainless steel, and AL1100 alloys but vary slightly as a function of material, indicating a substantial dependence on the viscosity and surface tension of the liquid metal. While high duty cycles produce weld tracks of comparable quality to CW melting, lower duty cycles introduce substantial defect concentrations. At intermediate duty cycles, careful control of modulation parameters can repeatably and precisely yield one pore per laser pulse, suggesting a method for intentionally inserting engineered porosity at specific sites during an LPBF build.

3D printing↗
DOE OSTI2026

Nondestructive ultrasonic characterization of a triple-weld-bead wire arc additively manufactured ER70S-6 S-curved wall

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Formation mechanisms of Sn-rich δ phase and its role in strengthening Cu-10Sn manufactured by laser powder bed fusion

Cu-Sn alloys produced via laser powder bed fusion (L-PBF) additive manufacturing (AM) have gained significant attention because they combine the advantages of AM relevant to intricate component design with outstanding combinations of strength, ductility, and resistance to wear and corrosion. However, a detailed understanding of the microstructure that contributes to the enhancement of the mechanical properties of L-PBF Cu-10Sn alloys remains unclear. In particular, there is a lack of understanding of the formation mechanisms of the Sn-rich δ phase commonly observed in Cu-10Sn. This study reveals two distinct variants of the δ phase possessing unique morphological characteristics. These characteristics are attributed to the local solidification conditions inherent to the melt pool boundaries versus those at the interiors of melt pools. A phase transformation pathway that elucidates the origin of the morphological variants of the δ phase from the Sn-rich metastable phases during the cyclic heating of the AM process is proposed. We report superior mechanical properties in L-PBF Cu-10Sn compared to those of conventionally manufactured counterparts due to the synergistic contributions from grain boundaries, dislocations, and the δ phase. Notably, the δ phase alone contributes approximately 22 % to the overall strength observed in the L-PBF Cu-10Sn alloy. The discovery of two types of distinct Sn-rich δ phase offers key insights into precise microstructural control in AM Cu-Sn alloys to enhance mechanical properties, providing practical strategies for improving material performance for diverse applications in automotive, aerospace, and machinery industries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A detailed study of pre-heating effects in electron beam melting powder bed fusion process

Metal-based additive manufacturing processes, such as powder bed fusion with electron beam (PBF-EB) process, also referred to as electron beam melting (EBM), can produce high-density parts with minimal residual stresses due to the uniform and coherent preheating of the powder bed. However, understanding and controlling the multiple stages of preheating is required to enable the production of high-quality, consistent parts of various materials. This work presents a large-scale, multi-layer, three-dimensional numerical analysis focused on studying the preheating stages for predicting thermal history during the PBF-EB process. The model follows a continuous multi-stage cyclic process, that incorporates all the main stages of the PBF-EB process for 316 L stainless steel. This includes the gradual deposition of a new powder layer, the first and second preheating levels of the powder bed, and the energy deposition during melting (excluding the actual melt-pool behavior simulation). The model employs an adaptive time-scaling approach that automatically adjusts the energy deposition for each solution time-increment. This allows for localized changes in time-resolution over an otherwise computationally expensive multi-layer procedure. The material property variations are also taken into account, with an emphasis on the subtle irreversible changes in powder effective thermal conductivity after the two requisite preheating stages of the powder bed. This effect is studied using simplified conductivity models from the literature for partially sintered powder, validated by a dedicated experiment and numerical simulation. The large-scale model is then used to estimate the actual temperatures during first and second preheating levels for 316 L steel, which is not yet fully supported commercially for PBF-EB. Model predictions are corroborated by experiments, using and analyzing IR images, taken at the completion of each layer by the machine’s built-in infrared camera. The current model also incorporates a qualitative assessment for the effects of conductivity change during pre-heating, as well as evaluates the applicability of the time-scaling approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗
DOE OSTI2026

X-ray observation of individual Ti-6Al-4V spherical powder particle impact in an in-situ operando laser directed energy deposition system

Understanding the particle capture mechanism in the laser directed energy deposition additive manufacturing process provides a foundation for improving productivity and reducing material loss. Capturing this phenomenon is challenging due to its highly transient time interval. To analyze the impact behavior of spherical Ti-6Al-4V powder, a custom laser directed energy deposition system was designed to control the deposition of individual particles. Synchrotron X-ray imaging at 24 kHz monitored the impact dynamics of individual powder particles. A multi-physics model based on the Smoothed-Particle Hydrodynamics scheme supported the analysis by providing the temperature and velocity fields of the molten pool. Results revealed that in laser directed energy deposition, surface tension forces dominated the powder–molten pool interaction. Hydrophobic Ti-6Al-4V powder particles had an equilibrium contact angle of 121 degrees with their molten state. Furthermore, Ti-6Al-4V powder particles required a high impact velocity (6 to 12 m/s) to transition from oscillation to submergence behavior. Lastly, oscillating powder particles that impacted near the location of the laser beam exhibited faster melting, highlighting the contribution of the laser beam to the melting mechanism. This work lays the foundation for investigations of powder particle impact in laser directed deposition and supports the validation of numerical models of powder–molten pool interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Implementation of disruptive designs for gas turbine components using direct energy deposition additive manufacturing

This research aims to develop a framework for establishing the correlation between in-situ monitoring data, process parameters, and microstructure evolution in blown-powder laser-directed energy deposition (DED) additive manufacturing (AM). To achieve this, a comprehensive manufacturing framework has been developed, spanning from in-situ data acquisition, melt-pool simulation, microstructure modeling, and statistical microstructure quantification. A machine learning-based surrogate model is constructed to predict melt pool geometry directly from in-situ coaxial camera data. The surrogate model is trained using outputs from a high-fidelity melt pool simulation, which provides accurate melt pool dimension data under varying process conditions. The predicted melt pool geometry is then used as input to a microstructure model to predict microstructural features. To rigorously compare and analyze microstructures, the project introduces statistical metrics that quantify differences based on key features such as morphology and texture. Microstructures are represented using advanced statistical descriptors including angular chord length distribution, two-point spatial statistics, orientation distribution function, and global spherical harmonic. These representations are used to compute four distinct “dissimilarity scores” that quantitatively capture differences in texture and morphology. This framework is demonstrated to enable automated calibration of simulation parameters by minimizing discrepancies between simulated and target microstructures. The technology developed in this project enables direct correlation between in-situ monitoring data and resulting microstructure, paving the way for adaptive microstructure control in metal AM. This capability strengthens the connection between process parameters and final material properties, facilitating more precise and reliable material design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synthesizing intermetallic thermoelectric materials using metal flux growth method

With zero energy poverty by 2050 goals, exploring innovative energy technologies is essential. Thermoelectric materials (TEMs) have the potential to harness waste heat and convert it to electricity (e.g., for spacecraft power, sensors, and cryogenic cooling). Two limitations of thermoelectric compounds are their low efficiency and limited pool of materials. Optimizing the efficiency of TEMs is challenging due to the interdependent relationship between electrical and thermal conductivity. A deeper understanding of electronic properties and lattice thermal conductivity is necessary to “understand, predict and ultimately control” the thermoelectric properties of TEMs. Understanding the influence of light-atom-doping and intrinsic defects on the electronic properties of the f-element containing TEMs are important questions that need to be answered to design and synthesize TEMs with optimal parameters. The purpose of this work is to understand how doping f-element based TEMs with light elements, such as carbon and boron, would impact the crystal structure, bond lengths, band gaps, and thermoelectric characteristics. High-quality f¬-element containing intermetallic single crystals are grown in metal flux media. In molten metal flux growth method, one or more low-melting metals such as aluminum, gallium, tin, and bismuth are used in excess as the reaction medium. As these are solution-state reactions, we can use lower temperatures than solid-state reactions and isolate the kinetic products instead of the thermodynamically stable compound. Then these are characterized using X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, magnetization, electrical and thermal conductivities, and thermoelectric power.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗