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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

From lab to lamp: Understanding downconverter degradation in LED packages

Downconverters, primarily inorganic phosphors, are critical components in white solid-state LED-based lighting and liquid crystal display backlights. Research efforts have led to a fundamental understanding of a downconverter's absorption, photoluminescence, and efficiency as a function of composition, structure, and processing conditions. However, considerably less work has focused on the reliability of phosphors once they are incorporated into LED packages. Solving these issues is often the final step before the commercialization of new materials, but the significant resources and time required to evaluate and mitigate materials failure are rarely discussed in the literature. In this Perspective, we discuss the need for conducting downconverter reliability testing and the potential of accelerating, screening, and understanding downconverter failure modes. Our focus highlights the mechanisms of failure and discusses how this influences materials selection and the design of different LED packages. We also stress the potential for accelerated reliability testing protocols and note the potential role first-principles calculations and data-driven models could play in establishing the compositional-processing trends for different aspects of downconverter reliability. In conclusion, we close with possible research directions that could improve downconverter reliability and emphasize the importance of assessing a material's (chemical) stability where multiple manufacturing and processing steps can dictate system performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Microstructure Alignment Effects from Engineered Cooling during Additive Manufacturing of Alnico Magnets from Prealloyed Powder

Alnico is a rare-earth free; permanent magnet (PM) which maintains its saturation magnetization while at temperatures up to 550°C but lacks the coercivity and energy product needed for a wide range of demanding applications. With an optimal set of processing and manufacturing techniques, Alnico could replace Dy-free Nd-Fe-B magnets in certain applications if the microstructure is textured in a $\langle$001$\rangle$ direction. Additive manufacturing (AM) of near-net-shape magnets may provide such texture. To investigate the possibility, directed-energy deposition (DED) in conjunction with an actively cooled substrate was used to build samples with a compositionally modified, gas-atomized, Alnico 8 alloy. The resulting samples were solutionized and quenched, followed by magnetic annealing and a heat treatment. Magnetic properties and microstructures are compared to previous work.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A systematic study and framework of fringe projection profilometry with improved measurement performance for in-situ LPBF process monitoring

Fringe Projection Profilometry (FPP) is a cost-effective and non-invasive technology that has been shown to measure finer features. Here, in this work, we developed an in-situ FPP method to measure the dynamic topography of powder bed and printed layer during Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A systematic study towards developing a comprehensive framework of LPBF-specific FPP is demonstrated to enhance and evaluate the performance of applying FPP for in-situ LPBF monitoring, including 1) a modified sensor model with localized correction; 2) improved phase unwrapping with FFT filtering 3) quantitative uncertainty analysis; and 4) experimental validation with ex-situ characterization. The developed LPBF-specific FPP system and methods are implemented on a commercial LPBF-AM machine, achieving better accuracy, more robustness, and increased field of view while maintaining sufficient measurement range and decent resolution, in contrast to literature methods. The established FPP framework will facilitate the development of closed-loop control strategies for advancing LPBF based AM.

42 ENGINEERING↗
DOE OSTI2021

Computational study of the effect of core–skin structure on the mechanical properties of carbon nanofibers

The effect of the core–skin structure on the mechanical properties of carbon nanofibers is investigated in large-scale molecular dynamics simulations of tensile deformation of carbon nanofibers with the core–skin and homogeneous structures. Contrary to an established notion of the deleterious effect of the skin layer on the strength of carbon fibers, the presence of a high-quality skin layer is found to increase both the Young’s modulus and tensile strength of the nanofiber. A detailed analysis of the fracture process indicates that the nanofiber strengthening is related to the ability of skin layer to suppress crack nucleation at the core–skin interface. Furthermore, the computational predictions suggest that the design of new approaches to carbon fiber manufacturing and processing leading to the generation of a high-quality skin layer while avoiding the introduction of structural defects at the core–skin interface may yield a significant enhancement of the mechanical properties of carbon fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Review of the Influence of Processing Parameters on ODS Steels Produced via Additive Manufacturing Techniques

Abstract This paper reviews current observations regarding processing conditions for oxide dispersion-strengthened steels consolidated through additive manufacturing techniques. Variations in ODS steels observed across process parameters include changes in grain size, grain texture, oxide size, density of oxides, porosity, melt pool characteristics, and mechanical properties. These properties were then compared across techniques to understand which techniques and processing conditions lead to the highest strength, ductility, and oxide density. Current literature suggests that a mix of grain types, in the form of either morphology or phase, can significantly increase the strength of printed ODS steels. Meanwhile, the most ductile samples, regardless of consolidation technique or matrix material, were made from feedstock with oxide additions located on the powder surface. Reported grain and oxide sizes were plotted against the ratio of laser power to scan speed, volumetric energy density, and normalized enthalpy. No strong correlation between these values and microstructural features was observed. The plots that were made suggest that a larger data set, more in-depth representative equations, and more defined material properties as a function of specific feedstock used are necessary to determine a value that can be correlated to the printed ODS steel microstructure.

deJong, Matthew↗
DOE OSTI2023

Downselection and Basic Properties of Additively Manufactured ODS Alloys

In the AMMT program the work package for development of new materials aimed to explore the advanced manufacturing techniques that are feasible for the manufacturing of advanced materials components. A merit-based feasibility study was attempted to identify an accelerated development path for dispersion strengthened (ODS) alloys by creatively combining additive manufacturing (AM) technologies with the recent advances in ODS materials and traditional manufacturing technologies. For the fiscal year, the primary tasks were focused to develop additive manufacturing (AM) and post-build processing route for oxide dispersion strengthened (ODS) ferritic (Fe-Cr alloy or 14YWT) and austenitic (Fe-Cr-Ni alloys or 316L and 316H) alloys and to perform basic microstructural and mechanical characterizations to provide feedbacks to the alloy and processing design. Further, the multi-laboratory effort created collaboratively a decision criteria matrix to evaluate and downselect the new materials processed by advanced manufacturing methods. This report is to describe the ODS alloy processing routes combining AM processes and post-build thermomechanical treatments, mechanical and microstructural characteristics of the newly developed materials, and the application results of the decision criteria matrix for the AM ODS alloys including a downselected material and feasible processing route. Key mechanical test results including tensile strength, tensile ductility, and fracture toughness data and are reported and explained. Higher strength was measured from the ferritic ODS alloys, while higher ductility and fracture toughness were measured from the austenitic ODS alloys. Many of the decision criteria were scored the same for the AM ferritic and austenitic ODS alloys, however, the generally known fact that the austenitic alloys have higher corrosion resistance and significantly better ductility. Although these scores are not significantly different to make them highly discernable, the austenitic ODS alloys were downselected to be the primary materials group in the future research on ODS materials in AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Controlling melt flow by nanoparticles to eliminate surface wave induced surface fluctuation

The high surface roughness is one of the major challenges encountered in laser metal additive manufacturing (AM) processes, which is closely related to the melt flow behavior. However, how to control the melt flow in laser metal AM processes to improve surface finish is unknown. Here we reveal the effects of nanoparticles on melt flow behavior at every location of melt pool during laser metal AM process for the first time using Al6061 + TiC nanoparticles system and achieve significant improvement of surface finish by using TiC nanoparticles to control the melt flow and damp the surface wave. Based on the in-situ x-ray imaging observation, the surface wave is fully damped after adding TiC nanoparticles, compared with only 56% damping without nanoparticles during LPBF of Al6061. Our in-depth in-situ x-ray imaging analysis and viscosity measurement enable us to identify that nanoparticle-induced increase of viscosity causes the fully damping of the surface wave by (1) increasing the internal fluid friction for more efficient wave amplitude reduction, (2) controlling the melt flow to increase the surface wave number, (3) controlling the melt flow to increase the wave damping time. Furthermore, we also quantified the relative contributions of increasing fluid friction, increasing wave number, and increasing damping time to wave damping, which account for 61%, 25%, and 14%, respectively. Furthermore, our research provides the mechanisms and potential method to address the surface finish challenge in laser metal AM processes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Which way does the dendrite grow? Competition among epitaxy, preferred growth direction, and thermal gradients in powder bed fusion additive manufacturing

The as-processed microstructure of metal alloy parts manufactured through laser powder bed fusion (LPBF) is heavily derived from the cellular dendritic solidification. The growth direction of dendrites within the melt pool is determined through competition among epitaxial growth, preferred growth directions, and maximum thermal gradients. However, the dominant factor and the specific role of each in developing melt pool microstructures remain unknown. Here, in this study, we performed single laser track scans on an SS316L single crystal substrate and combined experimental characterization of microstructure and crystal orientations with Computational Fluid Dynamics simulations of thermal gradients to evaluate the role of each factor in determining dendritic growth direction and evolution. Our results reveal that epitaxial growth dominates microstructure development by preferentially growing along a single 〈100〉 variant of the single crystal substrate adjacent to the melt pool boundary. Under LPBF’s highly curved and rapidly evolving thermal field, this preferential dendrite variant selection and its continued growth from the melt pool boundary to the centerline are governed by the local temperature gradient magnitude at the solid-liquid interface, rather than by the instantaneous maximum temperature gradient direction alone. Using these findings, we successfully predict changes in the dendrite growth direction with changing laser scan direction on a single crystal substrate, and show that the geometric melt pool centerline can deviate from the microstructural centerline because asymmetric local temperature gradient magnitudes transiently limit growth, resulting in different dendrite travel distances on each side of the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Method and device for a high temperature vacuum-safe solder resist utilizing laser ablation of solderable surfaces for an electronic module assembly

A process for manufacturing an electronic component having attaches includes providing a first component having a first attach, forming trenches on a portion of the first attach with a laser to form a solder stop, and providing a second component comprising a second attach. The process further includes providing solder between the first attach and the second attach to form a connection between the first component and the second component, where the trenches contain the solder to a usable area. A device produced by the process is disclosed as well.

Stabach, Jennifer↗
DOE OSTI2023

Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis Monte Carlo models for materials processing

Abstract SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Additive manufacturing for electrocaloric terpolymer thin films

Current heating, venting, and air conditioning (HVAC) systems have drawbacks of high energy consumption, large CO 2 emissions, and low efficiency. Electrocaloric (EC) cycles present an eco-friendly alternative by converting thermal energy to electrical energy. Defect-free thin films with uniform thickness are required to achieve optimal EC performance. A scalable thin film fabrication process is essential for integrating EC cycles into HVAC systems. This study introduces EC thin films prepared by electrospray (ES) processing, a manufacturing method that deposits EC polymer layer by layer using high voltage. The resulting films show superior thickness control, smoother surfaces, and improved thermal and electrical properties compared with solution casting. In addition, post-annealing at 120°C enhances the thermal and EC performance, with films achieving a temperature change (ΔT) of 3.6°C at 100 MV/m when tested near room temperature. With the potential for future scalability, the ES method offers a promising approach for fabricating EC thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimal toolpath generation system and method for additively manufactured composite materials

The present disclosure relates to a system for optimizing an additive manufacturing (AM) process. The system may use a printing component for using a material to form a component in a layer-by-layer process. An electronic controller may control movement of one of the printing component or a substrate on which the component is being formed, in a manner to optimize a toolpath for the printing component as each layer of the component is formed. Optimization operations are performed using an optimization subsystem which enables manufacturability constraints, as well as optimized toolpaths for each layer of the component, to be defined using contours of a level-set function. The level-set function may be used to define the optimized toolpaths within a fixed, predetermined grid, and the optimized toolpaths then used to generate suitable code for controlling movement of the printing component relative to the substrate to create the part or structure in a layer-by-layer process, using the optimized toolpaths.

Lewicki, James↗
DOE OSTI2020

Real-time cure monitoring of fiber-reinforced polymer composites using infrared thermography and recursive Bayesian filtering

Despite the desirable characteristics of fiber-reinforced polymer (FRP) composites, their utilization in high volume production industries is limited by a lack of efficient manufacturing techniques. Monitoring the curing process of these composites can help with improving the quality and efficiency of the manufacturing process. This article discusses a method that uses Kalman-filter-based fusion of the information obtained from infrared thermography (surface temperature measurements) and a heat conduction model to estimate degrees of cure and internal temperatures of curing FRP composite parts in real time. The effectiveness of the methodology is demonstrated by successfully monitoring the curing of an FRP composite part in a laboratory experiment. Finally, the proposed methodology is a crucial step towards identifying anomalies in the curing process that negatively impact the quality of FRP composite parts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

HYBRID COMPOSITES VIA CO-EXTRUSION ADDITIVE MANUFACTURING-COMPRESSION MOLDING FOR PERFORMANCE OPTIMIZATION

The growing demand for hybrid polymer composites with multifunctional properties has led to the development of various hybridization techniques, such as multi-material compounding and controlled laminate stacking sequence. In this study, a novel hybrid manufacturing approach was used by integrating a multiplexing extrusion system (MExS) based on additive manufacturing with subsequent compression molding process. This technique enabled the co-extrusion of different materials during the additive manufacturing process to fabricate composites with tailored performance. The developed hybrid composite featured a skin layer of glass fiberreinforced polycarbonate (PC/GF) encapsulating a carbon fiber-reinforced acrylonitrile butadiene styrene (CF/ABS) core. The structure was engineered to promote improved thermal and impact resistance at the surface, supported by a stiff core for enhanced overall mechanical integrity. Mechanical, thermal and morphological properties of the hybrid composites were investigated to understand trade-offs in performance compared to a single-material system. The results demonstrate that this approach enables the production of multifunctional composites suitable for applications such as automotive body panels and protective housings, where a balance of weight, mechanical strength, and thermal performance is essential.

Wasti, Sanjita [ORNL]↗
DOE OSTI2022

Interlayer fusion bonding of semi-crystalline polymer composites in extrusion deposition additive manufacturing

This work focuses on the evolution of interlayer fracture toughness properties of fiber-reinforced, semi-crystalline polymers in the extrusion deposition additive manufacturing (EDAM) process. Further, this work bridges the gap between the additive process conditions (time-temperature history) and the effective layer-to-layer fracture properties developed within a printed component. This is the first step to predict delamination that can occur during printing, during cooling to room temperature after printing, and during service performance of an additively manufactured geometry. A phenomenological model is developed for fusion bonding of semi-crystalline polymer matrix composites by coupling the interdiffusion of polymer chains with the evolution of polymer crystallinity. While the interdiffusion is captured by reptation theory of polymer dynamics, the evolution of crystallinity is modeled by phenomenological crystallization kinetics and crystal melting dynamics. Further, a methodology is developed to determine the critical strain energy release rate, G IC of the interlayer interface and experiments are conducted utilizing the double cantilever beam fracture test geometry. In conclusion, predictions of GIC as a function of thermal history are compared with experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Discrete Dendrite Dynamics Model for Epitaxial Columnar Grain Growth in Metal Additive Manufacturing with Application to Inconel

Epitaxial columnar grain growth is a prevalent microstructural feature in the additive manufacturing (AM) of metal components such as Inconel, with cubic unit cell crystal lattice structure (face centered cubic (FCC) or body centered cubic (BCC)). These columnar grains evolve from the partly molten grains in the substrate or the solidified metal. This work proposes an efficient model to simulate the competitive growth of epitaxial columnar dendritic grains. The proposed model tracks the dynamic changes in the dendrites emanating from discrete points along the solid/liquid interface of a quasi-steady melt pool (MP). These dynamic changes include convergence and divergence of growing dendrites. The model is extended to predict the microstructure of large 3D parts and experimentally validated by comparing the simulation results for laser powder bed fusion (L-PBF) and wire-arc additive manufacturing (WAAM) processes. The microstructure and pole figures are predicted for Inconel 718 samples produced by L-PBF and Inconel 740H samples produced by WAAM processes. Finally, the model predictions compare well with the observed microstructure and pole figures results for both the L-PBF and WAAM processes.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗