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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Phase-Field Model for In-Space Manufacturing of Binary Alloys

The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Additive Manufacturing for Powering the Blue Economy Applications: A Tidal Turbine Blade Case Study: Preprint

As the marine renewable energy industry continues to expand, innovation in the manufacturing space must grow accordingly to reduce costs and ensure the economic feasibility of new technologies. Additive manufacturing, more commonly known as 3D printing, provides an alternative for rapid prototyping of marine hydrokinetic technologies, particularly supporting Powering the Blue Economy initiatives of the U.S. Department of Energy Water Power Technologies Office. This study explores the application of additive manufacturing in the development of marine hydrokinetic structures, focusing on material and printing method selection, design, and analysis of a 3D-printed spar for an axial-flow tidal turbine blade. Corrosion-resistant metals were deemed ideal due to the loads and harsh marine environment the blade would experience. Laser metal deposition methods were determined to be the most effective and scalable for the considered scale. The designed spar adapts its geometry to the blade - a feature uniquely suited to additive manufacturing - and is intended to serve as the blade's primary structural component. A finite element model was used to study stresses and deformations under loading conditions. The spar was manufactured using 316L stainless steel through direct energy deposition, and defects were assessed and recorded. Future efforts will include mechanical testing of the spar. This research establishes a benchmark process for using additive manufacturing in developing marine hydrokinetic structures, paving the way for future optimization and techno-economic analysis.

additive manufacturing↗
DOE OSTI2026

Demonstration and analysis of volumetric additive manufacturing via sub-orbital spaceflight testing

Computed Axial Lithography (CAL) represents a significant advancement in the emerging field of Volumetric Additive Manufacturing (VAM). CAL addresses key limitations of traditional photopolymer additive manufacturing technologies, by eliminating the need for layering and support structures. Unlike conventional methods, CAL prints components by illuminating all points within a desired geometry simultaneously, using tomographic reconstruction to form the object in a single step. This unique approach eliminates the relative motion between the object and the precursor material, enabling faster printing speeds and reducing the waste associated with support structures. However, CAL parts require post-processing steps before they can be utilized. CAL's core attributes make it particularly suited for In-Space Manufacturing (ISM), due to its fast fabrication times, wide breadth of materials it can use, and minimized footprint. CAL has been successfully demonstrated in microgravity during parabolic flight experiments. However to fully validate and understand CAL's behaviour in microgravity, all manufacturing and post-processing steps must be integrated. In June 2024, we conducted SpaceCAL Mission 3, testing this entire workflow on a suborbital flight aboard Virgin Galactic's SpaceShipTwo. During ~140 s of microgravity, the system autonomously manufactured and post-processed four parts using PEGDA700 resin. Post-flight analysis showed that 2/4 parts were recognisable, while others were distorted due to bubble formation from residual water droplets, off-axis optical aberrations, and non-uniform solvent rinsing. Despite these limitations, this study represents the first integrated CAL workflow in space, providing an initial experimental demonstration and analysis for closed-loop in-space manufacturing.

Waddell, Taylor [Department of Mechanical Engineer↗
DOE OSTI2024

On-demand fabrication of piezoelectric sensors for in-space structural health monitoring

Abstract Inflatable structures, promising for future deep space exploration missions, are vulnerable to damage from micrometeoroid and orbital debris impacts. Polyvinylidene fluoride-trifluoroethylene (PVDF-trFE) is a flexible, biocompatible, and chemical-resistant material capable of detecting impact forces due to its piezoelectric properties. This study used a state-of-the-art material extrusion system that has been validated for in-space manufacturing, to facilitate fast-prototyping of consistent and uniform PVDF-trFE films. By systematically investigating ink synthesis, printer settings, and post-processing conditions, this research established a comprehensive understanding of the process-structure-property relationship of printed PVDF-trFE. Consequently, this study consistently achieved the printing of PVDF-trFE films with a thickness of around 40 µ m, accompanied by an impressive piezoelectric coefficient of up to 25 pC N −1 . Additionally, an all-printed dynamic force sensor, featuring a sensitivity of 1.18 V N −1 , was produced by mix printing commercial electrically-conductive silver inks with the customized PVDF-trFE inks. This pioneering on-demand fabrication technique for PVDF-trFE films empowers future astronauts to design and manufacture piezoelectric sensors while in space, thereby significantly enhancing the affordability and sustainability of deep space exploration missions.

Instruments & Instrumentation↗
DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗
DOE OSTI2024

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Recyclable Materials for Resource Constrained Environments

In-space manufacturing exhibits severe limitations in resources as astronauts are only afforded with the materials that are brought on-board the space craft. Consequently, the use of recyclable and re-usable materials is paramount. Researchers at NLR leverage their expertise in polymer and recycling chemistry to develop material systems capable of high performance applications with intentional consideration on multi-life use through chemical recycling, mechanical recycling, bio-degradation, and thermoforming. Disclosed within this poster presentation are highlighted projects that illustrate several recyclable by design material systems that have been developed.

09 BIOMASS FUELS↗
DOE OSTI2024

Business Opportunities in Clean Energy Supply Chains: Guidebook for Small and Medium-Sized Automotive Suppliers

This is the final report for the referenced TCF award which ran from Oct. 2019 through Jan. 2024 in conjunction with the industry partner Swift Solar. The long duration of the program was due to several factors including the pandemic and a technical work stoppage due to changes in the scope. Additionally, Swift’s business focus shifted during the course of the program. As a result of these factors, this program underwent two distinct modifications that dramatically changed the work scope. The following report is organized into three separate sections, each of which addresses a distinct work scope. Those scope changes, what necessitated them, and any new tasks/milestones are given, briefly, at the top of each section. The work performed was research on the hybrid halide perovskites (HHP), both the absorber material itself as well as other material layers that are required in a full device stack. At the start of the period of performance, there were two distinct challenges that we sought to address: (1) a wide band gap absorber (>1.6 eV), and (2) a recombination layer for tandem devices that provided good sequestration of the individual cell absorber materials in their respective device layers. NREL had previously published, and patented, advancements in both of these areas and they were the focus of much of the work throughout the program. The auto manufacturing space is evolving quickly. Sales of various electrified vehicles (xEVs) continue to grow steadily, which has medium to long-term ramifications for the thousands of U.S. manufacturers and hundreds of thousands of workers that contribute to the domestic automotive supply chain. In tandem with this growth in xEV sales, domestic clean energy manufacturing is surging (both for the xEV supply chain and other technologies), with public incentives spurring billions in private sector investment. Moreover, the next 2–3 years will see new and expanded industrial facilities come online to make products like hydrogen electrolyzers, solar panels, batteries, advanced electronics—and will create new supply chain needs and business opportunities as they do. DOE’s Office of Manufacturing and Energy Supply Chains (MESC) and Argonne National Laboratory developed this report to help automotive manufacturers—alongside various business support partners— understand these trends and their response options, and to make the most of current federal assistance programs for manufacturers. These market changes may create opportunities for small- and medium-sized manufacturers (SMMs) to expand production, grow profit margins, and diversify their businesses. For instance, SMMs could take advantage of engineering and process design similarities with new end-use industries that might enable greater business growth and stability as markets continue to change.

14 SOLAR ENERGY↗
DOE OSTI2025

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗
DOE OSTI2025

Sierra Space Technology Collaboration-Advanced Manufacturing of Thermal Protection System Tiles for Space Plane Atmospheric Reentry

Thermal protection systems (TPS) constitute a major material, engineering, and manufacturing challenge for space access. Atmospheric re-entry generates very high heats and requires advanced materials to withstand such conditions. Combining the required materials and integrating them into the vehicle is a major engineering undertaking that often must use creative designs to accommodate the selected materials and systems. Likewise, the manufacture of TPS is costly and challenging; it requires a combination of materials in a range of complex and unique shapes with specialized process conditions. Compounding these challenges, for harsh re-entry profiles or on high heat flux regions of the vehicle, even state of the art TPS is effectively single use and thereby creating a strong economic incentive to improve the TPS materials, integration, and manufacture. This work focuses on the use of ceramic modifications to TPS materials thereby allowing multi flight capability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Advanced Manufacturing of Thermal Protection System Tiles for Space Plane Atmospheric Reentry

Thermal protection systems (TPS) constitute a major material, engineering, and manufacturing challenge for space access. Atmospheric re-entry generates very high heats and requires advanced materials to withstand such conditions. Combining the required materials and integrating them into the vehicle is a major engineering undertaking that often must use creative designs to accommodate the selected materials and systems. Likewise, the manufacture of TPS is costly and challenging; it requires a combination of materials in a range of complex and unique shapes with specialized process conditions. Compounding these challenges, for harsh re-entry profiles or on high heat flux regions of the vehicle, even state of the art TPS is effectively single use and thereby creating a strong economic incentive to improve the TPS materials, integration, and manufacture. This work focuses on the use of ceramic modifications to TPS materials thereby allowing multi flight capability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

What Would It Take to Manufacture Perovskite Solar Cells in Space?

Imagine: Astronauts land on the moon. They verify their arrival with mission control and perform system checks and validations. After the dust settles, they open the airlock of the landing vehicle and venture outside. A side hatch opens, and a flexible substrate slowly unfurls on a boom. A series of printer heads raster, hovering over the substrate and sequentially vapor-depositing the constituent layers of a perovskite solar module. In time, a 1-megawatt array has been manufactured on the moon and can now be connected to supply power to the Artemis Base Camp. This ambitious vision could someday become a reality.

14 SOLAR ENERGY↗
DOE OSTI2023

Recyclability of additively manufactured bio-based composites

As the flexibility, efficiency, and application space of additive manufacturing continues to grow, many have begun to investigate more sustainable feedstocks as well as options for the end of life of additively manufactured parts. This study examines the effects of mechanical recycling on additively manufactured parts from bio-based feedstock. Here, articles were printed on the Big Area Additive Manufacturing (BAAM) system at the Oak Ridge National Laboratory using poly (lactic acid)/wood flour (PLA/WF) pellets. These parts were shredded and granulated, and the granulate was fed directly back into the BAAM system for re-printing, skipping the costly and energy-intensive steps of extrusion and pelletization. The chemical, mechanical, thermal, and rheological changes to PLA/WF before and after recycling were investigated. Additionally, the energy savings from directly printing granulate on the BAAM system without extrusion and pelletization is reported. It is shown that PLA/WF is an excellent candidate for recycling of large format additively manufactured parts, and value of these parts can be reclaimed while saving cost and energy through mechanical recycling.

42 ENGINEERING↗
DOE OSTI2022

Manufacturing Cost Analysis of Advanced Parabolic Trough Collector

The research team performed a detailed bottom-up manufacturing cost estimate for an advanced parabolic trough design - the Solar Dynamics Sunbeam-MT (Sunbeam Mid-Term). This includes all components for manufacturing and assembly in a manufacturing facility (e.g. space frame and arms), and the purchased parts (e.g. mirrors and receiver tubes). Estimates of the construction and assembly activities have been made to then determine an estimated installed cost. Prior analysis has already undertaken detailed bottom-up manufacturing, assembly, and construction analysis for the Ultimate Trough from schlaich bergermann partner (sbp), and this work updates the solar field cost estimates based on a similar aperture area as the SunBeam-MT. For this analysis, the Ultimate Trough is considered the commercial parabolic trough and the Sunbeam-MT as the advanced parabolic trough. For similarity, both the Sunbeam-MT and the Ultimate Trough have been modelled with a solar field with approximately 800,000 square meters (m2) in aperture area - the equivalent of a large CSP plant. The analysis has found a potential installed cost estimate of the Sunbeam-MT could be $120/m2 but must be built at scale to confirm this estimate. Compared to prior analysis, the commercial Ultimate Trough using U.S. conditions, has reduced in installed cost from $178/m2 to $152/m2. Both designs could be even cheaper with Chinese steel.

cost analysis↗
DOE OSTI2023

Investigation of Raster Pattern Spacing and Direction for Friction Stir Additive Manufacturing of Al-5083

Friction stir additive manufacturing (FSAM) is a sheet-lamination based additive manufacturing technique. In addition to the traditional factors that govern the friction stir process-structure-property relationship, the processing history is convoluted by the in-plane raster pattern and repeated thermal cycling from subsequent layers. This can lead to complex thermal gradients within the workpiece and reprocessing of material. Here, this work aims to understand the impact of raster pattern spacing and direction on the microstructure and properties during friction stir additive manufacturing of Al-5083. Control of the raster spacing can lead to an increase in hardness of up to 18% from the base material and defect-free joining. These results are then directly demonstrated at the component-scale for FSAM of Al-5083.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Object-space optimization of tomographic reconstructions for additive manufacturing

Volumetric 3D printing motivated by computed axial lithography enables rapid printing of homogeneous parts but requires a high dimensionality gradient-descent optimization to calculate image sets. Here we introduce a new, simpler approach to image-computation that algebraically optimizes a model of the printed object, significantly improving print accuracy of complex parts under imperfect material and optical precision by improving optical dose contrast between the target and surrounding regions. Quality metrics for volumetric printing are defined and shown to be significantly improved by the new algorithm. The approach is extended beyond binary printing to grayscale control of conversion to enable functionally graded materials. The flexibility of the technique is digitally demonstrated with realistic projector point spread functions, printing around occluding structures, printing with restricted angular range, and incorporation of materials chemistry such as inhibition. Finally, simulations show that the method facilitates new printing modalities such as printing into flat, rather than cylindrical packages to extend the applications of volumetric printing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗