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At least 163 records · Page 9

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NASA NTRS2004

AsterAnts: A Concept for Large-Scale Meteoroid Return and Processing using the International Space Station

AsterAnts is a concept calling for a fleet of solar sail powered spacecraft to retrieve large numbers of small (1/2-1 meter diameter) Near Earth Objects (NEOs) for orbital processing. AsterAnts could use the International Space Station (ISS) for NEO processing, solar sail construction, and to test NEO capture hardware. Solar sails constructed on orbit are expected to have substantially better performance than their ground built counterparts [Wright 1992]. Furthermore, solar sails may be used to hold geosynchronous communication satellites out-of-plane [Forward 1981] increasing the total number of slots by at least a factor of three. potentially generating $2 billion worth of orbital real estate over North America alone. NEOs are believed to contain large quantities of water, carbon, other life-support materials and metals. Thus. with proper processing, NEO materials could in principle be used to resupply the ISS, produce rocket propellant, manufacture tools, and build additional ISS working space. Unlike proposals requiring massive facilities, such as lunar bases, before returning any extraterrestrial larger than a typical inter-planetary mission. Furthermore, AsterAnts could be scaled up to deliver large amounts of material by building many copies of the same spacecraft, thereby achieving manufacturing economies of scale. Because AsterAnts would capture NEOs whole, NEO composition details, which are generally poorly characterized, are relatively unimportant and no complex extraction equipment is necessary. In combination with a materials processing facility at the ISS, AsterAnts might inaugurate an era of large-scale orbital construction using extraterrestrial materials.

Globus, Al↗

NASA NTRS2023

Reactive Additive Manufacturing for Fourth Industrial Revolution Exploration Systems (Ramfire) Aluminum 6061-Ram2 Nozzle Testing

The NASA Marshall Space Flight Center (MSFC) has applied various forms of metallic additive manufacturing (AM) in liquid rocket engine component design, development, and testing since 2010. These AM techniques reduce hardware cost, shorten fabrication schedules, increase reliability by reducing the number of joints, and improve hardware performance by allowing unconventional design. The RAMFIRE project, funded under Space Technology Mission Directorate (STMD) Game Changing Development (GCD) Program, has furthered the use of novel AM liquid rocket nozzles in collaboration with Elementum 3D. The project advanced novel large-scale AM aluminum material technology for significant weight savings in rocket engines and launch vehicles. Previously, aluminum alloys were difficult to weld and print using additive manufacturing. Elementum 3D’s patented Aluminum 6061-RAM2 alloy allows for aluminum alloys to be printed using various AM techniques and at various scales. The alloy can be leveraged for welding wire, showing drastic improvements in aluminum weldability. The RAMFIRE project focuses on five key areas: 1) Laser Powder Directed Energy Deposition (LP-DED) AL6061-RAM2 feedstock specification and verification, 2) LP-DED process development and validation, 3) LP-DED printed AL6061-RAM2 microstructural and mechanical property characterization, 4) Hot-fire test a 7k-lbf thrust class regeneratively cooled nozzle, 5) Print large scale regeneratively cooled nozzle. Hot-fire testing demonstrates potential of advanced space technologies to NASA and potential users by providing the relevant environments to advance TRL levels to the 5/6 range.

Al6061-RAM2↗

DOE OSTI2024

Integrated top-down process and voxel-based microstructure modeling for Ti-6Al-4V in laser wire direct energy deposition process

Laser-wire metal additive manufacturing (AM) is one of the ideal direct energy deposition (DED) processes for creating large-scale parts with a medium level of complexity. However, the DED process involves complex thermal signatures and wide length scales making the fabrication of realistic AM components and part qualification often reliant on experimental trial-and-error optimization. While experimental measurements over the full volume of a part are valuable and necessary, measuring the entire area of a part is significantly laborious and practically infeasible, particularly for large parts in terms of cost and rapid qualification. Therefore, in this work, we developed an effective thermal and microstructure modeling framework based on the Johnson–Mehl-Avrami-Kolmogorov (JMAK) and Koistinen & Marburger (KM) models through a top-down approach that considers plate distortion-affected thermal profiles. A voxel-by-voxel simulation method is used to predict individual phase fractions of Ti-6Al-4 V. The predicted results were validated through detailed metallurgical measurements. A combined voxel-by-voxel approach with a sparse data reconstruction technique produced a near-perfect reconstruction of the original data. This approach anticipates a significant reduction in data points and computation time and resources. Lastly, we conclude with potential extensions of this work to other modeling efforts.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation

Large-format additive manufacturing (LFAM) is a branch of additive manufacturing (AM) research with the ability to create large structures typically measuring several meters in scale. LFAM is advantageous for tooling applications, not only because it offers the ability to create complex geometries not easily made using subtractive manufacturing processes, but the cost savings of pelletized feedstock used by these systems result in larger parts printed at faster speeds than traditional AM systems. Fiber reinforced polymer (FRP) is a commonly used feedstock material in LFAM structures because it reduces the distortion experienced during printing. However, FRP introduces highly anisotropic thermomechanical properties and contributes to a nonhomogeneous microstructure that can result in critical distortion of dimensions during tooling. Measuring the global thermomechanical response of LFAM structures requires a more representative method that accounts for not only anisotropic properties but also the nonhomogeneous nature of the final part. This is where traditional techniques to measure thermomechanical response, such as thermomechanical analysis (TMA), fall short as they assume homogeneity. This study evaluated the coefficient of thermal expansion (CTE) of LFAM structures as measured by TMA as compared to a novel digital image correlation oven (DIC Oven) system. The LFAM structures were made from 20 % by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS). TMA measurements showed significant variations in CTE across a single LFAM bead, confirming the need for a global technique that captures overall thermomechanical response. The CTE values measured using the DIC Oven compared well to average TMA values obtained from localized measurements across the sample. The DIC Oven was also used to quantify the effects of different layer orientations on thermomechanical properties, which cannot be easily captured using TMA. A predictive model was also developed by using localized TMA values across an LFAM bead to predict the overall thermomechanical response of an LFAM structure.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Packing and flow particle simulations

Granular material is present across natural and industrial processes on Earth and other planets. Granular particles show up in space exploration (lunar regolith), avalanches (boulders), food (coffee), construction (concrete powder) and manufacturing (additive manufacturing powder, battery slurries). Important phenomena emerge from large collections of granular particles. The size scales of the particles in granular material, 10 μm diameter or larger, makes particle-based simulations a tractable computational method. This seminar will present the packing and flow of granular matter using particle-based discrete element modeling simulations. Particles modeled with rotational friction only require as few as 2.6 contacts for mechanical stability, as opposed to 6 contacts for frictionless particles. Optimal parameters for in-space manufacturing particulate material are identified. Specifically, the maximum density and contacts occurs for a large-to-small particle volume ratio of 0.265. Stress and contact fabric fluctuations of flowing dry granular matter have power-law scaling with strain rate, and a kink. The pressure-dependent slope change kink could identify the transition between slower, quasistatic and faster, inertial flows.

granular↗

NASA NTRSDate not supplied

Packing and flow particle simulations

granular↗

DOE OSTI2025

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale↗

DOE OSTI2022

Empower Wall: Active insulation system leveraging additive manufacturing and model predictive control

Buildings are one of the largest energy consumers worldwide, using large amounts of energy during their construction and for climate control during operation. Active insulation systems (AIS) have been shown to reduce the energy needed for climate control in buildings by dynamically regulating the heat transferred between a building’s interior and exterior. Infrastructure-scale additive manufacturing (AM) has the potential to reduce the resources needed for building construction. Combining these two technologies into a single building envelope would create a path towards more sustainable buildings. A test was conducted for the Federal Energy Management Program (FEMP) Energy Exchange training and trade show, in August 2021, to investigate a new building envelope design, termed the Empower Wall, that utilized an AIS and was constructed using AM. Model predictive control was implemented to manage operation of the Empower Wall in concert with the existing HVAC system. Finally, the prototype system demonstrated that the Empower Wall lowered total energy consumption and reduced the cost of energy used.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Lightweight Thrust Chamber Assemblies using Multi-Alloy Additive Manufacturing and Composite Overwrap

Additive Manufacturing (AM) has brought significant design and fabrication opportunities for complex components with internal features such as liquid rocket engine thrust chambers not previously possible. This technology allows for significant cost savings and schedule reductions in addition to new performance optimization through weight reduction and increased margins. Specific to regeneratively-cooled combustion chambers and nozzles for liquid rocket engines, additive manufacturing offers the ability to form the complex internal coolant channels and the closeout of the channels to contain the high pressure liquid propellants with a single operation. Much of additive manufacturing development has focused on monolithic alloys using Laser Powder Bed Fusion (L-PBF), which do not allow for complete optimization of the structure. The National Aeronautics and Space Administration (NASA) completed feasibility of an AM bimetallic L-PBF GRCop-84 copper-alloy combustion chamber with an AM electron beam freeform Inconel 625 structural jacket under the Low Cost Upper Stage Propulsion (LCUSP) Project. A follow-on project called Rapid Analysis and Manufacturing Propulsion Technology (RAMPT) is under development to further expand large-scale multi-alloy thrust chambers while maturing composite overwrap technology for significant weight savings opportunities. The RAMPT project has three primary objectives: 1) Advancing blown powder Directed Energy Deposition (DED) to fabricate integral-channel large scale nozzles, 2) Develop composite overwrap technology to reduce weight and provide structural capability for thrust chamber assemblies, and 3) Develop bimetallic and multi-metallic additively manufactured radial and axial joints to optimize material performance. In addition to these primary manufacturing developments, analytical modeling efforts compliment the process development to simulate the AM processes to reduce build failures and distortions. The RAMPT project is also maturing the supply chain for various manufacturing processes described above in addition to L-PBF of GRCop-42. This paper will present an overview of the RAMPT project, the process development and hardware progress to date, material and hot-fire testing results, along with future developments.

Additive Manufacturing↗

NASA NTRS2019

Channel Wall Nozzle Manufacturing Technology Advancements for Liquid Rocket Engines

A regeneratively-cooled nozzle is a critical component for expansion of the hot gases to enable high temperature and performance liquid rocket engines systems. Channel wall nozzles are a design solution used across the propulsion industry as a simplified method to fabricate the nozzle structure with internal coolant passages. The scale and complexity of the channel wall nozzle (CWN) design is challenging to fabricate leading to extended lead times and higher costs. Some of these challenges include: 1) unique and high temperature materials, 2) Tight tolerances during manufacturing and assembly to contain high pressure propellants, 3) thin-walled features to maintain adequate wall temperatures, and 4) Unique manufacturing process operations and tooling. The United States (U.S.) National Aeronautics and Space Administration (NASA) along with U.S. specialty manufacturing vendors are maturing modern fabrication techniques to reduce complexity and decrease costs associated with channel wall nozzle manufacturing technology. Additive Manufacturing (AM) is one of the key technology advancements being evaluated for channel wall nozzles. Much of additive manufacturing for propulsion components has focused on powder bed fusion, but the scale is not yet feasible for application to large scale nozzles. NASA is evolving directed energy deposition (DED) techniques for nozzles including arc-based deposition, blown powder deposition, and Laser Wire Direct Closeout (LWDC). There are different approaches being considered for fabrication of the nozzle and each of these DED processes offer unique process steps for rapid fabrication. The arc-based and blown powder deposition techniques are being used for the forming of the CWN liner. A variety of materials are being demonstrated including Inconel 625, Haynes 230, JBK-75, and NASA HR-1. The blown powder DED process is also being demonstrated for forming an integral channel nozzle in a single operation in similar materials. The LWDC process is a method for closing out the channels within the liner and forming the structural jacket using a localized laser wire deposition technique. Identical materials mentioned above have been used for this process in addition to bimetallic closeout (C-18150–SS347, and C-18150–Inconel 625). NASA has completed process development, material characterization, and hot-fire testing on a variety of these channel wall nozzle fabrication techniques. This paper will present an overview of the various processes and materials being evaluated and the results from the hot-fire testing. Future development and technology focus areas will also be discussed relative to channel wall nozzle manufacturing.

Gradl, Paul R.↗

DOE OSTI2022

Melt pool temperature measurement and monitoring during laser powder bed fusion based additive manufacturing via single-camera two-wavelength imaging pyrometry (STWIP)

Melt pool (MP) temperature is one of the determining factors and a key signature for evaluating the properties of printed components in metal additive manufacturing (AM). The state-of-the-art measurement systems are hindered, primarily by the large-scale data acquisition and processing demands. In this work, we introduce a novel coaxial, high-speed, single-camera two-wavelength imaging pyrometer (STWIP) system as opposed to the typical utilization of multiple cameras for measuring MP temperature profiles in laser powder bed fusion (LPBF) processes. Developed on a commercial LPBF machine (EOS M290), the STWIP system demonstrated its ability to quantitatively monitor the MP temperature and its variation for 50 layers at high framerates (>30,000 fps) for a real-world application (standard fatigue specimens) print. High performance computing is employed to analyze the acquired big data (MP images), for determining each MP's average temperature and 2D temperature profile. The MP temperature evolution in the gage section of a fatigue specimen is also examined at a temporal resolution of 1 ms, by evaluating the MP temperatures in the samples' first, middle, and last layers. This report is the first of its kind on monitoring MP temperature distribution and evolution at such a large, detailed scale for longer durations in practical applications.

42 ENGINEERING↗

DOE OSTI2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗

DOE OSTI2021

A chemical switch enabled autonomous two-stage crosslinking polymeric binder for high performance silicon anodes

Silicon (Si) is a promising high-capacity anode material for high-energy-density lithium-ion batteries. However, the drastic volumetric changes of Si upon lithiation/delithiation hinder the practical use of Si anodes. Although adhesive polymeric binders, such as poly(acrylic acid) (PAA), mitigate this issue, the cycling performance of the fabricated Si anodes is still far from meeting the criteria of practical applications. In this study, we present a novel polymeric binder system for Si anodes consisting of PAA, a chemical switch (ammonia, NH 3 ), and a crosslinker (branched polyethylenimine, PEI). The crosslinking between PAA and PEI is switched off in the slurry, which can then be turned on during electrode drying. Interestingly, the crosslinking reaction consists of two stages: ionic cross-linking (PAA-PEI-i) and covalent crosslinking (PAA-PEI-c) at a higher temperature (e.g., 130 °C). In half-cells, Si anodes fabricated using the PAA-PEI-c binder show a 67% increase in capacity retention compared to PAA anodes over 150 cycles at C/3 rate. The PAA-PEI-c binder also outperforms PAA in full cells. In addition, the chemical switch controlled crosslinking binder system also facilitates the slurry making process by avoiding early crosslinking. This system requires no additional steps compared to the conventional electrode lamination process, showing enormous potential for direct adoption in large-scale manufacturing.

25 ENERGY STORAGE↗

DOE OSTI2025

Upcycling of post-consumer mixed polyolefin feedstock: An economic and technical evaluation

Here, this study reports techno-economic and life cycle analyses to evaluate the economic and environmental impacts of mechanically recycled PE/PP blends in the presence of rheology modifiers. Additionally, fiber-reinforced composites derived from the compatibilized blends were prepared and evaluated for their performance compared with virgin plastics. Results suggest that compatibilized PE/PP blends exhibit a 70% lower selling price compared to virgin PE. Furthermore, these blends achieved a 74% reduction in greenhouse gas emissions or climate change impact compared to the virgin counterpart. Fiber-reinforced composites from compatibilized PE/PP blends demonstrated improved or comparable mechanical properties relative to composites made from virgin PE/PP blends. Based on their favorable cost and environmental impact, along with performance comparable to virgin composites, compatibilized PP/PE composites made from post-consumer plastics can find applications in large-scale composite manufacturing.

Fiber reinforced plastics (FRP)↗

DOE OSTI2024

Additive manufacturing of multiscale NiFeMn multi-principal element alloys with tailored composition

Nanostructured multi-principal element alloys (MPEAs) have been explored as next-generation engineering materials due to unique mechanical and functional properties which have significant advantages over traditional dilute alloys. However, the practical applications of nanostructured MPEAs are still limited due to the lack of scalable processing approaches to prepare a large quantity of nanostructured MPEAs, as well as lack of an efficient pathway for high-throughput discovery of better functional nanostructured MPEAs within their vast compositional space. Here we tackle these challenges by presenting an integrated approach by combining direct-ink-writing-based additive manufacturing, solid-state sintering, and chemical dealloying to manufacture hierarchically porous MPEAs. The hierarchical structure is comprised of macro- and micro-scale pores introduced via extrusion printing and polymer decomposition during sintering, as well as nanoscale pores formed via chemical dealloying. The macro- and micro-scale pores allow efficient dealloying of a large mass of material as the diffusion length that the corroding medium must penetrate remains at the scale of the ligaments formed after sintering (∼10 μm), despite the large volume of the 3D-printed samples. In addition, this integrated approach enables versatile control of the alloy composition via precisely tuning the ratio of elemental powders in the starting ink, thus offering a pathway for high-throughput discovery of novel functional MPEAs. As a case study, multiscale macro/micro/nanoporous NiFeMn MPEAs with three different compositions were investigated as catalysts to reduce the overpotential of oxygen evolution reaction (OER), where NiFeMn-based electrocatalysts display composition-dependent performance such that the overpotential measured at a current of 0.5 A g −1 for OER increases in the order of Ni 58 Fe 29 Mn 13 ⩽ Ni 64 Fe 26 Mn 10 < Ni 76 Fe 18 Mn 6 . This introduced manufacturing process offers new opportunities for scalable fabrication and rapid screening of nanostructured multi-component complex alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Registration and fusion of large-scale melt pool temperature and morphology monitoring data demonstrated for surface topography prediction in LPBF

In-situ monitoring technologies for laser powder bed fusion (LPBF) additive manufacturing often face one key challenge, extracting the ultrafast melt pool (MP) signatures for understanding the localized part properties. Further, the spatial information of each monitored MP signature is essential for correlating the MP – part property. This spatial information is often unavailable especially from commercial LPBF printers. Many MP monitoring methods have been reported and utilized. However, very few of these have the MP’s spatial information. To overcome this challenge, in this work we report a method for spatially registering the key MP signatures (MP intensity, temperature, and area) to the monitored print parts. The MP signatures are obtained from our coaxial high-speed single-camera based two-wavelength imaging pyrometry (STWIP) system and the MP spatial information is obtained from an off-axis camera system. A machine learning aided image analysis method is employed to retrieve the spatial distribution of MPs within the corresponding part’s coordinates system. Then, the MP signature maps (MPSMs) are reconstructed by mapping the STWIP measured MP signatures to the registered MP coordinates. Further, a long short-term memory (LSTM) neural network is developed for estimating the layer surface topography from the registered MPSMs. The obtained results indicate that the layer surface topography can be more accurately estimated by using MP temperature signature rather than MP intensity and/or area signatures as in common practice. Finally, our developed methods for MP monitoring, registration, and MP-surface topography prediction offer advanced capabilities for the online detection of process anomalies and part defects.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Thermal images collected during large-scale 3D printing with Ingersoll MasterPrint

This data set contains images produced to test the performance of anomaly and fault detection methods in the context of additive manufacturing. Two print jobs were executed using the Ingersoll MasterPrint with the Model 30 Strangpresse extruder. The material used was Techmer compounded polylactic acid (PLA) with wood flour as a filler (80/20 PLA/WF by weight). The first print job consists of the 3D printing of a hexagonal cylinder with a two-bead wall. This print was sliced at a gantry velocity of 3000 millimeter per minute, and an extruder screw speed of 68.14 rotations per minute. This are considered the normal operating conditions. A second hexagonal cylinder was printed using a reduced extruder screw speed, 15% lower than under normal operating conditions. The images were collected with a Teledyne FLIR Lepton 3.5 infra-red camera, a small form factor radiometric long-wave infrared camera with a spectral range of 8 µm to 14 µm. Sensor resolution was 160x120 pixels, with a pixel size of 12 µm, a temperature range of -10 - 450°C, and an accuracy of +/- 10°C in its low gain configuration. Images in this data set were collected with cameras oriented at the printer nozzle. The nozzle camera setup consisted of two cameras located 12.5cm from the nozzle center. These were mounted directly to the print head, so that the camera positions relative to the print direction would remain constant as it rotated around its C-axis to follow the print path. One camera was placed ahead of the nozzle to capture the previous layer immediately before being covered by the new layer of material, while the second camera was placed behind the nozzle and captured the freshly extruded bead. Images are collecting during each phase of the print: (a) idle (i.e., no material deposited), (b) extrusion (i.e., to prime the extruder), and (c) printing (deposition of material to manufacture the hexagonal cylinder).

36 MATERIALS SCIENCE↗

DOE OSTI2023

Magnetostrictive materials for enhanced sensors and electronic components

Magnetostriction is a property of magnetic materials that causes them to change their shape or dimensions proportional to their magnetization. Low-cost, mechanically robust magnetostrictive sensors would be valuable for a wide range of applications across the DOE and national security mission space, such as monitoring the internal conditions of pipelines, rapidly detecting high-impedance faults in power lines (e.g. trees touching power lines), or enhancing implantable systems for the human body. Dilute doping (<1 at.%) of rare earth elements (REE) has been shown to amplify the magnetostriction. Furthermore, alloy processing by rapid cooling from high temperature tends to result in texturing and therefore greater magnetostriction values, which bodes well for developing advanced manufacturing approaches significantly less expensive than single crystal growth. The goal of this effort was to develop robust, low-cost magnetostrictive materials compatible with advanced manufacturing techniques to exploit the rapid cooling of these approaches while retaining the ability to produce fully dense structures. To be useful as a sensor or actuator the coercivity of the material needs to be minimized so that there is minimal magnetic hysteresis. Employing a small scale laser powder bed fusion (L-PBF) system, specimens of Fe-Ga-Ce were built from alloy powder which had a magnetostriction of 289 ppm along the build direction and 197 ppm perpendicular to the build direction. These values are not far from the 310-350 ppm observed in single crystals of Fe-Ga. The results of the series of samples run suggest this is a very promising route for REE doping to higher levels, especially if the powders can be produced using far from equilibrium approaches such as ultrasonic atomization. The promising results from applying additive manufacturing techniques to these materials, particularly the inexpensive Fe-Al system, has potential for inexpensive high-performing magnetostrictive parts producible at large scales for low-cost sensors.

36 MATERIALS SCIENCE↗