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At least 433 records · Page 24

Developing tools and process controls to manufacture energy-efficient powders for additive manufacturing feedstocks: Computational analysis of metal powder manufacturing via machining

Traditionally, metal powders have been produced through methods such as grinding, atomization, and electrolysis. In contrast to these techniques, Metal Powder Works, Inc. has pioneered a methodology based on metal cutting. This innovative approach utilizes a vibrating cutting tool to machine metal particles, in the form of chips, from a workpiece. This technique allows for control of powder particle size, morphology, and avoids any thermally induced material changes. This collaboration aims to elucidate metal cutting characteristics and assess performance on tough materials like Inconel alloys. Computational models, using FEA and SPH techniques, will be developed initially, focusing on aluminum alloy (Al 7075-T6) for studying mesh sensitivity, cutting forces, and chip morphology.

99 GENERAL AND MISCELLANEOUS↗

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Gibson, Brian↗

High-Energy X-ray Tomographic Analysis of Precursor Metal Powders (Ti-6Al-4V) Used for Additive Manufacturing

We utilized high-energy x-ray tomography to characterize Ti-6Al-4V metal powders (both as-received and recycled) used in powder-bed additive manufacturing process. The image processing workflow was developed to process and analyze large amount of data objectively by computer program. The distribution of size and shape of the metal particles as well as defect (mainly porosity) inside the particles was analyzed with the statistical representation and resolution in micrometer. The result revealed that circular-shaped porosity with various sizes could be embedded in the powder particles. These porosities could potentially be transferred to the 3D printed part and critically affect the mechanical performance of the component. The present study shows the effectiveness of characterizing metal powders using x-ray imaging techniques where sufficient number of particles can be sampled within tens of minutes with a minimum sample preparation and high accuracy. Clear structural differences in the as-received and recycled powders were delineated that helps in determining the feasibility of using the recycled powders.

36 MATERIALS SCIENCE↗

Developing cathode infiltration processes for all-solid-state bilayer LLZO cells

To realize the bilayer architecture of lithium lanthanum zirconate (LLZO) for application in solid-state batteries (SSBs), the scaffold structure must be optimized, and effective cathode infiltration strategies must be established. In this study, we fabricate a modified bilayer LLZO using a sacrificial layer to enhance surface porosity, and systematically investigate various cathode infiltration techniques to fill the scaffold with oxide cathode active materials (CAM). Structural characterizations showed that the sacrificial layer significantly increased open surface porosity, enabling the surface of the scaffold to be filled with CAM. To further increase infiltration depth, applying vacuum or vibration was compared, with the full-depth infiltration achieved using a sonicator-based vibration. Full cells prepared using the modified bilayer LLZO and vibration-assisted technique demonstrated successful operation. This work demonstrates a practical and scalable approach for engineering bilayer LLZO structures and integrating oxide cathodes into porous scaffolds, offering a promising pathway toward high-performance solid-state batteries.

Bilayer↗

Characterizing Quantum Classifier Utility in Natural Language Processing Workflows

Quantum Natural Language Processing (QNLP) develops natural language processing (NLP) models for deployment on quantum computers. We explore feature and data prototype selection techniques to address challenges posed by encoding high dimensional features. Our study builds quantum circuit classifiers that includes classical feature pre-processing, quantum embedding and quantum model training. The quantum models are built on 4 or 6 qubits and the quantum neural network (QNN) uses the established bricklayer design. We compare the dependence of model performance (in terms of accuracy and F1 scores) on feature length, embedding gates and parameterized unitary design. We compare the performance of quantum machine learning models to classical convolution neural network model (CNN) on binary and multi-class classification tasks using two datasets of synthetic features and labels. The first is the ECP-CANDLE P3B3 dataset a corpus of synthetically generated cancer pathology reports. The second dataset is extracted from well-known benchmark dataset (MADELON) - features are generated with a combination of informative, repeated and uninformative features. Both datasets are used for binary classification and multi-class classification with 3 classes. We observe robust, accurate performance from all models on the binary classification tasks, but multiclass classification is a challenge for the quantum models-there is a notable decrease in accuracy when using 3 classes. Overall the performance is comparable in terms of recall and accuracy between QNNs and CNNs, even with large datasets. These results provide a point of comparison between quantum and classical models on real-world datasets.

Hamilton, Kathleen↗

Process and Applications Development for Recycled Mixed-Stream Composites

The goal of this IACMI Phase II Technical Collaboration Project was to establish the viability of producing affordable, recycled composite parts, which were produced from fibers with the properties in the range of those reclaimed through the controlled pyrolysis technology demonstrated in Phase I [1]. For the purpose of this report, we use the terms “recovered carbon fiber” (rCF) and “recovered glass fiber” (rGF) as the material reclaimed from controlled pyrolysis. This fiber recycling technology utilizes the inherent energy in composites for fuel and preserves the structural value of glass fiber (GF) and carbon fiber (CF) for reuse. It can also be used for recycling other waste streams at the same facility, thus spreading capital risk and recovery across multiple industries and achieving economy of scale. A second goal to be addressed was the viability of using recycled fibers as reinforcing materials in additive manufacturing applications.

36 MATERIALS SCIENCE↗

Plan for Developing TRISO Fuel Processing Technologies

This Plan demonstrates the availability of technologies for processing TRISO used nuclear fuel for waste management and actinide recovery purposes. These technologies are judged to be at a very low level of technology readiness and as such they constitute a fertile research area for the DOE-NE’s Office of Materials and Chemical Technologies. Strategies to mature the technologies to a point where they can reasonably be considered in engineering alternatives analyses typically involve laboratory-scale tests using fuel simulant to characterize process streams and demonstrate key engineering features. Several criteria are available to help selecting candidate technologies for further maturation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Process and Applications Development for Recycled Mixed-Stream Composites

The goal of this IACMI Phase II Technical Collaboration Project was to establish the viability of producing affordable, recycled composite parts, which were produced from fibers with the properties in the range of those reclaimed through the controlled pyrolysis technology demonstrated in Phase I. For the purpose of this report, we use the terms “recovered carbon fiber” (rCF) and “recovered glass fiber” (rGF) as the material reclaimed from controlled pyrolysis. This fiber recycling technology utilizes the inherent energy in composites for fuel and preserves the structural value of glass fiber (GF) and carbon fiber (CF) for reuse. It can also be used for recycling other waste streams at the same facility, thus spreading capital risk and recovery across multiple industries and achieving economy of scale. A second goal to be addressed was the viability of using recycled fibers as reinforcing materials in additive manufacturing applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Plasma Processing for In-Situ Field Emission Mitigation of Superconducting Radiofrequency (SRF) Cryomodules

Field emission (FE) is one of the main limiting factors of superconducting radio-frequency (SRF) cavities operating in accelerators and it occurs whenever contaminants, like dust, metal flakes or even absorbates, are present on the surface of the cavity high electric field region. Field emission reduces the maximum achievable accelerating field and generates free electrons that may interact with the beam, damage or activate the beamline. One practical method that can be used to mitigate this problem is in-situ plasma cleaning, or plasma processing. The development of a processing that can be applied in-situ is extremely advantageous, since it enables the recovery of the cryomodule performance without the need of disassembling the whole cryomodule, which is an extremely expensive and time-consuming process. On the other hand, plasma processing only requires the cryomodule warm-up to room-temperature and the subsequent processing of the contaminated cavities. The entire process is reasonably quick and involves a limited number of personnel. For these reasons we would like to advocate for continuing to invest in the R&D of plasma processing to optimize its applicability in cryomodules and for extending the technique to other frequency ranges and cavities geometries.

43 PARTICLE ACCELERATORS↗

Development of New Magnetron Sputter Deposition Processes for Laser Target Fabrication

Magnetron sputter deposition is an enabling technology for laser target fabrication. Solutions are readily available for the deposition of most sub-micron-thick elemental films on planar substrates. However, major challenges still remain for the development of robust deposition processes in regimes of ultrathick (over ~10 μm) coatings and nonplanar substrates. These challenging deposition regimes are directly relevant to laser target applications, including both sphero-cylindrical hohlraums and spherical ablators for inertial confinement fusion (ICF) targets. Understanding underlying physical mechanisms for a specific material system is crucial for process development, given the overall complexity of the deposition process, its nonlinear dependence on deposition parameters, and a very large process space, often precluding conventional process optimization approaches. Here, we describe our approach to developing new deposition processes and give practical advice with examples of new results from our ongoing studies of glassy boron carbide ceramics for next-generation ICF ablators and nonequilibrium gold-tantalum alloys for hohlraums for magnetized ICF schemes. Emphasis is given to two major challenges of ultrathick coatings related to achieving process stability and reducing residual stress.

36 MATERIALS SCIENCE↗