Predictive ultrasonic atomization for small-batch, high-yield metal powder synthesis
Abstract
This program will develop an integrated framework for predictive ultrasonic atomization of metallic powders, investigating a processing technology capable of small-batch, high-yield powder production. Current powder synthesis processes are labor and capital intensive, producing low yields at specific narrow particle size distributions of interest for powder-based repair and fabrication processes. The cost associated with current atomization processes thus restricts the exploration of novel alloys and restricts the operation of powder atomization capabilities to large laboratory and shipyard-scale facilities. The primary objective for this work is to develop a processing framework for ultrasonic atomization, an emerging technique that is well-suited for small-batch (<10 kg), low-footprint (6ft x 6ft x 8 ft height) powder production. The processing framework proposed in this work will correlate ultrasonic atomization processing parameters to powder characteristics relevant to repair and fabrication techniques, leveraging machine learning to optimize parameters to minimize experimental workload. To achieve our objective, the proposed approach is to perform ultrasonic atomization, powder characterization to include morphology, size, yield, composition, and flowability, and machine learning model training and implementation, with processing parameters suggested by the model for iterative experimentation. The materials selected for this work are corrosion-resistant 17-4 PH stainless steel and ultra-high strength AerMet 100 stainless steel. The expected outcomes from the proposed work are a processing framework for predictive ultrasonic atomization which correlates processing parameters to powder characteristics and process-relevant metrics, enhanced fundamental understanding of key parameters in ultrasonic atomization, and optimized processing parameters for 17-4 PH and AerMet 100 stainless steels. Enabled by efficient parameter exploration for ultrasonic atomization, we envision transformative opportunities for the DoD in small-batch, high-yield powder atomization of conventional and novel alloy compositions. For novel alloy exploration, the development of a processing framework for small-batch, high-yield atomization accelerates the optimization and validation of new alloys as high-quality feedstock in affordable quantities allows for rapid iteration for repair and fabrication experiments. For in-situ powder production for repair and fabrication, the development of a processing framework for a low-footprint atomization technique enhances the availability of small quantities of powder feedstock at depot-level maintenance centers for timely maintenance and repair of naval platforms. As an educational institution, UCSB performs fundamental and unclassified research. Any data or information developed or provided by UCSB, including but not limited to publications and reports, shall be unclassified fundamental research exempt from dissemination controls orreview requirements.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 13, 2024
- Source ID
- N000142412347
Entities
People
- Daniel Oropeza
Organizations
- Office of Naval Research
- United States Navy
- University of California, Santa Barbara