Abstract
Powder spreading is a key step in the powder-bed-based additive manufacturing process, which determines the quality of the powder bed and, consequently, affects the quality of the manufactured part. However, powder spreading behavior under additive manufacturing condition is still not clear, largely because of the lack of particle-scale experimental study. Here, we studied particle-scale powder dynamics during the powder spreading process by using in-situ high-speed high-energy x-ray imaging. Evolution of the repose angle, slope surface speed, slope surface roughness, and the dynamics of powder clusters at the powder front were revealed and quantified. Interactions of the individual metal powders, with boundaries (substrate and container wall), were characterized, and coefficients of friction between the powders and boundaries were calculated. The effects of particle size on powder flow dynamics were revealed. The particle-scale powder spreading dynamics, reported here, are important for a thorough understanding of powder spreading behavior in the powder-bed-based additive manufacturing process, and are critical to the development and validation of models that can more accurately predict powder spreading behavior.
Recommended Citation
L. I. Escano et al., "Revealing Particle-Scale Powder Spreading Dynamics in Powder-Bed-Based Additive Manufacturing Process by High-Speed X-Ray Imaging," Scientific Reports, vol. 8, no. 1, Springer Verlag, Oct 2018.
The definitive version is available at https://doi.org/10.1038/s41598-018-33376-0
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
International Standard Serial Number (ISSN)
2045-2322
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2018 The Author(s), All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Oct 2018
PubMed ID
30305675
Comments
This work is funded by Honeywell Federal Manufacturing & Technologies (FM&T), University of Missouri Research Board (UMRB), Intelligent Systems Center and Materials Research Center of Missouri S&T, National Science Foundation, and Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. The authors would like to thank Alex Deriy at the APS for his help on the beamline experiments. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. All data prepared, analyzed and presented has been developed in a specific context of this work and was prepared for internal evaluation and use pursuant to that work authorized under the referenced contract. Reference herein to any specific commercial product, process or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government, any agency thereof or Honeywell Federal Manufacturing & Technologies, LLC. This publication has been authored by Honeywell Federal Manufacturing & Technologies under Contract No. DE-NA0002839 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes.