|Friedman, Lawrence H
Additive manufacturing (AM) is a rapidly growing technology, but its commercial adaptation to ceramic-based materials lags behind the metals and polymers sectors . Innovations that improve the availability of reliable, custom, on-demand ceramic parts will benefit a range of structural, thermal management, medical, and electronic applications. These applications often call for multi-material or composite parts that require ceramics to be integrated with less-refractory materials . The ceramic AM field will progress with innovations that combine experience from traditional ceramic processing with recent breakthroughs in densification of ceramics.
Our effort at NIST focuses on developing predictive tools for ceramic AM by combining computational and experimental approaches to study fundamental material processes during direct-ink writing and post-processing of ceramic parts. Successful candidate will perform modeling and simulation of direct ink writing and processing of ceramic parts and test-structures. This is an excellent opportunity for a theoretical / computational scientist to work in equal partnership with experimentalists including collaborative experimental design and data analysis. (See related NRC opportunity http://nrc58.nas.edu/RAPLab10/Opportunity/Opportunity.aspx?LabCode=50&ROPCD=506521&RONum=C0562).
Current modeling methods include multi-phase Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM). The successful candidate will have experience in these methods, a strong background in computational model development and implementation, or an innovative proposal.
 A. J. Allen, I. Levin, S.E. Witt, Materials research & measurement needs for ceramics additive manufacturing. Journal of the American Ceramic Society 103 (2020) 6055-6069. https://doi.org/10.1111/jace.17369.
 A. Bandyopadhyay, B. Heer, Additive manufacturing of multi-material structures, Mater. Sci. Eng. R Reports. 129 (2018) 1–16. https://doi.org/10.1016/j.mser.2018.04.001.
Ceramics; Additive Manufacturing; Modeling; Simulation; Discrete Element Method; Computational Fluid Dynamics; Rheology; 3D-Printing