Collaborative Research: DMREF: Accelerating Adoption of Sintering-Assisted Additive Manufacturing Using Integrated Experiments, Theory, Simulation and Data Science

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). NON-TECHNICAL SUMMARY

Ceramic components are important for commercial and strategic uses, ranging from tooling for materials processing and machining to biomedical, energy storage, combustion, and other applications involving extreme environments. Additive manufacturing approaches to produce ceramics include binder jetting and robocasting of green ceramic parts, which are then sintered at elevated temperatures to produce finished ceramic components.

Progress in this area is hampered by directional and spatial variations in the packing density of the ceramic powder and multiple-scale defects within additively-manufactured green ceramics. The result is undesired variations in the properties and dimensional tolerances of the final parts. This project will integrate experiments, theory, simulations, and data science expertise to develop a new theory of sintering-assisted additive manufacturing to predict the structure, properties, and dimensional changes of finished ceramic components.

The effort will use data-driven approaches to solve the inverse problem, so that the required additive manufacturing and sintering conditions to achieve desired high performance, high tolerance ceramic components can be specified in advance. Anticipated outcomes include the tools and knowledge to significantly reduce trial and error approaches to process advanced ceramics.

A diverse team of undergraduate and graduate students will be trained in the principles of the Materials Genome Initiative, with experiential learning from three industrial partners, the Air Force Research Laboratory, and two international research centers. The research findings will be incorporated into graduate and undergraduate courses taught by the investigators and meaningful partnerships to reach out to middle and high school students will be developed.

TECHNICAL SUMMARY

The overarching goal of the proposed research is the development of a new type of experimentally-guided and validated multi-scale model that accounts for the micro- and macro-structural features arising from sintering-assisted additive manufacturing (SAAM). A solution to the fundamental inverse sintering problem is the ultimate objective of this project.

It will enable the determination of the optimal green state processing conditions, pre-sintered component shape, micro- and macro-structures, and sintering conditions required to obtain the desired shape, microstructure, and properties at the end of sintering. This project concentrates on two commonly used additive manufacturing approaches – binder jetting and robocasting.

The proposed integration of computation and experiments in a data-driven predictive framework addresses the complex interplay between green-state processing conditions and anisotropic microstructure. The project will provide fundamental knowledge and a novel practical approach to design and optimize the manufacture of advanced ceramic systems with programmable macroscopic characteristics, microstructure, properties, and performance.

The solution of the “inverse SAAM problem” will significantly reduce trial and error experiments and will advance the goals of the Materials Genome Initiative by accelerating the adoption of SAAM for advanced ceramics.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.