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The production of advanced functional ceramics from dry raw powders through the solid-state reaction method is a highly industrially relevant process used by numerous researchers and industries around the world. Functional ceramics enable many cutting-edge applications and are, as such, a critical material class. Despite this, the development of high-throughput platforms for accelerated ceramics development from dry powders has not been intensively investigated and has lagged behind other combinatorial technologies, such as solution- and vapor-based systems, due to the complexity of automating the various steps in this powder synthesis route while maintaining the phase purity of resulting materials. As such, there are numerous important opportunities for the accelerated experimental synthesis and characterization of functional ceramics in a high-throughput platform that will allow for the production of large, homogeneous datasets required for machine learning, which will be discussed in this review. In addition, limitations and challenges of the various processing steps will also be presented.
Webber et al. (Sat,) studied this question.