Predicting transformations during reactive flash sintering in CuO and Mn2O3

Reactive flash sintering has been demonstrated as a method to rapidly densify and synthesize ceramic materials, but determining the extent of chemical reactions can be complex since the maximum temperature reached by the sample may be brief in time. The black body radiation (BBR) model has been shown to accurately predict the sample temperature during the steady state of flash (stage III). This work demonstrates situations where the BBR model alone does not accurately predict when a phase transformation will occur. We examine the model reactions of CuO reduction to Cu2O during stage II and Mn(2)O(3)reduction to Mn(3)O(4)in stage III. In CuO, highly resistive samples result in initially localized current flow, a stochastic process resulting in inhomogeneous heating and error in the BBR model during stage II. CuO reduction does not occur in constant heating rate experiments with 6.25 V/mm fields, even though the sample temperature momentarily exceeds the phase transformation temperature. Increased furnace heating to 950 degrees C before application of a field is required to drive the transition. In Mn2O3, the calculated sample temperature of the gauge is less than the transformation temperature, but localized heating at the contact will exceed the transformation temperature, causing the transformation to propagate away from the electrode during stage III. This work demonstrates two forms of inhomogeneity (local, stochastic current flow, and local contact resistance) that result in a complex thermal profile of the sample. This profile should be interrogated to understand reaction kinetics, and can be beneficial when engineered.

Automated summary

Reactive flash sintering is an effective method for densifying and synthesizing ceramic materials, but the predictive capability of the BBR model for phase transformations during the process is limited. CuO reduction and Mn(2)O(3) reduction demonstrate the challenges of predicting phase transformations due to local, stochastic current flow and localized heating. Understanding and engineering the complex thermal profile that results from these sources of inhomogeneity can be beneficial for optimizing reaction kinetics.