| About this Abstract |
| Meeting |
MS&T24: Materials Science & Technology
|
| Symposium
|
Grain Boundaries, Interfaces, and Surfaces: Fundamental Structure-Property-Performance Relationships
|
| Presentation Title |
Data Analytics for Sintering Regimes Identification |
| Author(s) |
Jarrod Lund, Alfredo Sanjuan Sanjuan, R. Edwin García |
| On-Site Speaker (Planned) |
Jarrod Lund |
| Abstract Scope |
In the last 10 years, the application of multiphysical driving forces to enhance the classic sintering of materials has led to the experimental identification of flash (with sintering times in the order of seconds), FAST (Field Assisted Sintering), ultra-fast (mostly through high thermal heating rates). By starting from a physics-based coarse-grained physical description of the electric field-, and stress-assisted driving forces, a non-dimensionalized sintering kinetic equation is used to predict sintering of ionic ceramics. By integrating data analytic clustering algorithms over a million sintering profiles describing the six-dimensional material processing parameter space, distinct sintering regimes (e.g., flash, field-assisted) are readily identified. The resulting categorization enables the prediction of which materials will flash and under what conditions, laying the groundwork to enable fine-tuning of material properties to achieve the desired processing and performance. |