Double-tough and ultra-strong ceramics: leveraging multiscale toughening mechanisms through Bayesian Optimization

TL;DR

This paper introduces a Bayesian optimization framework to efficiently design a bio-inspired double-tough ceramic with a microstructure that balances high strength and fracture toughness, leveraging multiscale toughening mechanisms.

Contribution

The study presents a novel optimization-driven methodology using Bayesian optimization to accelerate the design of complex ceramic composites with enhanced mechanical properties.

Findings

Achieved a bending strength of 704 MPa.

Attained a fracture toughness of 13.6 MPa·m^0.5.

Developed a bio-inspired all-ceramic composite with superior properties.

Abstract

We present an optimization-driven approach to creating a double-tough ceramic material with a brick-and-mortar microstructure, where the mortar is itself transformation-toughened, engineered with the goal of simultaneously achieving high strength and fracture toughness levels. Specifically, we design a material where high-strength alumina bricks are interconnected via a ceria-stabilized zirconia mortar. As the design of such a material, driven by multiscale toughening mechanisms, requires a laborious trial-and-error approach, we propose a Bayesian optimization framework as an integral part of our methodology to streamline and accelerate the design process. We use a Gaussian process to emulate the material's mechanical response and implement a cost-aware batch Bayesian optimization to efficiently identify optimal design process parameters, accounting for the cost of experimentally varying them. This approach expedites the optimization of the material's mechanical properties. As a result, we develop a bio-inspired all-ceramic composite that exhibits an exceptional balance between bending strength (704 MPa), and fracture toughness (13.6 MPa m^0.5).