Collaborative Research: DMREF: Anharmonicity and Defect Engineering of Compositionally Complex Oxides for Anomalous Coupling Properties

Nontechnical Description: Electromechanically active materials experience mechanical strain - they stretch, compress, or shear - under applied electric fields. They represent an important example of materials with coupling properties – coupling electrical and mechanical properties in this case. Optimization of coupling properties for functional materials has been a key driver in materials research. Electromechanically active materials are essential components of actuators, sensors, and transducers used in applications ranging from medical ultrasound imaging to energy harvesting. Common electromechanically active materials contain lead. To advance lead-free alternatives, this project studies oxides with multiple types of cations (called compositionally complex oxides or CCOs) that can exhibit large mechanical deformation in response to an applied electric field. This project explores a vast compositional design space by integrating computation, experiments, and materials informatics into a unified framework that enables the prediction, search, and discovery of materials with exceptional properties. This framework could also be broadly applicable to the discovery and optimization of other types of materials with coupled electrical, mechanical, and thermal responses, potentially enabling future technologies that impact human health, energy harvesting, and national security. Technical Description: The project investigates electrostriction and thermal expansion in CCOs as examples of coupling properties. The project starts with fluorite oxides and artificially structured oxide multilayers, which provide precisely controlled model systems for testing computationally predicted structure-property relationships. The computational framework integrates a publicly available database of structure- and mechanism-sensitive response functions based on first-principles calculations, prediction of thermodynamic coupling properties with the tensorial cluster expansion method, and a physics-informed machine learning (ML) approach that can discover pathways to enhance desired mechanisms. This computational framework forms a “learning” loop with experiments on a subset of controlled structures and a “prediction” loop with bidirectional feedback between modeling and experiments. The experimental efforts target precisely controlled compositions, phase stabilities, and long- and short-range orders in CCO. Specifically, high-throughput bulk synthesis based on high-energy ball mill to prepare CCO powders and sintering them to dense specimens are performed at the University of California San Diego. Experimental efforts at Brown University focus on synthesizing artificially designed epitaxial thin films and heterostructures to form a subset of controlled structures for direct comparison with modeling. The project will deliver an extendable computational framework and design protocol for anomalous coupling properties; establish the mechanisms governing unusually large electrostriction and guide the discovery of high-performance lead-free electromechanical materials. 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.