We must go small and fast to go big: Accelerating the Transition from Lab to Fab via High Throughput Automated Synthesis and Characterization
Mahshid Ahmadi a, Jonghee Yang a b, Sheryl Sanchez a, Elham Foadian a
a Institute for Advanced Materials and Manufacturing Department of Materials Science and Engineering, University of Tennessee Knoxville, Knoxville, TN 37996, USA
b Department of Chemistry, Yonsei University, Seoul 03722, Republic of Korea
NIPHO
Proceedings of International Conference on Perovskite Thin Film Photovoltaics and Perovskite Photonics and Optoelectronics (NIPHO24)
Sardinia, Italy, 2024 June 17th - 18th
Organizers: Giulia Grancini, Francesca Brunetti and Maria Antonietta Loi
Invited Speaker, Mahshid Ahmadi, presentation 021
Publication date: 25th April 2024

The exceptional properties of metal halide perovskites make them ideal materials for photovoltaic applications, with the promise to completely disrupt the areas of building-based, utility scale, and space-based photovoltaic. However, the fundamental principles of microstructure formation, evolution, and stability that are crucial for designing functional perovskite devices are understood only weakly. Currently, this is the only remaining bottleneck for the lab-to-fab transformation and realization of the scalable manufacturing of these materials. In this talk, I will discuss the potential of machine learning-driven high throughput automated experiments to expedite the discovery of metal halide perovskites, optimize processing pathways, and enhance understanding of formation kinetics1-5. Additionally, I will showcase how high throughput automated synthesis provides a comprehensive guide for designing optimal precursor stoichiometry to achieve functional quasi-2D perovskite phases in films capable of realizing high-performance optoelectronics3,4. I further introduce the concept of co-navigation of theory and experiment spaces to accelerate the discovery and design of metal halide perovskites. These studies exemplify how a high-throughput automated experimental workflow effectively expedites discoveries and processing optimizations in complex materials systems with multiple functionalities, facilitating their realization in scalable optoelectronic manufacturing processes.

© FUNDACIO DE LA COMUNITAT VALENCIANA SCITO
We use our own and third party cookies for analysing and measuring usage of our website to improve our services. If you continue browsing, we consider accepting its use. You can check our Cookies Policy in which you will also find how to configure your web browser for the use of cookies. More info