Advancing Design and Discovery of 2D and Quasi-2D Perovskites via Combinatorial Synthesis and Characterization

The emergence of 2D and quasi-2D perovskites has opened exciting possibilities for next-generation optoelectronic devices. These materials exhibit unique electronic, optical, and transport properties, making them promising candidates for a wide range of applications including solar cells, light emitting diodes and radiation sensors. However, their complex structural and compositional nature presents significant challenges in the design and exploration of these materials.<br/>In this talk, I will discuss the use of high-throughput combinatorial synthesis and characterization techniques for the design, discovery, and exploration of 2D and quasi-2D hybrid perovskites [1,2]. By leveraging the power of automation, we can rapidly synthesize a diverse library of 2D and quasi-2D hybrid perovskite compositions and systematically investigate the effects of different synthesis parameters on the layer thickness and properties of these materials, facilitating the discovery of novel structures with enhanced performance.<br/>Furthermore, high-throughput characterization techniques including photoluminescence and Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS) [3] allow for rapid and comprehensive analysis of the synthesized materials. This multidimensional high-throughput characterization approach helps us understand the influence of synthesis parameters and composition on layer thickness, multi-phase formation and crystal structure on the optoelectronic properties of 2D and quasi-2D perovskites, paving the way for targeted design strategies.<br/>I will showcase recent advances in this field, including the discovery of new perovskite phases, general phase distributions in the quasi-2D hybrid perovskites compositional space, offering a comprehensive guide for designing phase-controlled systems [4].<br/><br/>References:<br/>Yang, J., Ahmadi, M. Empowering scientists with data-driven automated experimentation. <i>Nat. Synth</i> (2023). DOI: 10.1038/s44160-023-00337-z<br/>Yang J., Kalinin S.V., Cubuk E.D. Ziatdinov M., Ahmadi M. Toward self-organizing low-dimensional organic–inorganic hybrid perovskites: Machine learning-driven co-navigation of chemical and compositional spaces. <i>MRS Bulletin</i> <b>48</b>, 164–172 (2023). DOI: 10.1557/s43577-023-00490-y<br/>Yang J, Hidalgo J, Li R, Kalinin SV, Correa-Baena J-P, Ahmadi M. Accelerating materials discovery by high-throughput GIWAXS characterization of quasi-2D formamidinium metal halide perovskites. ChemRxiv (2023). 10.26434/chemrxiv-2023-x7sfr<br/>Yang J, Lawrie BJ, Kalinin SV, Ahmadi M. High-Throughput Automated Exploration of Phase Growth Kinetics in Quasi-2D Formamidinium Metal Halide Perovskites. ChemRxiv (2023). DOI: 10.26434/chemrxiv-2023-zcvl0