8:00 PM - MT02.12.14
Discovery Paradigm for Novel Organic-Inorganic Halide Perovskites for Optoelectronic Applications through Automated Synthesis
Mahshid Ahmadi1,Katherine Higgins1,Maxim Ziatdinov2,Rama Vasudevan2,Sergei Kalinin2
University of Tennessee, Knoxville1,Oak Ridge National Laboratory2
Hybrid organic-inorganic perovskites (HOIPs) are rapidly emerging as one of the most fascinating materials for photovoltaic, light emission, lasing, and sensing applications1-4. In general, three-dimensional (3D) HOIPs adopt the typical perovskite crystal structure of ABX3, where A, B, and X denote monovalent organic or inorganic cations (e.g., CH6N+ (MA+), CH5N2+ (FA+), guanidinium (GA+), Cs+ and Rb+), divalent inorganic cations (Pb2+, Sn2+), and halide anions (I−, Br−, Cl−), respectively. These compounds are among more than one thousand perovskite-inspired candidate compounds that have been theoretically predicted during the last few years5, 6. However, despite extensive theoretical studies, only a small fraction of predicted compounds has been experimentally realized since synthesis of each new material involved complex and time-consuming optimization cycle for synthesis. In addition, optimizing these materials for specific applications requires careful balance between intrinsic properties such as bandgap, defect chemistry, charge transport and crystal structures that affects material microstructure, and poorly understood parameters such as chemical stability of surfaces and interfaces. In this presentation we will demonstrate the first results on the automated synthesis and characterization for the combinatorial libraries of HOIPs. Using automated laboratory synthesis, we demonstrate formation of the library of HOIP compositions. Next, an automated characterization tool with capability of UV-Vis absorption and photoluminescence (PL) spectroscopy is used to rapidly measure the band gap energy and PL properties across the composition library. Finally, machine learning applied to the optical properties allows rapid elucidation of property evolution along 2- and 3-dimensional phase fields. We further discuses application of Gaussian process optimization for evolutionary search in the high dimensional composition spaces and balance between exploration and exploitative searches targeting individual aspects of figure of merits and their combinations. The synergy of compositional, and optical properties such as band gap and photoluminescence spectroscopy developed here allows a comprehensive picture of the functionality evolution across the composition series and attempts to establish predictive relationships across the composition in these material systems.
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