At the very heart of the global semiconductor industry lies the omnipresent push for new materials discovery. New materials constantly rise and fall out of fashion in the scientific literature, with those passing an initial phase of research scrutiny becoming hotbeds of characterization and optimization efforts. Yet, innumerable hours of painstaking research have been devoted to materials that have ultimately fallen by the wayside after crossing over an indefinable threshold, whereupon historical optimism is met with newfound skepticism. Materials have to perform well, and they have to do it quickly. In the past decade, metal-halide perovskites (MHPs) have garnered widespread attention. The hegemonic view in both academic and industrial circles is that these materials could be engineered to meet the demands of the semiconductor industry. Their promise as inexpensive solar cell devices is highly attractive, and it has been nothing short of remarkable that efficiencies have risen from 3.8% in 2009 to more than 25.5% in 2021. Moreover, MHPs are poised to be revolutionary materials in more ways than one. The highest MHP LED efficiency was recently reported (23.4%), and MHPs have demonstrated promise in photodetectors, memristors, and transistors. However, the many excellent properties of MHPs are contrasted by longstanding stability and reproducibility limitations that have hindered their commercialization. Overcoming the limitations of MHPs is ultimately a materials engineering problem, which should be solved by mapping more precise relationships between structure, composition, and device performance. In 1958, Francis Crick famously developed the central dogma of molecular biology which describes the unidirectional flow of information in biological systems. In the words of Crick, "nature has devised a unique instrument in which an underlying simplicity is used to express great subtlety and versatility." In this Account, taking inspiration from the hierarchical organization of nature, we describe a hierarchical approach to materials engineering of organic metal-halide semiconductors. We demonstrate that organo-metal halide semiconductors' dimensionality, composition, and morphology dictate their optoelectronic properties and can be exploited in defining more explicit relationships between structure and function. Here, we traverse three-dimensional (3D), two-dimensional (2D), and one-dimensional (1D) organo-metal halide semiconductors, detailing the morphological and compositional differences in each and the implications that can be drawn within each domain on the engineering process. Control over ion migration pathways via morphology engineering as well as control over charge formation in organic-inorganic semiconductors is demonstrated. Fundamental insights into the amount of static and dynamic disorder in the MHP lattice are provided, which can be continuously tuned as a function of composition and morphology. Using electroabsorption spectroscopy on 2D MHPs, a disorder-induced dipole moment in the exciton proportional to the summed value of static and dynamic disorder is measured. Spectroscopic isolation of exciton features in 2D MHP electroabsorption spectra allows us to obtain precise, model-independent measurements of exciton binding energies to study the effect of chemical substitutions, such as Sn2+ → Pb2+, on the value of the exciton binding energy. Finally, we conclude that this multidimensional platform, with the aid of machine learning and robotics, will be foundational in accurately predicting structure-property-device relationships in organo-metal halide semiconductors in the future.
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