Understanding the kinetics of the crystallization process for organometal halide perovskite formation is critical in determining the crystalline, nanoscale morphology and therefore the electronic properties of the films produced during thin film formation from solution. In this work, in situ grazing incidence small-angle X-ray scattering (GISAXS) and optical microscopy measurements are used to investigate the processes of nucleation and growth of pristine mixed halide perovskite (MAPbI 3– x Cl x ) crystalline films deposited by bar coating at 60 °C, with and without additives in the solution. A small amount of 1,8-diiodooctane (DIO) and hydriodic acid (HI) added to MAPbI 3– x Cl x is shown to increase the numbers of nucleation centers promoting heterogeneous nucleation and accelerate and modify the size of nuclei during nucleation and growth. A generalized formation mechanism is derived from the overlapping parameters obtained from real-time GISAXS and optical microscopy, which revealed that during nucleation, perovskite precursors cluster before becoming the nuclei that function as elemental units for subsequent formation of perovskite crystals. Additive-free MAPbI 3– x Cl x follows reaction-controlled growth, in contrast with when DIO and HI are present, and it is highly possible that the growth then follows a hindered diffusion-controlled mechanism. These results provide important details of the crystallization mechanisms occurring and will help to develop greater control over perovskite films produced.
A predictive model correlating the properties of a catalyst with its performance would be beneficial for the development, from biomass waste, of new, carbon-supported and Earth-abundant metal oxide catalysts. In this work, the effects of copper and iron oxide crystallite size on the performance of the catalysts in reducing nitrogen oxides, in terms of nitrogen oxide conversion and nitrogen selectivity, are investigated. The catalysts are prepared via the incipient wetness method over activated carbon, derived from palm kernel shells. The surface morphology and particle size distribution are examined via field emission scanning electron microscopy, while crystallite size is determined using the wide-angle X-ray scattering and small-angle X-ray scattering methods. It is revealed that the copper-to-iron ratio affects the crystal phases and size distribution over the carbon support. Catalytic performance is then tested using a packed-bed reactor to investigate the nitrogen oxide conversion and nitrogen selectivity. Departing from chemical characterization, two predictive equations are developed via an artificial neural network technique—one for the prediction of NOx conversion and another for N2 selectivity. The model is highly applicable for 250–300 °C operating temperatures, while more data are required for a lower temperature range.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.