AbstractThe high demand for energy consumption in everyday life, and fears of climate change are driving the scientific community to explore prospective materials for efficient energy conversion and storage. Perovskites, a prominent category of materials, including metal halides and perovskite oxides have a significant role as energy materials, and can effectively replace conventional materials. The simultaneous need for new energy materials together with the increased interest for making new devices, and exploring new physics, thrust the research to control the structuring of the perovskite materials at the nanoscale. Nanostructuring of the perovskites offers unique features such as a large surface area, extensive porous structures, controlled transport and charge-carrier mobility, strong absorption and photoluminescence, and confinement effects. These features together with the unique tunability in their composition, shape, and functionalities make perovskite nanocrystals efficient for energy-related applications such as photovoltaics, catalysts, thermoelectrics, batteries, supercapacitor and hydrogen storage systems. The synthesis procedures of perovskite nanostructures in different morphologies is summarized and the energy-related properties and applications are extensively discussed in this paper.
Automated machine learning structure-composition-property relationships of perovskite materials for energy conversion and storage
