硫系化合物
材料科学
卤化物
氧化物
钙钛矿(结构)
因子(编程语言)
纳米技术
化学工程
光电子学
无机化学
冶金
计算机科学
化学
工程类
程序设计语言
作者
Jonathan W. Turnley,Shubhanshu Agarwal,Rakesh Agrawal
出处
期刊:Materials horizons
[Royal Society of Chemistry]
日期:2024-01-01
卷期号:11 (19): 4802-4808
被引量:2
摘要
Tolerance factor analysis has been widely used to predict suitable compositions for oxide and halide perovskites. However, in the case of the emerging chalcogenide perovskites, the predictions from the tolerance factor have failed to align with experimental observations. In this work, we reconsider how tolerance factor is being applied, specifically adjusting for the effect of increased covalency of bonding on the ionic radii. Further, we propose a series of screening steps based on the octahedral factor, tolerance factor, and electronegativity difference to better predict the formation of sulfide perovskites.
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