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Can I read Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants on EtoBox?
Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants by Magdalena Miodyńska; Alicja Mikolajczyk; Paweł Mazierski; Tomasz Klimczuk; Wojciech Lisowski; Grzegorz Trykowski; Adriana Zaleska-Medynska is a Materials Science article available to read on EtoBox.
What is Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants about?
The use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs 3 Bi 2 X 9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore, the most promising Pb-free Bi-based Cs 3 Bi 2 X 9 perovskites (i.e., structures that present an optimal combination of structural features and efficiency) were selected using a machine learning based virtual screening methodology and enriched with the C 3 N 4 composite. The selected and designed Cs 3 Bi 2 (Cl/Br) 9 structures were in line with the "safe and sustainable by design" approach and applied for the first time in the aforementioned reaction, which allowed for approximately 84% efficiency under visible light. The main merit of this achievement was the optimum deposition of perovskite Cs 3 Bi 2 (Cl/Br) 9 (5 wt%) on the C 3 N 4 matrix, which resulted in approximately a two-fold increase in the apparent quantum efficiency of the composite compa
Who reads Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants?
It is typically read by researchers, students, and practitioners in Materials Science.
- Author
- Magdalena Miodyńska; Alicja Mikolajczyk; Paweł Mazierski; Tomasz Klimczuk; Wojciech Lisowski; Grzegorz Trykowski; Adriana Zaleska-Medynska
- Publisher
- Elsevier BV
- Published
- 2022
- Language
- EN
- Field
- Materials Science (Physical Sciences)