Predicting the photon energy of quasi-2D lead halide perovskites from the precursor composition through machine learning

Predicting the photon energy of quasi-2D lead halide perovskites from the precursor composition through machine learning

Quasi-2D perovskites with the general formula of L2An−1PbnX3n+1 (L = organic spacer cation, A = small organic cation or inorganic cation, X = halide ion, and n ≤ 5) are an emerging kind of luminescent material. Their emission color can be easily tuned by their composition and n value. Accurate predi...

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Bibliographic Details
Main Authors: Huang, X. (Author), Li, Y. (Author), Qiao, B. (Author), Shi, H. (Author), Song, D. (Author), Wang, W. (Author), Wei, D. (Author), Xu, Z. (Author), Zhao, S. (Author), Zou, A. (Author)
Format: Article
Language:English
Published: Royal Society of Chemistry 2022
Subjects:
Decision trees
Forecasting
General formulas
Halide perovskites
Inorganic cations
Lead compounds
Machine learning
Mean square error
Organic cations
Organic spacers
Organic/inorganic
Perovskite
Photon energy
Photons
Positive ions
Precursor composition
Quasi-2d
Random forest modeling
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