Accurate Dimension Prediction for Low-Dimensional Organic–Inorganic Halide Perovskites via a Self-Established Machine Learning Strategy-Reference-Cited by-同舟云学术

Accurate Dimension Prediction for Low-Dimensional Organic–Inorganic Halide Perovskites via a Self-Established Machine Learning Strategy

Published:2023-08-10 Issue:32 Volume:14 Page:7323-7330
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Yuan Songyang¹²,Liu Yulin¹²,Lan Jing¹²,Yang Wenjian¹²,Xiong Hui¹²,Li Wenzhe¹²^ORCID,Fan Jiandong¹²^ORCID

Affiliation:

1. Institute of New Energy Technology, Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, China

2. Key Laboratory of New Semiconductors and Devices of Guangdong Higher Education Institutes, Jinan University, Guangzhou 510631, China

Funder

State Key Laboratory of Crystal Materials

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Guangdong Basic and Applied Basic Research Foundation for Distinguished Young Scholar

Hundred Talents Program of Hubei Province

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.3c01915

Reference33 articles.

1. Advances in two-dimensional organic–inorganic hybrid perovskites

2. Giant Rashba splitting in 2D organic-inorganic halide perovskites measured by transient spectroscopies

3. White-Light Emission from Layered Halide Perovskites

4. Two-Dimensional Hybrid Halide Perovskites: Principles and Promises

5. Spin-dependent charge transport through 2D chiral hybrid lead-iodide perovskites

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