Rationalizing Perovskite Data for Machine Learning and Materials Design-Reference-Cited by-同舟云学术

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Rationalizing Perovskite Data for Machine Learning and Materials Design

Published:2018-11-27 Issue:24 Volume:9 Page:6948-6954
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Xu Qichen¹²,Li Zhenzhu¹²,Liu Miao³,Yin Wan-Jian¹²^ORCID

Affiliation:

1. College of Energy, Soochow Institute for Energy and Materials InnovationS (SIEMIS), Soochow University, Suzhou 215006, China

2. Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province, Soochow University, Suzhou 215006, China

3. Institute of Physics (IOP), Chinese Academy of Science (CAS), Beijing 100100, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.8b03232

Reference35 articles.

1. Oxide perovskites, double perovskites and derivatives for electrocatalysis, photocatalysis, and photovoltaics

2. Chemical Structures and Performance of Perovskite Oxides

3. The emergence of perovskite solar cells

4. Organometal Halide Perovskites as Visible-Light Sensitizers for Photovoltaic Cells

5. Lead Iodide Perovskite Sensitized All-Solid-State Submicron Thin Film Mesoscopic Solar Cell with Efficiency Exceeding 9%

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