Thermodynamic Stability Landscape of Halide Double Perovskites via High-Throughput Computing and Machine Learning-Reference-Cited by-同舟云学术

Thermodynamic Stability Landscape of Halide Double Perovskites via High-Throughput Computing and Machine Learning

Published:2019-01-17 Issue:9 Volume:29 Page:1807280
ISSN:1616-301X
Container-title:Advanced Functional Materials
language:en
Short-container-title:Adv. Funct. Mater.

Author:

Li Zhenzhu¹,Xu Qichen¹,Sun Qingde¹,Hou Zhufeng²,Yin Wan-Jian¹^ORCID

Affiliation:

1. College of Energy, Soochow Institute for Energy and Materials InnovationS (SIEMIS), and Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province; Soochow University; Suzhou 215006 China

2. Center for Materials Research by Information Integration; National Institute for Materials Science; 1-2-1 Sengen Tsukuba Ibaraki 305-0047 Japan

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Suzhou Key Laboratory for Advanced Carbon Materials and Wearable Energy Technologies, China

Publisher

Wiley

Subject

Electrochemistry,Condensed Matter Physics,Biomaterials,Electronic, Optical and Magnetic Materials

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/adfm.201807280/fullpdf

Reference64 articles.

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

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

3. Efficient Hybrid Solar Cells Based on Meso-Superstructured Organometal Halide Perovskites

4. Sequential deposition as a route to high-performance perovskite-sensitized solar cells

5. NREL, Best Research Cell-Efficiencies https://www.nrel.gov/pv/assets/pdfs/pv-efficiency-chart.20190103.pdf 2019

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