Issue 5, 2019
From the journal:

Physical Chemistry Chemical Physics

Correction: Exploring new approaches towards the formability of mixed-ion perovskites by DFT and machine learning

Heesoo Park,*a   Raghvendra Mall,b   Fahhad H. Alharbi,ac   Stefano Sanvito,d   Nouar Tabet,ac   Halima Bensmailb  and  Fedwa El-Mellouhi*a  

* Corresponding authors

a Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, PO Box 34110, Doha, Qatar
E-mail: hpark@hbku.edu.qa, felmellouhi@hbku.edu.qa

b Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar

c College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

d School of Physics, AMBER and CRANN Institute, Trinity College, Dublin 2, Ireland

Abstract

Correction for ‘Exploring new approaches towards the formability of mixed-ion perovskites by DFT and machine learning’ by Heesoo Park et al., Phys. Chem. Chem. Phys., 2019, DOI: 10.1039/c8cp06528d.

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Article information

DOI
https://doi.org/10.1039/C9CP90013F
Article type
Correction
Submitted
08 Jan 2019
Accepted
08 Jan 2019
First published
18 Jan 2019
This article is Open Access
Creative Commons BY license

Phys. Chem. Chem. Phys., 2019,21, 2821-2821

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Correction: Exploring new approaches towards the formability of mixed-ion perovskites by DFT and machine learning

H. Park, R. Mall, F. H. Alharbi, S. Sanvito, N. Tabet, H. Bensmail and F. El-Mellouhi, Phys. Chem. Chem. Phys., 2019, 21, 2821 DOI: 10.1039/C9CP90013F

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