Perovskite Quantum Dots Modeled Using ab Initio and Replica Exchange Molecular Dynamics
KAUST Grant NumberKUS-11-009-21
Online Publication Date2015-06-08
Print Publication Date2015-06-18
Permanent link to this recordhttp://hdl.handle.net/10754/599169
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Abstract© 2015 American Chemical Society. Organometal halide perovskites have recently attracted tremendous attention at both the experimental and theoretical levels. Much of this work has been dedicated to bulk material studies, yet recent experimental work has shown the formation of highly efficient quantum-confined nanocrystals with tunable band edges. Here we investigate perovskite quantum dots from theory, predicting an upper bound of the Bohr radius of 45 Å that agrees well with literature values. When the quantum dots are stoichiometric, they are trap-free and have nearly symmetric contributions to confinement from the valence and conduction bands. We further show that surface-associated conduction bandedge states in perovskite nanocrystals lie below the bulk states, which could explain the difference in Urbach tails between mesoporous and planar perovskite films. In addition to conventional molecular dynamics (MD), we implement an enhanced phase-space sampling algorithm, replica exchange molecular dynamics (REMD). We find that in simulation of methylammonium orientation and global minima, REMD outperforms conventional MD. To the best of our knowledge, this is the first REMD implementation for realistic-sized systems in the realm of DFT calculations.
CitationBuin A, Comin R, Ip AH, Sargent EH (2015) Perovskite Quantum Dots Modeled Using ab Initio and Replica Exchange Molecular Dynamics. The Journal of Physical Chemistry C 119: 13965–13971. Available: http://dx.doi.org/10.1021/acs.jpcc.5b03613.
SponsorsThis publication is based in part on work supported by Award KUS-11-009-21, made by King Abdullah University of Science and Technology (KAUST), by the Ontario Research Fund Research Excellence Program, and by the Natural Sciences and Engineering Research Council (NSERC) of Canada. Computations were performed on the Southern Ontario Smart Computing Innovation Platform (SOSCIP) Blue Gene/Q supercomputer located at the University of Toronto’s SciNet(50) HPC facility. The SOSCIP multiuniversity/industry consortium is funded by the Ontario Government, and the Federal SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund—Research Excellence; and the University of Toronto.
PublisherAmerican Chemical Society (ACS)