The Harvard organic photovoltaic dataset

The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functiona...

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Autores principales: Lopez, Steven A., Pyzer-Knapp, Edward O., Simm, Gregor N., Lutzow, Trevor, Li, Kewei, Seress, Laszlo R., Hachmann, Johannes, Aspuru-Guzik, Alán
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037972/
https://www.ncbi.nlm.nih.gov/pubmed/27676312
http://dx.doi.org/10.1038/sdata.2016.86
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author Lopez, Steven A.
Pyzer-Knapp, Edward O.
Simm, Gregor N.
Lutzow, Trevor
Li, Kewei
Seress, Laszlo R.
Hachmann, Johannes
Aspuru-Guzik, Alán
author_facet Lopez, Steven A.
Pyzer-Knapp, Edward O.
Simm, Gregor N.
Lutzow, Trevor
Li, Kewei
Seress, Laszlo R.
Hachmann, Johannes
Aspuru-Guzik, Alán
author_sort Lopez, Steven A.
collection PubMed
description The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications.
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spelling pubmed-50379722016-10-04 The Harvard organic photovoltaic dataset Lopez, Steven A. Pyzer-Knapp, Edward O. Simm, Gregor N. Lutzow, Trevor Li, Kewei Seress, Laszlo R. Hachmann, Johannes Aspuru-Guzik, Alán Sci Data Data Descriptor The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications. Nature Publishing Group 2016-09-27 /pmc/articles/PMC5037972/ /pubmed/27676312 http://dx.doi.org/10.1038/sdata.2016.86 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.
spellingShingle Data Descriptor
Lopez, Steven A.
Pyzer-Knapp, Edward O.
Simm, Gregor N.
Lutzow, Trevor
Li, Kewei
Seress, Laszlo R.
Hachmann, Johannes
Aspuru-Guzik, Alán
The Harvard organic photovoltaic dataset
title The Harvard organic photovoltaic dataset
title_full The Harvard organic photovoltaic dataset
title_fullStr The Harvard organic photovoltaic dataset
title_full_unstemmed The Harvard organic photovoltaic dataset
title_short The Harvard organic photovoltaic dataset
title_sort harvard organic photovoltaic dataset
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037972/
https://www.ncbi.nlm.nih.gov/pubmed/27676312
http://dx.doi.org/10.1038/sdata.2016.86
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