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Titel:

Machine Learning Bandgaps of Inorganic Mixed Halide Perovskites

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Stanley, J.; Gagliardi, A.
Abstract:
The identification of suitable lead-free perovskites is crucial for their envisioned applications in photovoltaics. Efficient and accurate vetting of these compounds for a range of properties has recently been accomplished in high-throughput studies by use of statistical learning methods. Here we demonstrate how one such property, the fundamental bandgap, can be predicted for a family of inorganic mixed halide perovskites using fingerprints based solely on the atomic arrangement of the unit cell...     »
Kongress- / Buchtitel:
IEEE 18th International Conference on Nanotechnology (IEEE-NANO)
Kongress / Zusatzinformationen:
Cork, Ireland, 23-26 July 2018-07
Verlag / Institution:
IEEE Xplore Digital Library
Jahr:
2018
Quartal:
3. Quartal
Jahr / Monat:
2018-07
Monat:
Jul
Print-ISBN:
978-1-5386-5337-1
E-ISBN:
978-1-5386-5336-4
Serien-ISSN:
1944-9380 1944-9399
Sprache:
en
Volltext / DOI:
doi:10.1109/NANO.2018.8626420
WWW:
https://ieeexplore.ieee.org/document/8626420
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