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Dokumenttyp:
Konferenzbeitrag 
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz 
Autor(en):
Stanley, J.; Gagliardi, A. 
Titel:
Machine Learning Bandgaps of Inorganic Mixed Halide Perovskites 
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:
2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO) 
Kongress / Zusatzinformationen:
Cork, Ireland, 23-26 July 2018 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