|
|
|
|
LEADER |
01000caa a22002652 4500 |
001 |
NLM372836895 |
003 |
DE-627 |
005 |
20240809232506.0 |
007 |
cr uuu---uuuuu |
008 |
240526s2024 xx |||||o 00| ||eng c |
024 |
7 |
|
|a 10.1002/jcc.27434
|2 doi
|
028 |
5 |
2 |
|a pubmed24n1496.xml
|
035 |
|
|
|a (DE-627)NLM372836895
|
035 |
|
|
|a (NLM)38795374
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
100 |
1 |
|
|a Sannino, Gennaro Vincenzo
|e verfasserin
|4 aut
|
245 |
1 |
0 |
|a Effective prediction of SnO2 conduction band edge potential
|b The key role of surface oxygen vacancies
|
264 |
|
1 |
|c 2024
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
500 |
|
|
|a Date Revised 09.08.2024
|
500 |
|
|
|a published: Print-Electronic
|
500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
520 |
|
|
|a © 2024 Wiley Periodicals LLC.
|
520 |
|
|
|a Several theoretical studies at different levels of theory have attempted to calculate the absolute position of the SnO2 conduction band, whose knowledge is key for its effective application in optoelectronic devices such us, for example, perovskite solar cells. However, the predicted band edges fall outside the experimentally measured range. In this work, we introduce a computational scheme designed to calculate the conduction band minimum values of SnO2, yielding results aligned with experiments. Our analysis points out the fundamental role of encompassing surface oxygen vacancies to properly describe the electronic profile of this material. We explore the impact of both bridge and in-plane oxygen vacancy defects on the structural and electronic properties of SnO2, explaining from an atomistic perspective the experimental observables. The results underscore the importance of simulating both types of defects to accurately predict SnO2 features and provide new fundamental insights that can guide future studies concerning design and optimization of SnO2-based materials and functional interfaces
|
650 |
|
4 |
|a Journal Article
|
700 |
1 |
|
|a Pecoraro, Adriana
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Veneri, Paola Delli
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Pavone, Michele
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Muñoz-García, Ana Belén
|e verfasserin
|4 aut
|
773 |
0 |
8 |
|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 45(2024), 26 vom: 05. Aug., Seite 2198-2203
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
|
773 |
1 |
8 |
|g volume:45
|g year:2024
|g number:26
|g day:05
|g month:08
|g pages:2198-2203
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1002/jcc.27434
|3 Volltext
|
912 |
|
|
|a GBV_USEFLAG_A
|
912 |
|
|
|a SYSFLAG_A
|
912 |
|
|
|a GBV_NLM
|
912 |
|
|
|a GBV_ILN_350
|
951 |
|
|
|a AR
|
952 |
|
|
|d 45
|j 2024
|e 26
|b 05
|c 08
|h 2198-2203
|