001     1005303
005     20250610131449.0
024 7 _ |a 10.26599/NRE.2023.9120057
|2 doi
024 7 _ |a 2128/34424
|2 Handle
024 7 _ |a WOS:001494133100001
|2 WOS
037 _ _ |a FZJ-2023-01415
082 _ _ |a 333.7
100 1 _ |a Yu, Yuan
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Metavalent bonding impacts charge carrier transport across grain boundaries
260 _ _ |a Beijing
|c 2023
|b Tsinghua University Press
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1684224556_1638
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Understanding the mechanisms underpinning the charge carrier scattering at grain boundaries is crucial to design thermoelectrics and other electronic materials. Yet, this is a very challenging task due to the complex characteristics of grain boundaries and the resulting difficulties in correlating grain boundary structures to local properties. Recent advances in characterizing charge transport across grain boundaries are reviewed, demonstrating how the microstructure, composition, chemical bonding and electrical properties of the same individual grain boundary can be correlated. A much higher potential barrier height is observed in high-angle grain boundaries. This can be ascribed to the larger number density of deep trapping states caused by the local collapse of metavalent bonding. A novel approach to study the influence of the local chemical bonding mechanism around defects on the resulting local properties is thus developed. The results provide insights into the tailoring of electronic properties of metavalently bonded compounds by engineering the characteristics of grain boundaries.
536 _ _ |a 5233 - Memristive Materials and Devices (POF4-523)
|0 G:(DE-HGF)POF4-5233
|c POF4-523
|f POF IV
|x 0
588 _ _ |a Dataset connected to DataCite
700 1 _ |a Wuttig, Matthias
|0 P:(DE-Juel1)176716
|b 1
773 _ _ |a 10.26599/NRE.2023.9120057
|g Vol. 2, p. e9120057 -
|0 PERI:(DE-600)3156672-8
|p e9120057 -
|t Nano research energy
|v 2
|y 2023
|x 2791-0091
856 4 _ |u https://juser.fz-juelich.de/record/1005303/files/nre-2-1-9120057.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1005303
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)176716
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-523
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Neuromorphic Computing and Network Dynamics
|9 G:(DE-HGF)POF4-5233
|x 0
914 1 _ |y 2023
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)PGI-10-20170113
|k PGI-10
|l JARA Institut Green IT
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)PGI-10-20170113
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21