Almost Perfect Spin Filtering in Graphene-Based Magnetic Tunnel Junctions.
ACS Nano
; 16(9): 14007-14016, 2022 Sep 27.
Article
en En
| MEDLINE
| ID: mdl-36068013
We report on large spin-filtering effects in epitaxial graphene-based spin valves, strongly enhanced in our specific multilayer case. Our results were obtained by the effective association of chemical vapor deposited (CVD) multilayer graphene with a high quality epitaxial Ni(111) ferromagnetic spin source. We highlight that the Ni(111) spin source electrode crystallinity and metallic state are preserved and stabilized by multilayer graphene CVD growth. Complete nanometric spin valve junctions are fabricated using a local probe indentation process, and spin properties are extracted from the graphene-protected ferromagnetic electrode through the use of a reference Al2O3/Co spin analyzer. Strikingly, spin-transport measurements in these structures give rise to large negative tunnel magneto-resistance TMR = -160%, pointing to a particularly large spin polarization for the Ni(111)/Gr interface PNi/Gr, evaluated up to -98%. We then discuss an emerging physical picture of graphene-ferromagnet systems, sustained both by experimental data and ab initio calculations, intimately combining efficient spin filtering effects arising (i) from the bulk band structure of the graphene layers purifying the extracted spin direction, (ii) from the hybridization effects modulating the amplitude of spin polarized scattering states over the first few graphene layers at the interface, and (iii) from the epitaxial interfacial matching of the graphene layers with the spin-polarized Ni surface selecting well-defined spin polarized channels. Importantly, these main spin selection effects are shown to be either cooperating or competing, explaining why our transport results were not observed before. Overall, this study unveils a path to harness the full potential of low Resitance.Area (RA) graphene interfaces in efficient spin-based devices.
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Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
ACS Nano
Año:
2022
Tipo del documento:
Article
País de afiliación:
Francia
Pais de publicación:
Estados Unidos