Quantifying Mn diffusion through transferred versus directly-grown graphene barriers
Patrick J. Strohbeen, Sebastian Manzo, Vivek Saraswat, Katherine Su,, Michael S. Arnold, Jason K. Kawasaki

TL;DR
This study compares manganese diffusion through transferred versus directly-grown graphene barriers on semiconductor substrates, revealing that direct growth significantly reduces diffusion and defect-related diffusion pathways.
Contribution
It provides quantitative analysis of Mn diffusion mechanisms through graphene, emphasizing the impact of growth method and defect density on diffusion barriers.
Findings
Direct-grown graphene reduces Mn diffusion by 1000 times compared to no graphene.
Transferred graphene suppresses Mn diffusion by a factor of 10 compared to no graphene.
Diffusion primarily occurs at graphene defects, with low activation energy.
Abstract
We quantify the mechanisms for manganese (Mn) diffusion through graphene in Mn/graphene/Ge (001) and Mn/graphene/GaAs (001) heterostructures for samples prepared by graphene layer transfer versus graphene growth directly on the semiconductor substrate. These heterostructures are important for applications in spintronics; however, challenges in synthesizing graphene directly on technologically important substrates such as GaAs necessitate layer transfer and anneal steps, which introduce defects into the graphene. \textit{In-situ} photoemission spectroscopy measurements reveal that Mn diffusion through graphene grown directly on a Ge (001) substrate is 1000 times lower than Mn diffusion into samples without graphene (cm/s, cm/s at 500C). Transferred graphene on Ge suppresses the Mn in Ge diffusion by a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
