The detection of Kondo effect in the resistivity of graphene: artifacts and strategies
Johannes Jobst, Ferdinand Kisslinger, Heiko B. Weber

TL;DR
This paper explores the challenges in identifying the Kondo effect in graphene's resistivity, proposing refined analysis methods and simulations to distinguish it from similar phenomena like electron-electron interactions.
Contribution
It introduces a new evaluation scheme combining numerical simulations and experimental analysis to reliably differentiate Kondo effects from other quantum corrections in graphene.
Findings
Logarithmic corrections can arise from multiple effects, not just Kondo physics.
The proposed analysis can distinguish between Kondo effect and electron-electron interactions.
Experimental data alone are insufficient to confirm Kondo physics without thorough evaluation.
Abstract
We discuss the difficulties to discover Kondo effect in the resistivity of graphene. Similarly to the Kondo effect, electron-electron interaction effects and weak localization appear as logarithmic corrections to the resistance. In order to disentangle these contributions, a refined analysis of the magnetoconductance and the magnetoresistance is introduced. We present numerical simulations which display the discrimination of both effects. Further, we present experimental data of magnetotransport. When magnetic molecules are added to graphene, a logarithmic correction to the conductance occurs, which apparently suggests Kondo physics. Our thorough evaluation scheme, however, reveals that this interpretation is not conclusive: the data can equally be explained by electron-electron interaction corrections in an inhomogeneous sample. Our evaluation scheme paves the way for a more refined…
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.
