Ultrafast Electron Dynamics in Epitaxial Graphene Investigated with Time- and Angle-Resolved Photoemission Spectroscopy
S{\o}ren Ulstrup, Jens Christian Johannsen, Alberto Crepaldi, Federico, Cilento, Michele Zacchigna, Cephise Cacho, Richard T. Chapman, Emma, Springate, Felix Fromm, Christian Raidel, Thomas Seyller, Fulvio Parmigiani,, Marco Grioni, Philip Hofmann

TL;DR
This study uses ultrafast time- and angle-resolved photoemission spectroscopy to investigate electron dynamics in epitaxial graphene on different substrates, revealing substrate-dependent hot carrier behaviors and relaxation processes.
Contribution
It provides new insights into ultrafast electron interactions in graphene supported on semiconducting and metallic substrates, highlighting substrate effects on hot carrier dynamics.
Findings
Hot carrier dynamics are complex on semiconducting substrates, with increased electronic temperature and linewidth.
On metallic substrates, hot carrier dynamics are suppressed due to screening effects.
Electron relaxation channels can be disentangled through analysis of these ultrafast processes.
Abstract
In order to exploit the intriguing optical properties of graphene it is essential to gain a better understanding of the light-matter interaction in the material on ultrashort timescales. Exciting the Dirac fermions with intense ultrafast laser pulses triggers a series of processes involving interactions between electrons, phonons and impurities. Here we study these interactions in epitaxial graphene supported on silicon carbide (semiconducting) and iridium (metallic) substrates using ultrafast time- and angle-resolved photoemission spectroscopy (TR-ARPES) based on high harmonic generation. For the semiconducting substrate we reveal a complex hot carrier dynamics that manifests itself in an elevated electronic temperature and an increase in linewidth of the band. By analyzing these effects we are able to disentangle electron relaxation channels in graphene. On the metal substrate…
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.
