Electrical tunability of terahertz nonlinearity in graphene

Kovalev S, Eid HAH, Tielrooij K-J, Deinert J-C, Ilyakov I, Awari N, Alcaraz D, Soundarapandian K, Saleta D, Germanskiy S, Chen M, et al. (2021)
Science advances 7(15): eabf9809.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Kovalev, Sergey; Eid, Hassan A. HafezUniBi; Tielrooij, Klaas-Jan; Deinert, Jan-Christoph; Ilyakov, Igor; Awari, Nilesh; Alcaraz, David; Soundarapandian, Karuppasamy; Saleta, David; Germanskiy, Semyon; Chen, Min; Bawatna, Mohammed
Alle
Abstract / Bemerkung
Graphene is conceivably the most nonlinear optoelectronic material we know. Its nonlinear optical coefficients in the terahertz frequency range surpass those of other materials by many orders of magnitude. Here, we show that the terahertz nonlinearity of graphene, both for ultrashort single-cycle and quasi-monochromatic multicycle input terahertz signals, can be efficiently controlled using electrical gating, with gating voltages as low as a few volts. For example, optimal electrical gating enhances the power conversion efficiency in terahertz third-harmonic generation in graphene by about two orders of magnitude. Our experimental results are in quantitative agreement with a physical model of the graphene nonlinearity, describing the time-dependent thermodynamic balance maintained within the electronic population of graphene during interaction with ultrafast electric fields. Our results can serve as a basis for straightforward and accurate design of devices and applications for efficient electronic signal processing in graphene at ultrahigh frequencies. Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).
Erscheinungsjahr
2021
Zeitschriftentitel
Science advances
Band
7
Ausgabe
15
Art.-Nr.
eabf9809
eISSN
2375-2548
Page URI
https://pub.uni-bielefeld.de/record/2954076

Zitieren

Kovalev S, Eid HAH, Tielrooij K-J, et al. Electrical tunability of terahertz nonlinearity in graphene. Science advances. 2021;7(15): eabf9809.
Kovalev, S., Eid, H. A. H., Tielrooij, K. - J., Deinert, J. - C., Ilyakov, I., Awari, N., Alcaraz, D., et al. (2021). Electrical tunability of terahertz nonlinearity in graphene. Science advances, 7(15), eabf9809. https://doi.org/10.1126/sciadv.abf9809
Kovalev, Sergey, Eid, Hassan A. Hafez, Tielrooij, Klaas-Jan, Deinert, Jan-Christoph, Ilyakov, Igor, Awari, Nilesh, Alcaraz, David, et al. 2021. “Electrical tunability of terahertz nonlinearity in graphene”. Science advances 7 (15): eabf9809.
Kovalev, S., Eid, H. A. H., Tielrooij, K. - J., Deinert, J. - C., Ilyakov, I., Awari, N., Alcaraz, D., Soundarapandian, K., Saleta, D., Germanskiy, S., et al. (2021). Electrical tunability of terahertz nonlinearity in graphene. Science advances 7:eabf9809.
Kovalev, S., et al., 2021. Electrical tunability of terahertz nonlinearity in graphene. Science advances, 7(15): eabf9809.
S. Kovalev, et al., “Electrical tunability of terahertz nonlinearity in graphene”, Science advances, vol. 7, 2021, : eabf9809.
Kovalev, S., Eid, H.A.H., Tielrooij, K.-J., Deinert, J.-C., Ilyakov, I., Awari, N., Alcaraz, D., Soundarapandian, K., Saleta, D., Germanskiy, S., Chen, M., Bawatna, M., Green, B., Koppens, F.H.L., Mittendorff, M., Bonn, M., Gensch, M., Turchinovich, D.: Electrical tunability of terahertz nonlinearity in graphene. Science advances. 7, : eabf9809 (2021).
Kovalev, Sergey, Eid, Hassan A. Hafez, Tielrooij, Klaas-Jan, Deinert, Jan-Christoph, Ilyakov, Igor, Awari, Nilesh, Alcaraz, David, Soundarapandian, Karuppasamy, Saleta, David, Germanskiy, Semyon, Chen, Min, Bawatna, Mohammed, Green, Bertram, Koppens, Frank H L, Mittendorff, Martin, Bonn, Mischa, Gensch, Michael, and Turchinovich, Dmitry. “Electrical tunability of terahertz nonlinearity in graphene”. Science advances 7.15 (2021): eabf9809.
Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 33827824
PubMed | Europe PMC

Suchen in

Google Scholar