Desorption timescales on epitaxial graphene via Fermi level shifting and Reststrahlen monitoring

Archive ouverte : Article de revue

Tran, Ngoc Thanh Mai | Mhatre, Swapnil | Santos, Cristiane | Biacchi, Adam | Kelley, Mathew | Hill, Heather | Saha, Dipanjan | Liang, Chi-Te | Elmquist, Randolph | Newell, David | Hackens, Benoit | Hacker, Christina | Rigosi, Albert

Edité par HAL CCSD ; Elsevier

International audience. This work reports information on the transience of hole doping in epitaxial graphene devices when nitric acid is used as an adsorbent. Under vacuum conditions, desorption processes are monitored by electrical and spectroscopic means to extract the relevant timescales from the corresponding data. It is of vital importance to understand the reversible nature of hole doping because such device processing can be a suitable alternative to large-scale, metallic gating. Most measurements are performed post-exposure at room temperature, and, for some electrical transport measurements, at 1.5 K. Vacuum conditions are applied to many measurements to replicate the laboratory conditions under which devices using this doping method would be measured. The relevant timescales from transport measurements are compared with results from X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy measurements, with the latter performed at ambient conditions and accompanied by calculations of the spectra in the Reststrahlen band.

Consulter en ligne

Suggestions

Du même auteur

Split-ring resonators imaged by THz s-SNOM

Archive ouverte: Communication dans un congrès

Santos, Cristiane | 2022-08-28

International audience. Split-ring resonators (SRRs) are one of the most common building blocks to design metamaterials operating over a large range of frequencies in the electromagnetic spectrum. Here we acquire s-...

PFM and s-SNOM imaging of minimally-twisted double bilayer graphene: moirés...

Archive ouverte: Communication dans un congrès

de Crombrugghe, Pauline | 2022-07-05

poster. International audience. Twisting graphene-based heterostructures results in local atomic reconstructions which have large consequences in terms of local and global electronic and optical properties [1]. At s...

On the origins of transport inefficiencies in mesoscopic networks

Archive ouverte: Article de revue

Toussaint, Sébastien | 2018-12

International audience. A counter-intuitive behavior analogous to the Braess paradox is encountered in a two-terminal mesoscopic network patterned in a two-dimensional electron system (2DES). Decreasing locally the ...

Du même sujet

Reading History of Science as a Physics and Mathematics Framework for Newto...

Archive ouverte: Communication dans un congrès

Pisano, Raffaele | 2017-04-19

International audience

On Mechanics and Thermodynamics Analogies in History of Physics-Mathematics...

Archive ouverte: Communication dans un congrès

Pisano, Raffaele | 2017-05-12

International audience

On the epistemic interplay between physics and mathematics such as a dynami...

Archive ouverte: Communication dans un congrès

Pisano, Raffaele | 2017-06-12

International audience

A CMOS Compatible Thermoelectric Device made of Crystalline Silicon Membran...

Archive ouverte: Article de revue

Bah, Thierno-Moussa | 2022-12-10

International audience. Herein, we report the use of nanostructured crystalline silicon as a thermoelectric material and its integration into thermoelectric devices. The proof-of-concept relies on the partial suppre...

Effet de l'angle de charge sur les harmoniques d'efforts magnétiques dans l...

Archive ouverte: Communication dans un congrès

Le Besnerais, Jean | 2016-06-07

International audience. Cet article étudie l'effet de l'angle de charge sur les efforts harmoniques de Maxwell (tangentiels et radiaux) et les bruits et vibrations d'origine magnétique dans deux machines synchrones ...

Further investigation of convolutional neural networks applied in computati...

Archive ouverte: Article de revue

Gong, Ruohan | 2022-04-07

International audience. Convolutional neural networks (CNN) have shown great potentials and have been proven to be an effective tool for some image-based deep learning tasks in the field of computational electromagn...

Chargement des enrichissements...