journal article·2026-03Open access

Stability of highly hydrogenated monolayer graphene in ultra-high vacuum and in air

Alice Apponi, Orlando Castellano, Daniele Paoloni, Domenica Convertino, Neeraj Mishra, Camilla Coletti, Andrea Casale, Luca Cecchini, Alfredo G. Cocco, Benedetta Corcione, Nicola D’Ambrosio, Angelo Esposito, Alfredo Ferella, Marcello Messina, Francesco Pandolfi, Francesca Pofi, Ilaria Rago, Nicola Rossi, Sammar Tayyab, Ravi Prakash Yadav, Federico Virzi, Carlo Mariani, Gianluca Cavoto, Alessandro Ruocco

Abstract

The stability of hydrogenated monolayer graphene was investigated via X-ray photoemission spectroscopy (XPS) for two different environmental conditions: ultra-high vacuum (UHV) and ambient pressure. The study is carried out by measuring the C 1s line shape evolution for two hydrogenated samples one kept in the UHV chamber and the other progressively exposed to air. In particular, the $sp^3$ relative intensity in the C 1s core-level spectrum, represented by the area ratio $\frac{sp^3}{sp^2+sp^3}$, was used as a marker for the hydrogenation-level. After four months in UHV, it resulted almost unchanged within the experimental uncertainty. Thus, a long-term stability of hydrogenated monolayer graphene was found, that indicates this material as a good candidate for hydrogen (or tritium) storage as long as it is kept in vacuum. On the other hand, the C 1s spectrum of the sample exposed to air shows a significant oxidation. A rapid growth up to saturation of the carbon oxides was observed with a time constant $τ$ = 2.8 $\pm$ 1.2 hours. Finally, the re-exposure of the oxidised sample to atomic hydrogen was found to be an effective method for the recovery of hydrogenated graphene. The CH stretching mode was measured via electron energy loss spectroscopy as direct footprint of hydrogenated graphene recovery.
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Research context

OpenAlex topics: Graphene research and applications · Graphite, nuclear technology, radiation studies · Fiber-reinforced polymer composites

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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