The effect of the thermal reduction on the kinetics of low temperature 4He sorption and the structural characteristics of graphene oxide
A.V. Dolbin (1), M.V. Khlistuck (1), V.B. Esel'son (1), V.G. Gavrilko, (1), N.A. Vinnikov (1), R.M. Basnukaeva (1), A.I. Prokhvatilov (1), I.V., Legchenkova (1), V.V. Meleshko (1), W.K. Maser (2), A.M. Benito (2) ((1) B., Verkin Institute for Low Temperature Physics

TL;DR
This study investigates how thermal reduction affects helium sorption kinetics and structural properties of graphene oxide, revealing changes in diffusion mechanisms and activation energies with different annealing temperatures.
Contribution
It provides new insights into how thermal treatment modifies helium sorption kinetics and structural defects in graphene oxide, especially regarding diffusion mechanisms and activation energy variations.
Findings
Lower activation energy in TRGO-200 compared to GtO.
Transition from thermally activated diffusion to tunneling at low temperatures.
Structural recovery and defect generation influence activation energy dependence.
Abstract
The kinetics of the sorption and the subsequent desorption of 4He by the starting graphite oxide (GtO) and the thermally reduced graphene oxide samples (TRGO, Treduction = 200, 300, 500, 700 and 900 C) have been investigated in the temperature interval 1.5 - 20 K. The effect of the annealing temperature on the structural characteristics of the samples was examined by the X-ray diffraction (XRD) technique. On lowering the temperature from 20 K to 11-12 K, the time of 4He sorption increased for all the samples, which is typically observed under the condition of thermally activated diffusion. Below 5 K the characteristic times of 4He sorption by the GtO and TRGO-200 samples were only weakly dependent on temperature, suggesting the dominance of the tunnel mechanism. In the same region (T<5 K) the characteristic times of the TRGOs reduced at higher temperatures (300, 500, 700 and 900 C) were…
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.
