Raman microscopy as a defect microprobe for hydrogen bonding characterization in materials used in fusion applications
C\'edric Pardanaud (PIIM), Youn\`es Addab (PIIM), C\'eline Martin, (PIIM), Pascale Roubin (PIIM), Bernard Pegouri\'e (IRFM), Martin Oberkofler, (PIIM), Martin K\"oppen (PIIM), Timo Dittmar (IRFM), Christian Linsmeier, (PIIM)

TL;DR
This paper demonstrates how Raman microscopy can effectively detect and analyze hydrogen bonding in materials relevant to fusion reactors, providing a rapid, non-destructive characterization method for plasma-facing components.
Contribution
It introduces Raman microscopy as a novel microprobe technique for hydrogen bonding analysis in fusion materials, including graphite, beryllium, and tungsten oxide.
Findings
Raman spectroscopy can identify local structural changes related to hydrogen content.
The technique is fast, non-destructive, and suitable for nanometer-scale analysis.
It can distinguish hydrogen bonding environments in various fusion-relevant materials.
Abstract
We present the Raman microscopy ability to detect and characterize the way hydrogen is bonded with elements that will be used for ITER's plasma facing components. For this purpose we first use hydrogenated amorphous carbon samples, formed subsequently to plasma-wall interactions (hydrogen implantation, erosion, deposition...) occurring inside tokamaks, to demonstrate how this technique can be used to retrieve useful information. We pay attention in identifying which spectroscopic parameters are sensitive to the local structure (sp 3 /sp 2) and which gives information on the hydrogen content using isothermal and linear temperature ramp studies on reference samples produced by plasma enhanced chemical vapor deposition. We then focus on the possibility to use this fast, non-destructive and non-contact technique to characterize the influence of hydrogen isotope implantation in few…
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.
