Hydrogen charging and desorption from microstructural viewpoint: A method for deconvoluting hydrogen desorption spectra and unveiling the hydrogen-microstructure interaction

Cheng, Jiahao; Zhong, Weicheng; Mayeur, Jason; Yamamoto, Yukinori; Thapliyal, Saket

doi:10.1016/j.commatsci.2025.114132

Hydrogen charging and desorption from microstructural viewpoint: A method for deconvoluting hydrogen desorption spectra and unveiling the hydrogen-microstructure interaction

Journal Article · Mon Jul 21 00:00:00 EDT 2025 · Computational Materials Science

DOI:https://doi.org/10.1016/j.commatsci.2025.114132· OSTI ID:3002790

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Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Understanding the interaction of hydrogen with microstructural features in metallic materials is crucial for designing hydrogen-resistant alloys. Although thermal desorption spectroscopy (TDS) is widely used for investigating the hydrogen binding behavior of various microstructural features, its application to face-centered cubic (fcc) metals and alloys that exhibit low hydrogen diffusivity is limited due to the lumped TDS desorption signals. This paper shows that, by coupling a Sofronis–McMeeking type hydrogen transport model with a microstructure-informed finite-element model, TDS data can be deconvoluted to reveal the underlying adsorption–diffusion–desorption processes, hydrogen diffusivity, and trap-binding energies. In conclusion, the austenitic steel SS316L in solution-annealed condition is used as a demonstration material, and we focused on investigating the interaction of deuterium (hydrogen isotope) with grain boundaries, which is difficult to investigate from experiments alone but critical for design of alloys for hydrogen infrastructure.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 3002790

Journal Information:: Computational Materials Science, Journal Name: Computational Materials Science Vol. 258; ISSN 0927-0256

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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