Quantitative calibration of the relationship between Volta potential measured by scanning Kelvin probe force microscope (SKPFM) and hydrogen concentration

The quantitative relationship between the Volta potential measured by scanning Kelvin probe force microscope (SKPFM) and hydrogen concentration values on the pure nickel surface has been calibrated. With continuous SKPFM scanning on the back of hydrogen charged side of a foil specimen, the changing Volta potential was achieved. On the other hand, the evolution of hydrogen concentration values on the SKPFM measured surface was obtained by combining the diffusion equation and electrochemical hydrogen permeation tests, which could estimate the constant hydrogen concentration on charging surface C-0 and the hydrogen diffusion coefficient inside the nickel foil D simultaneously. The results suggest that the Volta potential involving SKPFM sharply decreases with the increase of hydrogen concentration in the low hydrogen concentration range. However, the change of the Volta potential is less considerable with the increase of hydrogen concentration at a high hydrogen amount level. The relationship between the SKPFM derived Volta potential and hydrogen concentration is quantitatively described by a modified Nernst equation model. The study shows that SKPFM is a powerful tool to quantify the hydrogen distribution, but may only prevail in low hydrogen concentration range. In addition, it is reasonable to consider the Volta potential to be linearly proportional to hydrogen concentration over a wide range of potential change. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

The quantitative relationship between the Volta potential measured by SKPFM and hydrogen concentration values on the pure nickel surface has been calibrated. It was found that the Volta potential sharply decreases with the increase of hydrogen concentration in the low range, but the change becomes less considerable at high levels. The relationship is described by a modified Nernst equation model.