A machine vision tool for multi-color H₂O₂ sensing by MoOx nanoparticles with oxygen vacancies

Improving the ease of operation and portability of hydrogen peroxide (H₂O₂) detection in daily production and life holds significant application value. However, it remains a challenge to achieve rapid colorimetric detection of H₂O₂ and color change quantification. In this study, we achieved rapid and visual detection of H₂O₂ by MoOx (2 ≤ x ≤ 3) nanoparticles with rich oxygen vacancies using machine vision. As the concentration of H₂O₂ increases, the detection system exhibited a visible multi-color change from blue to green and then yellow and the absorption peak near 680 nm measured by the UV-visible spectrophotometer gradually decreased. With excellent sensitivity, a wide linear range of 0.1-600 μmol/L, concentrations as low as 0.1 μmol/L can be detected with good selectivity towards H₂O₂. The sensing mechanism of detecting H₂O₂ by the change of oxygen vacancies in MoOx was revealed through characterization methods such as XPS, EPR, and DFT. In addition, the Hue, Saturation, Value (HSV) visual analysis system based on MoOx was constructed to assist in the rapid, portable, and sensitive monitoring of H₂O₂ in practical application scenarios. This work offers an easy-to operate, low cost, and convenience for achieving rapid colorimetric determination of H₂O₂ and has broad application prospects in daily life and industrial production.