fig3

From: Defect engineering and machine learning enhance n-butanol sensing of γ-Fe₂O₃

Defect engineering and machine learning enhance <i>n</i>-butanol sensing of γ-Fe<sub>2</sub>O<sub>3</sub>

Figure 3. (A) Response to 100 ppm n-butanol at different operating temperatures; (B and C) Linear fitting of response-concentration data from Supplementary Figure 6B and C; (D) Cyclic response to 100 ppm n-butanol; (E) Selectivity toward 100 ppm various VOCs; (F) 30-day stability of Fe400 and 15%-Fe400 sensors to 100 ppm n-butanol. Error bars denote the standard error of the mean (SEM) from 35 independent measurements; (G and H) Response/recovery times and response values to 100 ppm n-butanol for sensors subjected to heat treatment at different temperatures and with various H₂BDC contents; (I) Responses of Fe400 and 15%-Fe400 sensors to 100 ppm n-butanol under different relative humidities. All subfigures are original. Panels (A-I) were plotted using Origin 2024. VOC: Volatile organic compound; H₂BDC: terephthalic acid.