Upgrading Smartphone RGB Colorimetry for Rapid Determination of Hydrogen Peroxide Decomposition Kinetics

试剂 分析化学(期刊) 化学 比色法 滴定法 比色分析 过氧化氢 活化能 再现性 RGB颜色模型 分光光度法 反应速率常数 校准曲线 材料科学 溶剂 阿伦尼乌斯图 分解 化学计量学 动力学 曲线拟合 产量(工程) 吸收光谱法 滴定曲线 无机化学 光谱学 化学动力学 计算机科学
作者
Zhuodong Ou,Fuxuan Li,Weijie Yang,Faqiong Zhao,Haibo Zhang
出处
期刊:Journal of Chemical Education [American Chemical Society]
标识
DOI:10.1021/acs.jchemed.5c01468
摘要

Abstract The determination of the pseudo-first-order rate constant (k) for the catalytic decomposition of hydrogen peroxide is a fundamental experiment in general chemistry education. Traditional titration or gas-volumetric methods are laborious, require substantial reagents, and often yield inconsistent results. Inspired by the principles of intelligent chemistry (i.e., the integration of smart-device-based measurement and automated data analysis), we present an enhanced methodology that integrates the potassium titanyloxalate–H2O2 color-forming system with smartphone-based RGB blue-channel analysis. This experiment was implemented with 28 undergraduate students, who successfully determined activation energy using only a smartphone and a Python script. The color of this orange-yellow complex exhibits a broad absorption spectrum in the range of 430–470 nm (B channel). A linear calibration curve (R2 = 0.9902, 0.1–1.5 mM) was established by correlating the B value (i.e., this is the blue value in the RGB image) with the concentration of H2O2. Sequential images captured throughout the reaction process provided concentration–time profiles that were analyzed with first-order kinetics. Activation energy (Ea), calculated from the Arrhenius plot (ln k vs 1/T) at temperatures ranging from 5–45 °C, was 44.8 ± 2.4 kJ mol–1, showing excellent consistency with the value determined by UV–Vis spectrophotometry (44.8 ± 0.07 kJ mol–1). Compared to titration and gas-volumetric methods, our method eliminates specialized apparatus requirements, reduces the experimental duration to approximately 45 min, markedly decreases reagent consumption, and improves reproducibility (RSD < 5%). Translating to a sustainable and scalable learning experience, this cost-effective, digitalized procedure transforms the undergraduate kinetics laboratory into an active learning environment.
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