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Citation: Tianrong Zhu, Fan Yu, Yuhang Liu, Haiyi Xu, Tingting Ma, Ming Li, Yuhang Xue, Yazhen Wang, Aihua Li, Biao Xiao, Xiaolun Peng. Intelligent Visualization, Precise Iodometry: Color Recognition-based Indirect Iodometric Method for Copper Determination[J]. University Chemistry, ;2026, 41(1): 264-275. doi: 10.12461/PKU.DXHX202503096 shu

Intelligent Visualization, Precise Iodometry: Color Recognition-based Indirect Iodometric Method for Copper Determination

School of Optoelectronic Materials and Technology, Jianghan University, Wuhan 430056, China

Corresponding author: Tianrong Zhu, Fan Yu,
Received Date: 26 March 2025
Revised Date: 29 October 2025

Digital experimentation proves advantageous for chemical education due to its capabilities in convenient data acquisition, visualization, and intelligent processing. The indirect iodometric determination of copper content requires precise identification of three critical color transitions: the light yellow endpoint after adding starch indicator, the light blue transition after KSCN addition, and the final off-white titration endpoint. Through extensive experimentation, we established a comprehensive database to determine HSV (Hue-Saturation-Value) color thresholds for these key transitions and developed a supporting titration application. The digitally enhanced method demonstrated a relative average deviation of 0.11%, significantly improving measurement precision compared to visual observation while stimulating students’ interdisciplinary research interests.
- Indirect iodometric method,
- Copper content,
- HSV color recognition,
- Experiment digitization
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