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Citation: Yuejiao Wang, Quanxing Mao, Junshuo Cui, Xiaogeng Feng, Xiaohong Chang, Zhenning Lou, Ying Xiong. 颜色识别式人工智能融入混合碱滴定实验的应用[J]. University Chemistry, ;2026, 41(1): 107-113. doi: 10.12461/PKU.DXHX202506020 shu

颜色识别式人工智能融入混合碱滴定实验的应用

College of Chemistry, Liaoning University, Shenyang 110036, China

Corresponding author: Ying Xiong, xiongying@lnu.edu.cn
Received Date: 3 June 2025
Revised Date: 27 August 2025

Conventional mixed alkali titration analysis suffers from subjective endpoint determination at the first equivalence point and significant variability in triplicate measurements. This study employs Color-Discriminable Artificial Intelligence (CDAI) for endpoint detection, combining precise hardware control with intelligent algorithms to establish an objective, quantifiable dynamic color discrimination model for phenolphthalein and methyl orange indicators. The developed system effectively resolves endpoint determination challenges and improves measurement reproducibility. This work demonstrates an innovative intelligent titration methodology, offering a scalable solution for the digital transformation of chemical laboratory education.
- Mixed Alkali,
- Titration,
- Python,
- Artificial Intelligence,
- Color-discrimination
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