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Citation: Qi Chen, Hanyi Li, Yu Gao, Yinan Yang, Jianhao Zhou, Suning Li. Application of a Programmable Heating Control System in Organic Chemistry Experiment[J]. University Chemistry, ;2026, 41(1): 310-320. doi: 10.12461/PKU.DXHX202506016 shu

Application of a Programmable Heating Control System in Organic Chemistry Experiment

Qi Chen ¹ ,
Hanyi Li ¹ ,
Yu Gao ¹ ,
Yinan Yang ² ,
Jianhao Zhou ¹ ,
Suning Li ^1,,

1.
School of Chemistry and Chemical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;
2.
Qian Xuesen College, Nanjing University of Science and Technology, Nanjing 210094, China

Corresponding author: Suning Li, suning7758@sina.com
Received Date: 3 June 2025
Revised Date: 16 September 2025

This study designed and implemented a programmable heating control system coupled with a wireless temperature-sensing stir bar to optimize experimental procedures for Hofmann degradation reactions. The integrated system incorporates Internet of Things (IoT)-based wireless temperature monitoring, a combined heating/cooling device, and Proportional-Integral-Derivative (PID) algorithm-based precision temperature control to improve the success rate and product purity in temperature-sensitive organic chemistry experiments. The wireless temperature sensing technology overcomes the limitations of conventional thermometers and thermocouples in organic solvent environments, enabling real-time, accurate internal temperature monitoring. The dual-function heating/cooling unit eliminates the need for traditional ice baths, facilitating fully automated temperature regulation throughout the experimental process while enhancing operational efficiency and measurement accuracy. Utilizing PID control algorithms, the system dynamically adjusts heating power according to the difference between target and actual temperatures, maintaining thermal stability and preventing temperature fluctuations, thereby improving reaction success rates and product purity. This automated design significantly reduces manual operation errors while improving experimental reproducibility and safety, offering novel approaches and technical support for digital education in organic chemistry experiments.
- Automated temperature control,
- Hofmann degradation,
- Wireless temperature sensing,
- PID algorithm,
- Experimental optimization
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