ABSTRACT

In this paper, an electrochemical sensor array utilizing metal materials was designed, and its applications in sugar content analysis from mixtures were conducted. The system adopts the conventional three-electrode system. Cyclic Voltammetry (CV) and Amperometric i-t Curve (i-t) were utilized as testing methods. The curve of the relationship between current and time could be obtained by i-t scanning. The relationship between the sugar concentration and the current density of the sensor was developed. The data was analyzed using multiple linear regression (MLR). The sugar mixtures were automatically measured by using this instrument. CV and i-t methods were utilized to carry out the experiments. Different scan rates CV results showed that it was a typical diffusion controlled electrochemical process. Different sugars CV results showed that different electrodes for CV experiments with different sugars produced different anode peak potential and current. Control experiments showed that neither Na₂CO₃ nor NaCl had any effect on the experimental results. The developed system has good stability and repeatability. I-t fitting results indicated that there was a good linear relationship between system responses and sugar concentrations. The linear range was between 0.14 mM and 4.76 mM. A python-based MLR model was developed for sugar content determination. Results were obtained by solving the system of equations, indicating that this method presented content determination abilities for sugar mixtures. The method proposed in this paper had the advantages of easy operation, low cost, rapid analysis, and low detection limit. It provided a new idea for sugar quantitative determination in solution.

摘要

本文设计了一种利用金属材料的电化学传感器阵列，并对其在混合物糖含量分析中的应用进行了研究。该系统采用常规的三电极系统。循环伏安法 (CV) 和电流法 it 曲线 (it) 被用作测试方法。通过扫描可以得到电流与时间的关系曲线。开发了糖浓度与传感器电流密度之间的关系。使用多元线性回归（MLR）分析数据。使用该仪器自动测量糖混合物。利用CV和it方法进行实验。不同扫描速率的 CV 结果表明这是一个典型的扩散控制电化学过程。不同糖类 CV 结果表明，使用不同糖类进行 CV 实验的不同电极会产生不同的阳极峰值电位和电流。对照实验表明 Na₂ CO ₃和NaCl对实验结果没有任何影响。所开发的系统具有良好的稳定性和重复性。拟合结果表明，系统响应与糖浓度之间存在良好的线性关系。线性范围介于 0.14 mM 和 4.76 mM 之间。开发了基于 Python 的 MLR 模型用于糖含量测定。通过求解方程组得到结果，表明该方法具有对糖混合物的含量测定能力。本文提出的方法具有操作简便、成本低、分析速度快、检出限低等优点。为溶液中糖的定量测定提供了新思路。