A facile online multi-gear capacitively coupled contactless conductivity detector for an automatic and wide range monitoring of high salt in HPLC
Literature Information
Weiwen Liu, Ziqi Liang, Yuanyu Wang, Jun Cao, Qiang Zhang, Xiaoping Liu, Yuxing Wang
Sensing the electrolyte solution or aqueous–organic mixture has attracted much interest in chemical separation, pharmaceutical engineering, bioprocess, and biochemical experiments. However, reports on online contactless sensor with automatic and wide range sensing of high content electrolyte have been rarely presented. Herein, a facile model and theory of online multi-gear capacitively coupled contactless conductivity detection (M-C4D) sensor was proposed using one excitation electrode and multiple detection electrodes. Further, the relevant digital computation based on the M-C4D theory was developed for parameter optimization: the electrode gap of 5–150 mm, inner radius of 0.25–0.75 mm, electrode length of 10–60 mm, and frequency of 40–250 kHz using MATLAB. To demonstrate the model, theory, and digital computation, liquid chromatography (LC) was chosen as the model of bioprocess, and the sensor was designed and used as an online sensing device for the automatic monitoring of high salt elution in LC. The experiments showed that (i) the detection results were in agreement with the digital data, validating the digital computation, theory, and model of M-C4D and (ii) the monitoring data of M-C4D were in agreement with those via the traditional meter, further validating the model and theory. Finally, the developed sensor was applied to the automated detection of high salt gradient in LC. In contrast to the currently used meters and C4D, the developed M-C4D sensor had the following merits: (i) facile and automatic online detection avoiding cumbersome manual switching of detector heads, (ii) fair linear range of 0.015–20 mS cm−1 (equivalently 0.1–159 mM KCl) that does not fit the range of traditional C4D, and (iii) fair accuracy of less than 1.50% relative error. All these results indicate that the developed model, theory, and sensor have potential for the process monitoring of high content electrolytes transfer in biochemical engineering and clinic pre-warning.
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