Automated solid phase extraction and electrospray chip based on programmatic pneumatic micro-valves.

Microfluidic chips coupled with electrospray ionization (ESI) mass spectrometry (MS) is an analytical platform with high detection throughputs and low sample consumptions. However, its applications in probing real samples are limited by the absence of reliable on-chip sample pretreatments, which are indispensable due to both the low contents of analytes and the poor salt tolerance of ESI MS. Herein, we propose an automated extraction and ESI chip (AEEC), consisting of a solid phase extraction (SPE) zone, seven on-chip pneumatic micro-valves, a monolithic ESI nozzle, and other components, to implement on-chip SPE prior to on-line ESI for analytes. In the SPE zone, magnetic silica beads were immobilized by magnets, and used as the SPE sorbent. Additionally, open and closed statuses of all micro-valves were simultaneously controlled by turning off and on applied pneumatic pressures, thus regulating the direction of various flows in AEEC. Further, the SPE in AEEC, consisting of sample introduction and extraction, elution introduction, and analytes elution, was automatically implemented by regulating the direction of both sample and elution flows in AEEC. After these steps, the analytes elution was on-line introduced to the monolithic ESI nozzle, at which the ESI for analytes was achieved. After optimizations, the AEEC-MS method was used to investigate two standard chemicals and ten pesticides, achieving a limit of detection and an enrichment ratio between 0.10 and 0.75 ng μL-1 and 2.1-6.2, respectively. In addition, linear calibration curves with and without the SPE beads were compared, demonstrating the effect of the automated SPE in improving reliability and sensitivity of the AEEC method. Finally, we applied AEEC to quantify a new herbicide, quinotrione, in sorghum plant as 0.176 mg kg-1 (RSD=5.70%), presenting an improved error compared with related reports. With the AEEC method, a SPE and ESI MS investigation for analytes could be automatically implemented within 300 s, effectively reducing random error and analytical time compared with manual strategies.