During the last few years,various flow-based separation/preconcentration methodologies have gained pertinent novel advances and exhibited powerful capability in the field of sample pretreatment and their hyphenation with detection by atomic spectrometry.The present mini-review presents and discusses the progress of flow-based sample processing approaches commonly used for the assay of trace elemental species with detection by atomic spectrometry,including preliminary sample pretreatment,solid phase extraction(including solid phase microextraction),liquid-liquid extraction,vapor generation and dialysis techniques.Special emphasis has been paid on the novel applications and analytical procedures hyphenated with atomic spectrometry.The future perspectives of flow-based sample pretreatment protocols in the determination of trace elements and their speciation are also discussed.
A novel fluid micromixer based on pneumatic perturbation and passive structures was developed. This micromixer facilitates integration and is applicable to fluid mixing over a wide range of flow rates. The microfluidic mixing device consists of an S-shaped structure with two mixing chambers and two barriers, and two pneumatic chambers designed over the S-shaped channel. The performance of the micromixer for fluids with wide variation of flow rates was significantly improved owing to the integration of the pneumatic mixing components with the passive mixing structures. The mixing mechanism of the passive mixing structures was explored by numerical simulation, and the influencing factors on the mixing efficiency were investigated. The results showed that when using a gas pressure of 0.26 MPa and a 100 pm-thick polydimethylsiloxane （PDMS） pneumatic diaphragm, the mixing of fluids with flow rates ranging from 1 to 650 ~tL/min was achieved with a pumping frequency of 50 Hz. Fast synthesis of CdS quantum dots was realized using this device. Smaller particles were obtained, and the size distribu- tion was greatly improved compared with those obtained using conventional methods.
WANG XinMA XiuFengAN LanLanKONG XiangWeiXU ZhangRunWANG JianHua
