4.7 Article

3D printing for electroanalysis: From multiuse electrochemical cells to sensors

期刊

ANALYTICA CHIMICA ACTA
卷 1033, 期 -, 页码 49-57

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2018.06.021

关键词

3D-printer; Wall-jet cell; Gold CDtrode; Screen-printed electrode; Flow analysis; Graphene

资金

  1. CNPq [478081/2010-3, 305227/2010-6, 307271/2017-0]
  2. FAPEMIG [01856-10, 01537-14, 02118-15]
  3. CAPES [23038.007073/2014-12]
  4. INCTBio [CNPq 465389/2014-7]

向作者/读者索取更多资源

This work presents potential applications of low-cost fused deposition modeling 3D-printers to fabricate multiuse 3D-printed electrochemical cells for flow or batch measurements as well as the 3D-printing of electrochemical sensing platforms. Electrochemical cells and sensors were printed with acrylonitrile butadiene styrene (ABS) and conductive graphene-doped polylactic acid (G-PLA) filaments, respectively. The overall printing operation time and estimated cost per cell were 6 h and $ 6.00, respectively, while the sensors were printed within minutes (16 sensor strips of 1 x 2 cm in 10 min at a cost of $ 1.00 each sensor). The cell performance is demonstrated for the amperometric detection of tert-butylhydroquinone, dipyrone, dopamine and diclofenac by flow-injection analysis (FIA) and batch-injection analysis (BIA) using different working electrodes, including the proposed 3D-printed sensor, which presented comparable electroanalytical performance with other carbon-based electrodes (LOD of 0.1 mu mol L-1 for dopamine). Raman spectroscopy and scanning electron microscopy of the 3D-printed sensor indicated the presence of graphene nanoribbons within the polymeric matrix. Electrochemical impedance spectroscopy and heterogeneous electron transfer constants (k(0)) for the redox probe Ru(NH3)(6)(+3) revealed that a glassy-carbon electrode presented faster electron transfer rates than the 3D-printed sensor; however, the latter presented lower LOD values for dopamine and catechol probably due to oxygenated functional groups at the G-PLA surface. (C) 2018 Elsevier B.V. All rights reserved.

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