How normalisation factors influence the interpretations of 3D-printed sensors for electroanalysis

Aya Abdalla, Fernando Perez, Ana Tendero Canadas, Santanu Ray, Bhavik Patel

Research output: Contribution to journalArticlepeer-review


The ability to produce electrodes through 3D-printing techniques for use in sensing applications has significant potential. This is mainly due to the mass production of electrodes at any desired geometry. However, comparing different 3D-printed carbon electrodes for electroanalytical performance can be challenging due to the significant variation in each conductive printed material. This study investigates different normalisations that could be applied to compare between different 3D-printed electrodes. We compared 3D-printed carbon black and graphene electrodes for the monitoring of three important biological analytes (dopamine, ascorbic acid and hydrogen peroxide). These 3D printed electrodes have different conductive loads and surface profiles, and therefore we utilised eight different approaches for normalising the current response. There was no perfect normalisation technique and therefore using a combination of approaches to survey the best performing electrode would be a better approach. This study showcases the different possible normalisation methods and highlights the impact these can have on the interpretation of electrodes for electroanalytical measurement.
Original languageEnglish
Article number114937
Number of pages8
JournalJournal of Electroanalytical Chemistry
Publication statusPublished - 18 Dec 2020


  • 3D-printing
  • Ascorbic acid
  • Carbon black
  • Dopamine
  • Graphene
  • Hydrogen peroxide
  • Normalisation


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