Microscopy-Guided 3-D Reconstruction of Nanodendrites in Biosensors

Sue Yuan Fan, Yi Pin Huang, Sucharita Khuntia, Jen Wen Chang, Ci Ruei Liou, Bing Zhang, Li Chia Tai*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Nanodendritic structures have gained increasing popularity in electrochemical sensors. However, it is still rare to generate a 3-D model in a short period of time to understand the structure-function relationship of the sensors. Here, we report the construction of a 3-D model for nanodendritic, metallic structures frequently grown on top of bioelectronics. This is achieved by merging two sources of 2-D dendritic information, which includes top-view images from scanning electron microscopy (SEM) and side-view visualization from Monte Carlo simulations. The microscopy images provide the boundary conditions to tune the Monte Carlo simulations to construct the 3-D dendritic morphology. We validated the 3-D model by comparing the dendritic area densities predicted via this model with those computed from microscopy images. In addition, tuning the simulation parameters in the 3-D model can be used to find the optimized dendritic density, which is an essential indicator for sensitivity enhancement. The success of this model provides a means to understand the sensitivity limits of bioelectronics through dendritic growth without the need for time-consuming sensor fabrication and testing. Furthermore, our SEM-guided Monte Carlo technique provides a dendritic model with a significant resemblance to experimental images. It possesses the potential for applications in 3-D morphological investigations for future biosensor design.

Original languageEnglish
Pages (from-to)9025-9032
Number of pages8
JournalIEEE Sensors Journal
Volume23
Issue number9
DOIs
StatePublished - 1 May 2023

Keywords

  • Biosensors
  • Monte Carlo methods
  • nanodendrites
  • scanning electron microscopy (SEM)

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