Accession Number:



SERS Nanosensors for in vivo Glucose Sensing

Descriptive Note:

Technical Report,01 Sep 2018,21 Aug 2019

Corporate Author:

Northwestern University Chicago United States

Report Date:


Pagination or Media Count:



The goal of this program is to develop small and sensitive nanosensors for the continuous glucose monitoring in living tissue without the need for drawing blood. A major advantage of the transdermal sensors we are developing is to directly detect glucose itself not the byproducts of its transformation. The technique we use surface-enhanced Raman spectroscopy SERS is based on light and informs on the presence of glucose on or near metallic nanosensors. In Year 1, we have worked on the development of i sensitive nanosensors, ii selective capture layers that can be immobilized onto metal surfaces, and iii the integration of both. We have successfully developed a novel SERS nanoplatform that integrates gold nanorods with biocompatible hydrogels of variable stiffness. In Year 2, we have implemented the glucose-capture ligand on the gold nanorod surface that are already integrated with polymeric microneedle patches. The stability of the nanorods in buffer conditions as well as organic solvents was evaluated. Additionally, SERS activity and device performance after functionalizing the surface with a pH-sensitive Raman reporter molecule was investigated by measuring reversible pH change from solution and in a skin phantom. In Year 3, the SERS performance of the plasmonic microneedle was evaluated ex vivo human skin. In addition to this platform, we successfully fabricated an electrochemical microneedle sensor with SERS activity that allows us to apply potential and detect analytes using SERS without the need of a capture ligand. We have demonstrated the sensing capability of this sensor platform by detecting model molecules benzenethiol, caffeine, and theobromine. In addition, we developed an electrochemical strategy to reversibly localize analytes within the SERS detecting zone and enable separation of SERS signals from different analytes through multivariate analysis.

Subject Categories:

  • Medicine and Medical Research
  • Biochemistry
  • Medical Facilities, Equipment and Supplies

Distribution Statement: