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Updated: Feb 5, 2026

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A novel capacitive sensor based on molecularly imprinted nanoparticles as recognition elements.

Francesco Canfarotta1, Joanna Czulak1, Antonio Guerreiro1

  • 1MIP Diagnostics Ltd., Fielding Johnson Building, University of Leicester, LE1 7RH, United Kingdom.

Biosensors & Bioelectronics
|September 3, 2018
PubMed
Summary
This summary is machine-generated.

Molecularly Imprinted Polymers (MIPs) nanoparticles offer a stable, selective alternative for biosensing. This study presents a new method for integrating nanoMIPs with capacitive sensors for real-time, label-free detection.

Keywords:
BiosensorCapacitanceMIPNanoparticleProtein sensor

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Area of Science:

  • Materials Science
  • Analytical Chemistry
  • Biotechnology

Background:

  • Molecularly Imprinted Polymers (MIPs) serve as synthetic recognition elements, replacing less stable biological receptors like enzymes and antibodies in assays and sensors.
  • Developing robust and sensitive sensor platforms is crucial for real-time molecular detection.

Purpose of the Study:

  • To develop a manufacturing-friendly protocol for integrating MIP nanoparticles (nanoMIPs) with label-free capacitive sensors.
  • To demonstrate the enhanced performance of nanoMIPs in terms of selectivity and limit of detection compared to microparticles.
  • To validate the general applicability of the biosensor platform for detecting diverse targets.

Main Methods:

  • Solid-phase synthesis was employed to produce nanoMIPs for small molecules (tetrahydrocannabinol) and proteins (trypsin).
  • NanoMIPs were deposited onto capacitive sensor surfaces.
  • Label-free capacitive measurements were performed to detect target binding, analyzing changes in capacitance (ΔC).

Main Results:

  • The nanoMIP-based capacitive sensor demonstrated improved selectivity and a one-order-of-magnitude lower limit of detection compared to MIP microparticles.
  • The increased surface-to-volume ratio and specificity of solid-phase synthesized nanoMIPs contributed to enhanced performance.
  • The sensor exhibited high selectivity, rapid response times (45 min), and straightforward data analysis for real-time monitoring.

Conclusions:

  • The developed protocol enables the straightforward integration of nanoMIPs with capacitive sensors, offering a viable alternative to traditional recognition elements.
  • The nanoMIP-based biosensor platform is suitable for label-free, real-time monitoring with broad applicability across different target molecules.
  • This approach provides a robust and scalable solution for advanced sensing applications.