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A genetic algorithm-based method for the mechanical characterization of biosamples using a MEMS microgripper:

M Verotti1, P Di Giamberardino2, N P Belfiore3

  • 1Department of Mechanical, Energy, Management and Transportation Engineering, University of Genoa, 16145, Genoa, Italy.

Journal of the Mechanical Behavior of Biomedical Materials
|April 29, 2019
PubMed
Summary

This study introduces a microelectromechanical systems (MEMS) microgripper for biosample viscoelastic characterization. A genetic algorithm optimizes parameters for Maxwell and Maxwell-Wiechert models, enabling precise material property analysis.

Keywords:
Biosamples analysisGenetic algorithmsMEMS microgripperMicromanipulationParameters estimationViscoelastic characterization

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Area of Science:

  • Biomaterials Science
  • Mechanical Engineering
  • Microtechnology

Background:

  • Viscoelastic characterization is crucial for understanding biosample behavior.
  • Microelectromechanical systems (MEMS) offer advanced tools for precise measurements.
  • Existing methods may lack the resolution for microscale biosamples.

Purpose of the Study:

  • To develop and validate a MEMS microgripper for biosample viscoelasticity.
  • To model the coupled nonlinear dynamics of the micro-system and biosample.
  • To identify viscoelastic parameters using established material models and optimization algorithms.

Main Methods:

  • Utilizing a MEMS technology-based microgripper for sample manipulation.
  • Developing a mechanical model for the microsystem's coupled nonlinear dynamics.
  • Applying the Maxwell liquid drop and generalized Maxwell-Wiechert models for biosamples.
  • Implementing a genetic algorithm for parameter identification.

Main Results:

  • Successful characterization of biosample viscoelastic properties.
  • Validation of the developed mechanical model for the micro-system.
  • Accurate identification of viscoelastic parameters through genetic algorithm optimization.

Conclusions:

  • The MEMS microgripper provides an effective platform for biosample viscoelastic analysis.
  • The integrated modeling and genetic algorithm approach enables precise parameter extraction.
  • This technique advances the study of microscale material properties in biological samples.