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Digital Twins for 3D Confocal Microscopy: Near-Field, Far-Field, and Comparison with Experiments.

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Summary

Researchers developed digital twins using rigorous models to predict confocal microscopy sensor responses for complex surfaces. This approach enhances accuracy and reduces simulation time for advanced microscopy applications.

Keywords:
BEMFEMFMMconfocal microscopydigital twinfar-field calculationmetrologymicroscopynear-field calculationnumerical simulation

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Area of Science:

  • Optics and Photonics
  • Computational Physics
  • Microscopy Techniques

Background:

  • Confocal microscopy faces limitations with complex surface geometries.
  • Accurate prediction of sensor responses is crucial for advancing microscopy.
  • Existing methods can be time-intensive for detailed surface analysis.

Purpose of the Study:

  • To overcome current limitations in confocal microscopy.
  • To predict sensor responses for complex surface geometries.
  • To develop a novel, efficient method for confocal microscopy simulations.

Main Methods:

  • Digital twins were constructed using three rigorous models: finite element method (FEM), Fourier modal method (FMM), and boundary element method (BEM).
  • Light-surface interactions were modeled, and Fourier optics calculated sensor signals.
  • A 3D illumination model was applied to periodic and aperiodic structures, with scanning achieved via focal-point shifts.

Main Results:

  • FEM, FMM, and BEM models produced identical, highly accurate results for rectangular gratings, validated by experimental data.
  • Simulations provided insights into instrument transfer functions, tilted gratings, and edge rounding effects.
  • The novel FMM-based confocal microscopy method was described in detail.

Conclusions:

  • The developed digital twin approach offers a promising method for correcting systematic errors in confocal microscopy.
  • This research enhances the predictive capabilities of confocal microscopy for complex surfaces.
  • The findings pave the way for more accurate and efficient microscopy analyses.