Model-aided hybrid metrology for surface roughness measurement fusing AFM and SEM data

In this paper, we propose a hybrid metrology approach to the measurement and characterization of the nanoroughness of freeform film surfaces. The basic idea is to combine measurement data from Atomic Force and Scanning Electron Microscopes (AFM and SEM respectively) in a synergetic manner exploiting the advantages of both methods and reducing the effects of their shortcomings. The fusion of data is realized through a model reconstruction of the measured rough surface. In particular, the hybrid approach is implemented by obtaining the height distribution function from AFM topographies (given the high accuracy in AFM height measurements) and the autocorrelation function or Fourier transform of the surface morphology from SEM images (given the high spatial resolution in SEM images). These functions are then used as input to an algorithm to generate rough surfaces in which AFM tip size effects are minimized and hence are more accurate statistical representation of the real surface. The output morphologies may be employed to estimate all roughness parameters and metrics and especially the so-called hybrid parameters (active surface area, distributions of surface derivatives and curvatures etc.) which depend on both vertical and spatial roughness aspects. The latter parameters may be critical in many applications where surface roughness is used to control wetting behaviour, light scattering, bioadhesion or wear properties. As an example, we apply the hybrid approach to the estimation of the active surface area of a sample of cyclic olefin film etched in oxygen plasma for wetting control.

[1]  K. To̸nder,et al.  Simulation of 3-D random rough surface by 2-D digital filter and fourier analysis , 1992 .

[2]  Peter Grutter,et al.  Tip artifacts of microfabricated force sensors for atomic force microscopy , 1992 .

[3]  Douglas J. Thomson,et al.  Tip artifacts in atomic force microscope imaging of thin film surfaces , 1993 .

[4]  J. Villarrubia Scanned probe microscope tip characterization without calibrated tip characterizers , 1996 .

[5]  J. Villarrubia Algorithms for Scanned Probe Microscope Image Simulation, Surface Reconstruction, and Tip Estimation , 1997, Journal of research of the National Institute of Standards and Technology.

[6]  H. Haussecker,et al.  Shape‐from‐shading and simulation of SEM images using surface slope and curvature , 2005 .

[7]  Stefano Piccarolo,et al.  Some experimental issues of AFM tip blind estimation: the effect of noise and resolution , 2006 .

[8]  Enrico Savio,et al.  Critical factors in SEM 3D stereo microscopy , 2008 .

[9]  David Qu,et al.  Wetting and Roughness , 2008 .

[10]  Ludger Koenders,et al.  Aspects of scanning force microscope probes and their effects on dimensional measurement , 2008 .

[11]  Maxence Bigerelle,et al.  Relative influence of surface topography and surface chemistry on cell response to bone implant materials. Part 1: Physico-chemical effects , 2010, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[12]  Surojit Chattopadhyay,et al.  Anti-reflecting and photonic nanostructures , 2010 .

[13]  Peter Ebersbach,et al.  A holistic metrology approach: hybrid metrology utilizing scatterometry, CD-AFM, and CD-SEM , 2011, Advanced Lithography.

[14]  Johann Foucher,et al.  Hybrid CD metrology concept compatible with high-volume manufacturing , 2011, Advanced Lithography.

[15]  C. Mack Generating random rough edges, surfaces, and volumes. , 2013, Applied optics.

[16]  Todd C. Bailey,et al.  Leveraging advanced data analytics, machine learning, and metrology models to enable critical dimension metrology solutions for advanced integrated circuit nodes , 2014 .

[17]  Alok Vaid,et al.  Hybrid metrology: from the lab into the fab , 2014 .

[18]  Angeliki Tserepi,et al.  Hierarchical micro and nano structured, hydrophilic, superhydrophobic and superoleophobic surfaces incorporated in microfluidics, microarrays and lab on chip microsystems , 2015 .