Deconvolution Algorithm
Mathematical modeling deconvolves physical depth profiles from sputter-induced distortion parameters in surface and thin-film metrology. Surface profiling tools do not measure pristine step-function interfaces because instrumental and physical artifacts blur the true chemical boundary. The mixing roughness information depth model uses three physical parameters to reconstruct the unaltered elemental distribution from experimental data.
Sputter profiling of electronic contact finishes and thin barrier films relies on this algorithm to extract real layer thicknesses. The model loses validity if sample surfaces undergo non-uniform crater development or extreme chemical segregation.
Resolution Recovery
Depth profiles distorted by atomic mixing, surface roughness, and escape depth limits regain sharp interface boundaries through mathematical deconvolution. The first model parameter accounts for collision cascade mixing that shoves atoms past the nominal interface. The second parameter models surface roughness development as the sputter crater erodes.
The third parameter represents the escape depth of analyzed secondary ions or electrons. Quantifying these three terms allows software to deconvolve blurred experimental profiles into accurate step profiles. Engineers profiling thin gold and nickel layers on circuit pads use this model to verify true diffusion barrier effectiveness without misinterpreting sputter artifacts as metal migration.
Profile Reconstruction
Analytical software fits the theoretical response function to raw secondary ion mass spectrometry curves to calculate true physical layer thicknesses. Calibrated reference multilayer samples establish the mixing and roughness coefficients for specific ion beam energies. Transmission electron cross-sections validate the reconstructed interface positions against physical microstructure boundaries.
Applying this mathematical deconvolution confirms that immersion gold barriers maintain adequate integrity over nickel underlayers.
