System and method for deconvoluting the effect of topography on scanning probe microscopy measurements
AssigneeWaters Investments Limited
InventorsMichael Reading, Duncan M. Price
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AssigneeWaters Investments Limited
InventorsMichael Reading, Duncan M. Price
Estimating the term…
A method for using a neural network to deconvolute the effects due to surface topography from the effects due to the other physical property being measured in a scanning probe microscopy (SPM) or atomic force microscopy (AFM) image. In the case of a thermal SPM, the SPM probe is scanned across the surface of a sample having known uniform thermal properties, measuring both the surface topography and thermal properties of the sample. The data thus collected forms a training data set. Several training data sets can be collected, preferably on samples having different surface topographies. A neural network is applied to the training data sets, such that the neural network learns how to deconvolute the effects dues to surface topography from the effects dues to the variations in thermal properties of a sample.
A method for deconvoluting scanning probe microscopy images comprising:
A method for creating an image reflecting a physical property of a surface of a sample from data obtained using a physical property scanning probe microscope, comprising:
An apparatus for obtaining images reflecting a physical property of a surface of a sample comprising:
A thermal scanning probe microscope comprising:
A method for using a neural network to deconvolute the effect of topography from a thermal conductivity measurement made by a thermal scanning probe microscope comprising the steps of:
A method for deconvoluting the effects of topography from a thermal conductivity measurement made by a thermal scanning probe microscope, comprising the steps of:
A system for deconvoluting the effects of topography from a thermal conductivity measurement, comprising the steps of:
Dependencies are inferred from the claim text.