System and method for deconvoluting the effect of topography on scanning probe microscopy measurements
US7366704B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 27, 2002 |
| Grant date | Apr 29, 2008 |
| Priority date | — |
| Expiry date | Jun 19, 2025 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01Q70/04
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.