摘要:
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.
摘要:
By employing a "modulated-temperature" heating program composed of a series of heat-isotherm stages, it is possible to separate the change in dimensions of an oriented material during heating into two contributions: a thermally "reversing" component which is due to linear thermal expansion and a "non-reversing" part arising from relaxation to the disordered state on heating above T.sub.g. Some preliminary results for biaxially drawn poly(ethylene terephthalate) film are presented.