A Monte Carlo electron scattering simulation tool that can create SEM images of 3D features with arbitrary geometry has been developed. This is combined with both a stochastic resist model and synthetic 3D features to probe the effect of the effect of roughness on SEM measurements. Sidewall roughness makes it difficult to precisely identify the true feature width of a line because the roughness increases the SEM signal non-proportionally to the amount of material with which it is interacting. LER generally under predicts sidewall surface roughness because the SEM has an averaging effect as the electron beam interacts with a volume of material. LER becomes a better measure of surface roughness as the correlation length of the surface roughness increases. Decreasing film thickness causes a decrease in the linewidth and increase in LER measured by SEM, especially for features 35 nm thick and below. This occurs even if the true 3D feature width and roughness is approximately constant, meaning that the apparent change in linewidth and LER is a metrology effect. Threshold based estimations of line edges are difficult because the threshold choice that best matches the true feature width changes with the feature geometry. Model based library fits of linescans do not appear to provide a solution because sidewall roughness and sidewall angle have similar effects on the linescan meaning no unique linescan likely exists.Keywords: photoresists, scanning electron microscopy, electron scattering, sidewall roughness, line edge roughness, film thickness effects on LER, sidewall angle, stochastic photoresist model
INTRODUCTIONScanning electron microscopes (SEMs) have long been and will likely remain the metrology tool of choice due to their ease of use, high resolution, and ability to easily image at a range of length scales. Despite often being treated as such, the image produced by an SEM is not identical to an optical image. This is because the SEM works by shooting a beam of electrons into a sample and then measuring the number of lower energy secondary electrons emitted by the sample for that incident location. This electron-material interaction means that there are certain biases or effects associated with the measurement that must be accounted for to correctly interpret the SEM image. One commonly known effect is the fact that the SEM signal is more sensitive to topography; this means that the signal is higher at the edges of features than in the middle. This fact is used to measure the width of features by identifying the edges where the signal is highest. Like many things in the semiconductor industry, SEM metrology of patterned features has become more difficult as the features sizes have shrank. The current length scales of features can potentially cause a whole new series of metrology effects that must be accounted for to correctly interpret the SEM images.One of the major issues is that the roughness length scale of current features is on the order of the feature size itself. This means there can be significant errors...