Calibration of Scanning Electron Microscope with Improved Model of the Silicon Relief Measure

Accuracy of measurements with scanning electron microscope (SEM) depends on the environment conditions, noises in nanometer-ranges (caused by non-ideal surface of measures), non-ideal SEM design, influence of external factors (vibration, acoustic noise, magnetic fields, etc.). To reduce the influence of these variables, the calibration procedure, with the use of silicon measures to reproduce dimensions is performed preferably. The model of measure real image (which is used for calibration) can be formalized as the convolution of the level of secondary electron emission and the distribution of electrons in the crossover of the electron probe. Based on the developed model, the general approach to SEM calibration is formulated and proved. The step by step removal of non-parametric and parametric uncertainty of scale factor and electron probe equivalent diameter is proposed. As the first step, the approximation of individual cuts on the measured object image, which correspond to the same cuts of measure relief with further averaging and estimating the metrological parameters and their error distributions, is performed. In the second step (of optimal estimation), the vector containing metrological characteristics using Bayesian criterion and the theory of optimal estimations is find. Proposed approach can significantly increase SEM accuracy and performance.