EUV phase defect characterization based oncomplex amplitudes of the aerial images

The profile deformation of a phase defect in an extreme ultraviolet (EUV) mask blank is the key factor to simulate its optical effects accurately and to compensate for it precisely. This paper provides a new, to the best of our knowledge, profile characterization method based on complex amplitudes of the aerial images for phase defects in EUV mask blanks. Fourier ptychography is adopted to retrieve the complex amplitudes of the aerial images and improve the lateral resolution. Both amplitude and phase impacted by the defect are taken into consideration to reconstruct the defect profile parameters (the height and the full width at half maxima of the defect’s top and bottom profiles). A conformal convolutional neural network model is constructed to map the amplitudes and phases of aerial images to the defect profile parameters. The Gaussian-shaped defect models with the mapped profile parameters can be used to simulate the amplitude and phase properties of the defects when compensating for them. The proposed method is verified to reconstruct the defect profile parameters of both bump defects and pit defects accurately. The involvement of both the amplitude and phase information makes the reconstructed defect profile parameters more appropriate to simulate the optical effects of the defects.