Neural network application to the inverse scattering problem in high-resolution X-ray diffraction

The complicated inverse scattering problem of reconstructing depth-dependen t lattice parameters from high-resolution X-ray diffraction spectra is anal ysed by using neural networks. Attention is paid to the practically importa nt case of structural modifications in the near-surface layers of ion-impla nted single crystals. The feasibility of a neural network algorithm is asse ssed on the basis of the performance statistics on a large number of simula ted examples. The performance of the method on experimental data is tested using high-resolution X-ray diffraction spectra taken from He-implanted lit hium niobate crystals.