Retrieving information from experimental data is a very difficult task, known as inverse problem. Such problems in physical chemistry has been solved using the Hopfield Neural Network. The robustness of this method in inverting scattering data for liquids has been demonstrated. Its performance will be evaluated in this work using data for a glassy solid. The preliminarly results shows a excellent outcome for the data considered.