Ccelerating The Phase Identification Of Multiphase Mixtures With Deep Learning

Researchers have developed a deep learning model that can identify a previously unknown quasicrystalline phase present in multiphase crystalline samples. The model was tested on a sample containing an Al-Si-Ru i-QC phase and was also tested on simulated data for decagonal and dodecagonal quasicrystals, demonstrating its potential for identifying other structures. This model has the potential to accelerate the phase identification process of multiphase samples.