Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals

Abstract

An investigation of the phase sequence isotropic-fluid smectic-hexatic smectic-soft crystal–crystalline reveals the potential and limitations of convolutional neural networks applied to the classification of achiral orthogonal liquid crystal phases.