Exploring machine learning methods for absolute configuration determination with vibrational circular dichroism.

The added value of supervised Machine Learning (ML) methods to determine the Absolute Configuration (AC) of compounds from their Vibrational Circular Dichroism (VCD) spectra was explored. Among all ML methods considered, Random Forest (RF) and Feedforward Neural Network (FNN) yield the best performance for identification of the AC. At its best, FNN allows near-perfect AC determination, with accuracy of prediction up to 0.

Optical second harmonic generation in a ferromagnetic liquid crystal.

A comparative experimental investigation of the dependence of second harmonic generation (SHG) on an applied external voltage between a standard nematic liquid crystalline material and an analogue ferromagnetic nematic liquid crystalline material was performed by using a fundamental optical beam at an 800 nm wavelength. For the ferromagnetic material, the dependence of SHG on an applied magnetic field was also examined. Three different polarization combinations of the fundamental and the second harmonic radiation were analysed.