This work investigates the structural and nonlinear optical properties of a D-A type 1-[4-({(E)-[4-(methylsulfanyl)phenyl]methylidene}amino)phenyl]ethanone, MMP in which charge transfer occurs from -SCH3 donor to -COCH3 acceptor group through methylidene backbone; and some of its modeled analogues using quantum chemical calculations with pure BLYP and hybrid B3LYP correlation with high basis se...

Graph neural networks (GNNs) are emerging in chemical engineering for the end-to-end learning of physicochemical properties based on molecular graphs. A key element GNNs is pooling function which combines atom feature vectors into fingerprints. Most previous works use a standard to predict variety properties. However, unsuitable functions can lead unphysical that poorly generalize. We compare a...