Search

Chitosan is a functional polymer with diverse applications in biomedicine, agriculture, water treatment, and beyond. Via derivatization of pristine chitosan, its functionality can be tailored to desired applications, e.g. immobilization of biomolecules. Here, we performed molecular dynamics simulations of three aminated chitosan polymers, where one, two, and three long-distanced side chains have been incorporated. These polymers have been previously synthesized and their properties were investigated experimentally, however, the observed dependencies could not be fully explained on the molecular level. Here, we develop a computational protocol for the simulation of functionalized chitosan polymers and perform advanced analysis of their conformational states, intramolecular interactions, and water binding. We demonstrate that intra- and intermolecular forces, especially hydrogen bonds induced by polymer side chain modifications, modulate dihedral angle conformational states of the polymer backbone and interactions with water. We explain the role of the chemical composition of the functionalized chitosans in their tendency to collapse and reveal the key role of the protonation of the amino group near the polymer backbone on the reduction of polymer collapse. We demonstrate that specific binding of water molecules, especially the intermediate water, is more pronounced in the polymer exhibiting such an amino group., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

While materials based on organic molecules usually have either superior optoelectronic or superior chiral properties, the combination of both is scarce. Here, a crystalline chiroptical film based on porphyrin with homochiral side groups is presented. While the dissolved molecule has a planar, thus, achiral porphyrin core, upon assembly in a metal-organic framework (MOF) film, the porphyrin core is twisted and chiral. The close packing and the crystalline order of the porphyrin cores in the MOF film also results in excellent optoelectronic properties. By exciting the Soret band of porphyrin, efficient photoconduction with a high On-Off-ratio is realized. More important, handedness-dependent circularly-polarized-light photoconduction with a dissymmetry factor g of 4.3×10 -4 is obtained. We foresee the combination of such assembly-induced chirality with the rich porphyrin chemistry will enable a plethora of organic materials with exceptional chiral and optoelectronic properties., (© 2022 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials. Graph neural networks (GNNs) are one of the fastest growing classes of machine learning models. They are of particular relevance for chemistry and materials science, as they directly work on a graph or structural representation of molecules and materials and therefore have full access to all relevant information required to characterize materials. In this Review, we provide an overview of the basic principles of GNNs, widely used datasets, and state-of-the-art architectures, followed by a discussion of a wide range of recent applications of GNNs in chemistry and materials science, and concluding with a road-map for the further development and application of GNNs., Competing Interests: Competing interestsThe authors declare no competing interest., (© The Author(s) 2022.)