Supramolecular nanostructures of coil-rod-coil molecules containing a 9,10-distyrylanthracene group in aqueous solution and their optical properties of assemblies

A series of coil-rod-coil molecules containing a 9,10-distyrylanthracene (DSA) core was successfully synthesized. The flexible parts of these molecules are composed of different polyethylene oxide chains. These molecules with aggregation-induced luminescence properties can be assembled into micelles, spheres, and sheet-like nano-assemblies in aqueous solution and have a strong ability to form charge-transfer complexes with the electron-deficient small molecules 2,4,5,7-tetranitro-9-fluorenone and 2,4,6-trinitrophenol. Interestingly, under ultraviolet light irradiation, the DSA structure undergoes photolysis and induces the disappearance of the aggregation-induced luminescence phenomena, giving these molecules application potential as a photodegradable material. In addition, these molecules are suitable organic dyes for information encryption and anti-counterfeiting applications.

Assembling photoactive materials from polycyclic aromatic hydrocarbons (PAHs): room temperature phosphorescence and excimer-emission in co-crystals with 1,4-diiodotetrafluorobenzene

Co-crystallization of PAHs with a polyhalogenated co-former afforded three novel co-crystals, which display remarkable features such as mechanochemical interconversion, photoreactivity, excimer fluorescence, and RTP phosphorescence in the solid state.

One class classification as a practical approach for accelerating π-π co-crystal discovery

The implementation of machine learning models has brought major changes in the decision-making process for materials design. One matter of concern for the data-driven approaches is the lack of negative data from unsuccessful synthetic attempts, which might generate inherently imbalanced datasets. We propose the application of the one-class classification methodology as an effective tool for tackling these limitations on the materials design problems. This is a concept of learning based only on a well-defined class without counter examples. An extensive study on the different one-class classification algorithms is performed until the most appropriate workflow is identified for guiding the discovery of emerging materials belonging to a relatively small class, that being the weakly bound polyaromatic hydrocarbon co-crystals. The two-step approach presented in this study first trains the model using all the known molecular combinations that form this class of co-crystals extracted from the Cambridge Structural Database (1722 molecular combinations), followed by scoring possible yet unknown pairs from the ZINC15 database (21 736 possible molecular combinations). Focusing on the highest-ranking pairs predicted to have higher probability of forming co-crystals, materials discovery can be accelerated by reducing the vast molecular space and directing the synthetic efforts of chemists. Further on, using interpretability techniques a more detailed understanding of the molecular properties causing co-crystallization is sought after. The applicability of the current methodology is demonstrated with the discovery of two novel co-crystals, namely pyrene-6H-benzo[c]chromen-6-one (1) and pyrene-9,10-dicyanoanthracene (2).

Exploring the semiconductor properties of a charge transfer cocrystal of 1-aminopyrene and TCNQ

The n-type semiconductor nature of a 1 : 1 mixed stack charge transfer cocrystal of 1-aminopyrene and TCNQ is explored.

Unravelling substitution effects on charge transfer characteristics in cocrystals of pyrene based donors and 3,5-dinitrobenzoic acid

Ambipolar to p-type semiconductivity switching with the change of the ⋯DADADA⋯ to ⋯ADDADD⋯ packing arrangement in charge transfer cocrystals of pyrene based donors is discussed.

Donor-acceptor interaction-driven self-assembly of amphiphilic rod-coil molecules into supramolecular nanoassemblies

Rigid-flexible amphiphilic molecules consisting of an aromatic segment based on pyrene and biphenyl units and hydrophilic polyethylene oxide chains self-assemble into lamellar, hexagonal columnar, and two-dimensional columnar nanostructures in the bulk state. In aqueous solution, these molecules self-assemble into nanofibers, spherical micelles, and multilayer nanotubes, depending on the chain or rod length of the molecules. Notably, ordered nanostructures of supramolecular polymers, such as single-layer curving fragments, nanofibers, and nanosheets, were constructed through charge-transfer interactions between the nanoobjects and an electron-acceptor molecule, 2,4,5,7-tetranitrofluorenone. These experimental results reveal that diverse supramolecular morphologies can be controlled by tuning rod-coil molecular interactions or charge-transfer interactions between the donor and acceptor molecules.