Halogen-bonded architectures of multivalent calix[4]arenes

A small family of novel halogen-bonded crystalline supramolecular architectures of calixarenes was obtained by the co-crystallization of cone (1) and 1,3-alternate tetrakis(3-iodopropargyloxy)calix[4]arene (4) as tetradentate halogen donors with different multidentate acceptors. Particularly interesting is the interpenetrated diamondoid network of 4 with DABCO, which represents the first example of a 2D network of calixarene macrocycles where halogen bonding is the key interaction for self-organization

Study of Cathode Materials for Na-Ion Batteries: Comparison Between Machine Learning Predictions and Density Functional Theory Calculations

Energy storage technologies have experienced significant advancements in recent decades, driven by the growing demand for efficient and sustainable energy solutions. The limitations associated with lithium’s supply chain, cost, and safety concerns have prompted the exploration of alternative battery chemistries. For this reason, research to replace widespread lithium batteries with sodium-ion batteries has received more and more attention. In the present work, we report cutting-edge research, where we explored a wide range of compositions of cathode materials for Na-ion batteries by first-principles calculations using workflow chains developed within the AiiDA framework. We trained crystal graph convolutional neural networks and geometric crystal graph neural networks, and we demonstrate the ability of the machine learning algorithms to predict the formation energy of the candidate materials as calculated by the density functional theory. This materials discovery approach is disruptive and significantly faster than traditional physics-based computational methods