Data-driven design of molecular nanomagnets - Duan, Yan; Rosaleny, Lorena E.; Coutinho, Joana T.; Giménez-Santamarina, Silvia; Scheie, Allen; Baldoví, José J.; Cardona-Serra, Salvador; Gaita-Ariño, Alejandro (Nature communications, 2022)
Three decades of research in molecular nanomagnets have raised their magnetic memories from liquid helium to liquid nitrogen temperature thanks to a wise choice of the magnetic ion and coordination environment. Still, serendipity and chemical intuition played a main role. In order to establish a powerful framework for statistically driven chemical design, here we collected chemical and physical data for lanthanide-based nanomagnets, catalogued over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis. Our analysis shows that the Arrhenius energy barrier correlates unexpectedly well with the magnetic memory. Furthermore, as both Orbach and Raman processes can be affected by vibronic coupling, chemical design of the coordination scheme may be used to reduce the relaxation rates. Indeed, only bis-phthalocyaninato sandwiches and metallocenes, with rigid ligands, consistently present magnetic memory up to high temperature. Analysing magnetostructural correlations, we offer promising strategies for improvement, in particular for the preparation of pentagonal bipyramids, where even softer complexes are protected against molecular vibrations. Three decades of research in molecular nanomagnets have enabled the preparation of compounds displaying magnetic memory at liquid nitrogen temperature. Here, the authors provide an innovative framework for the design of molecular magnets based on data mining, and develop an interactive dashboard to visualize the dataset.