Abstract
Having served as a playground for fundamental studies on the physics of d and f electrons for almost a century, magnetic molecules are now becoming increasingly important for technological applications, such as magnetic resonance, data storage, spintronics and quantum information. All of these applications require the preservation and control of spins in time, an ability hampered by the interaction with the environment, namely with other spins, conduction electrons, molecular vibrations and electromagnetic fields. Thus, the design of a novel magnetic molecule with tailored properties is a formidable task, which does not only concern its electronic structures but also calls for a deep understanding of the interaction among all the degrees of freedom at play. This Review describes how state-of-the-art ab initio computational methods, combined with data-driven approaches to materials modelling, can be integrated into a fully multiscale strategy capable of defining design rules for magnetic molecules.
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Acknowledgements
The authors thank M. Briganti, A. Droghetti, J. Fernández-Rossier and M. Stamenova for useful discussion. A.L. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 948493). S.S. acknowledges the Irish Research Council (Advanced Laureate Award IRCLA/2019/127) for financial support.
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Glossary
- Nuclear magnetic resonance
-
Nuclear magnetic resonance is an experimental technique in which radiofrequencies are used to induce nuclear spin transitions, providing insights on the chemical structure of a compound.
- Electron paramagnetic resonance
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Electron paramagnetic resonance is an experimental technique in which microwave radiation is used to induce electron’s spin transitions and provides insights on the magnetic properties and electronic structures of the systems.
- Eigenstates
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Physical quantities, such as energy, are represented by matrices in quantum mechanics. To capture the state of a system, such matrices are diagonalized to obtain eigenvectors and eigenvalues. The latter describe a set of possible states for the systems, hence the name eigenstates.
- Perturbative methods
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Quantum-chemistry algorithms based on perturbation theory make it possible to obtain an accurate description of the electronic structure of molecules by considering electronic correlation as a correction to mean-field-value inter-electronic interactions.
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Lunghi, A., Sanvito, S. Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations. Nat Rev Chem 6, 761–781 (2022). https://doi.org/10.1038/s41570-022-00424-3
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DOI: https://doi.org/10.1038/s41570-022-00424-3
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