Artificial intelligence design of molecular nano-magnets and molecular qubits

Project Information

AI-DEMON

Grant agreement ID: 948493

DOI 10.3030/948493

EC signature date 15 September 2020

Start date 1 January 2021

End date 31 December 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost € 1 499 786,00

EU contribution € 1 499 786,00

Coordinated by

THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD, OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Ireland

Publications

Peer reviewed articles (8)

Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations

Author(s): Alessandro Lunghi; Stefano Sanvito
Published in: Nature Reviews Chemistry, 2022, Page(s) 761–781, ISSN 2397-3358
Publisher: Springer Nature
DOI: 10.1038/s41570-022-00424-3

The critical role of ultra-low-energy vibrations in the relaxation dynamics of molecular qubits

Author(s): E. Garlatti, A. Albino, S. Chicco, V. H. A. Nguyen, F. Santanni, L. Paolasini, C. Mazzoli, R. Caciuffo, F. Totti, P. Santini, R. Sessoli, A. Lunghi and S. Carretta
Published in: Nature Communications, 2023, Page(s) 1653, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s41467-023-36852-y

A Complete Ab Initio View of Orbach and Raman Spin-Lattice Relaxation in a Dysprosium Coordination Compound.

Author(s): Matteo Briganti; Fabio Santanni; Lorenzo Tesi; Federico Totti; Roberta Sessoli; Alessandro Lunghi
Published in: Journal of the American Chemical Society, Issue 1, 2021, ISSN 1520-5126
Publisher: American Chemical Society
DOI: 10.48550/arxiv.2105.06953

Unraveling the Contributions to Spin–Lattice Relaxation in Kramers Single-Molecule Magnets

Author(s): Sourav Mondal; Alessandro Lunghi
Published in: The Journal of the American Chemical Society, Issue 1, 2022, Page(s) 22965-22975, ISSN 1520-5126
Publisher: American Chemical Society
DOI: 10.1021/jacs.2c08876

Predicting tensorial molecular properties with equivariant machine-learning models

Author(s): Vu Ha Anh Nguyen; Alessandro Lunghi
Published in: Physical Review B, Issue 1, 2022, ISSN 2469-9969
Publisher: American Physical Society
DOI: 10.48550/arxiv.2202.01449

Efficient Generation of Stable Linear Machine-Learning Force Fields with Uncertainty-Aware Active Learning

Author(s): Briganti, Valerio; Lunghi, Alessandro
Published in: Machine Learning: Science and Technology, Issue 1, 2023, Page(s) 035005, ISSN 2632-2153
Publisher: Institute of Physics
DOI: 10.1088/2632-2153/ace418

Spin-phonon decoherence in solid-state paramagnetic defects from first principles

Author(s): Sourav Mondal; Alessandro Lunghi
Published in: npj Computational Materials, 2023, ISSN 2057-3960
Publisher: Springer Nature
DOI: 10.1038/s41524-023-01082-9

Toward exact predictions of spin-phonon relaxation times: An ab initio implementation of open quantum systems theory

Author(s): Alessandro Lunghi
Published in: Science Advances, Issue 1, 2022, ISSN 2375-2548
Publisher: Science Advances
DOI: 10.1126/sciadv.abn7880

Book chapters (1)

Spin-Phonon Relaxation in Magnetic Molecules: Theory, Predictions and Insights

Author(s): Lunghi, Alessandro
Published in: Computational Modelling of Molecular Nanomagnets, Issue 1, 2023, Page(s) 219-289, ISSN 2542-4483
Publisher: Springer
DOI: 10.1007/978-3-031-31038-6_6