activity
20192026
most citedA complete ab initio view of Orbach and Raman spin-lattice relaxation in a Dysprosium coordination compound

227 citations · 456 across the 33 of their papers we have counts for

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Showing cond-mat.mtrl-sciShow all

20 papers · 1 filter

cond-mat.mtrl-sci2026★ 1 cited

Maximizing the magnetic anisotropy of Dy complexes by fine tuning organic ligands: A systematic multireference high-throughput exploration of over 30k molecules

Lion Frangoulis, Lorenzo A. Mariano. Vu Ha Anh Nguyen, Zahra Khatibi +1

The design of the coordination environment of magnetic ions is key to achieving properties such as large magnetic anisotropy and slow magnetic relaxation, but a systematic explorat…

cond-mat.mtrl-sci2026

A first-principles linear response theory for open quantum systems and its application to Orbach and direct magnetic relaxation in Ln-based coordination polymers

Mikolaj Żychowicz, Jakub J. Zakrzewski, Szymon Chorazy +1

Single-Molecule Magnets (SMMs) exhibit slow magnetic relaxation as a result of axial magnetic anisotropy inhibiting spin-phonon transitions. In order to establish a direct link bet…

cond-mat.mtrl-sci2026

Raman relaxation in Yb(III) molecular qubits: non-trivial correlations between spin-phonon coupling and molecular structure

Giacomo Sansone, Lorenzo A. Mariano, Stefano Carretta +2

The coordination complexes of Yb(III) exhibit some of the longest spin coherence times among 4f compounds, making them a promising platform for molecular quantum technologies. Whil…

cond-mat.mtrl-sci2026★ 1 cited

Efficient training of generative models from multireference simulations and its application to the design of Dy complexes with large magnetic anisotropy

Zahra Khatibi, Lorenzo A. Mariano, Lion Frangoulis +1

Generative machine learning models can potentially provide direct access to novel and relevant portions of the full chemical space, overcoming the cost of systematic sampling. Howe…

cond-mat.mtrl-sci2025

Generating new coordination compounds via multireference simulations, genetic algorithms and machine learning: the case of Co(II) molecular magnets

Lion Frangoulis, Zahra Khatibi, Lorenzo A. Mariano +1

The design of coordination compounds with target properties often requires years of continuous feedback loop between theory, simulations and experiments. In the case of magnetic mo…

cond-mat.mtrl-sci2024

The spin-phonon relaxation mechanism of single-molecule magnets in the presence of strong exchange coupling

Sourav Mondal, Julia Netz, David Hunger +5

Magnetic relaxation in coordination compounds is largely dominated by the interaction of the spin with phonons. Large zero-field splitting and exchange coupling values have been em…

cond-mat.mtrl-sci2024

The Mechanism of Spin-Phonon Relaxation in Endohedral Metallofullene Single Molecule Magnets

Tanu Sharma, Rupesh Kumar Tiwari, Sourav Dey +3

This study presents the first-ever investigation of spin-phonon coupling mechanisms in fullerene-based single-molecule magnets (SMMs) using ab initio CASSCF combined with DFT calcu…

cond-mat.mtrl-sci2024

A machine-learning framework for accelerating spin-lattice relaxation simulations

Valerio Briganti, Alessandro Lunghi

Molecular and lattice vibrations are able to couple to the spin of electrons and lead to their relaxation and decoherence. Ab initio simulations have played a fundamental role in s…

cond-mat.mtrl-sci2022

Unravelling the contributions to spin-lattice relaxation in Kramers single-molecule magnets

Sourav Mondal, Alessandro Lunghi

The study of how spin interacts with lattice vibrations and relaxes to equilibrium provides unique insights on its chemical environment and the relation between electronic structur…

cond-mat.mtrl-sci2022★ 3 cited

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

Alessandro Lunghi

Magnetic molecules have played a central role in the development of magnetism and coordination chemistry and their study keeps leading innovation in cutting-edge scientific fields…

cond-mat.mtrl-sci2022★ 49 cited

Predicting tensorial molecular properties with equivariant machine-learning models

Vu Ha Anh Nguyen, Alessandro Lunghi

Embedding molecular symmetries into machine-learning models is key for efficient learning of chemico-physical scalar properties, but little evidence on how to extend the same strat…

cond-mat.mtrl-sci2021★ 123 cited

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

Alessandro Lunghi

Spin-phonon coupling is the main drive of spin relaxation and decoherence in solid-state semiconductors at finite temperature. Controlling this interaction is a central problem for…

cond-mat.mtrl-sci2021

Stiffness and atomic-scale friction in superlubricant MoS bilayers

Rui Dong, Alessandro Lunghi, Stefano Sanvito

By using ab-initio-accurate force fields and molecular dynamics simulations we demonstrate that the layer stiffness has profound effects on the superlubricant state of two-dimensio…

cond-mat.mtrl-sci2021★ 227 cited

A complete ab initio view of Orbach and Raman spin-lattice relaxation in a Dysprosium coordination compound

Matteo Briganti, Fabio Santanni, Lorenzo Tesi +3

The unique electronic and magnetic properties of Lanthanides molecular complexes place them at the forefront of the race towards high-temperature single-ion magnets and magnetic qu…

cond-mat.mtrl-sci2020

Multiple Spin-Phonon Relaxation Pathways in a Kramer Single-Ion Magnet

Alessandro Lunghi, Stefano Sanvito

We present a first-principles investigation of spin-phonon relaxation in a molecular crystal of Co(II) single-ion magnets. Our study combines electronic structure calculations with…

cond-mat.mtrl-sci2019★ 4 cited

Ligand-field contributions to spin-phonon coupling in a family of Vanadium molecular qubits from multi-reference electronic structure theory

Alessandro Lunghi

Molecular electronic spins represent one of the most promising building blocks for the design of quantum computing architectures. However, the advancement of this technology requir…

cond-mat.mtrl-sci2019★ 1 cited

Pushing the limits of atomistic simulations towards ultra-high temperature: a machine-learning force field for ZrB2

Yanhui Zhang, Alessandro Lunghi, Stefano Sanvito

Determining thermal and physical quantities across a broad temperature domain, especially up to the ultra-high temperature region, is a formidable theoretical and experimental chal…

cond-mat.mtrl-sci2019

Surfing multiple conformation-property landscapes via machine learning: Designing magnetic anisotropy

Alessandro Lunghi, Stefano Sanvito

The advent of computational statistical disciplines, such as machine learning, is leading to a paradigm shift in the way we conceive the design of new compounds. Today computationa…

cond-mat.mtrl-sci2019★ 2 cited

First-principles investigation of spin-phonon coupling in vanadium-based molecular spin qubits

Andrea Albino, Stefano Benci, Lorenzo Tesi +5

Paramagnetic molecules can show long spin-coherence times, which make them good candidates as quantum bits. Reducing the efficiency of the spin-phonon interaction is the primary ch…

cond-mat.mtrl-sci2019★ 15 cited

Electronic spin-spin decoherence contribution in molecular qubits by quantum unitary spin dynamics

Alessandro Lunghi, Stefano Sanvito

The realisation of quantum computers based on molecular electronic spins requires the design of qubits with very long coherence times, T2. Dephasing can proceed over several differ…