arXiv subjects

Alessandro Lunghi

Publications and source records attributed to Alessandro Lunghi.

36 records · Page 2Linked to original sources

arXiv2023

Spin-vibronic dynamics in open-shell systems beyond the spin Hamiltonian formalism

Vibronic coupling has a dramatic influence over a large number of molecular processes, ranging from photo-chemistry, to spin relaxation and electronic transport. The simulation of vibronic coupling with multi-reference wavefunction methods has been largely applied to organic compounds, and only early efforts are available for open-shell systems such as transition metal and lanthanide complexes. In this work, we derive a numerical strategy to differentiate the molecular electronic Hamiltonian in the context of multi-reference ab initio methods and inclusive of spin-orbit coupling effects. We then provide a formulation of open quantum system dynamics able to predict the time evolution of the electrons' density matrix under the influence of a Markovian phonon bath up to fourth-order perturbation theory. We apply our method to Co(II) and Dy(III) molecular complexes exhibiting long spin relaxation times and successfully validate our strategy against the use of an effective spin Hamiltonian. Our study shed light on the nature of vibronic coupling, the importance of electronic excited states in spin relaxation, and the need for high-level computational chemistry to quantify it.

physics.chem-ph↗

arXiv2023

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

Machine-learning force fields enable an accurate and universal description of the potential energy surface of molecules and materials on the basis of a training set of ab initio data. However, large-scale applications of these methods rest on the possibility to train accurate machine learning models with a small number of ab initio data. In this respect, active-learning strategies, where the training set is self-generated by the model itself, combined with linear machine-learning models are particularly promising. In this work, we explore an active-learning strategy based on linear regression and able to predict the model's uncertainty on predictions for molecular configurations not sampled by the training set, thus providing a straightforward recipe for the extension of the latter. We apply this strategy to the spectral neighbor analysis potential and show that only tens of ab initio simulations of atomic forces are required to generate stable force fields for room-temperature molecular dynamics at or close to chemical accuracy. Moreover, the method does not necessitate any conformational pre-sampling, thus requiring minimal user intervention and parametrization.

physics.comp-ph↗

arXiv2023

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

Paramagnetic defects in diamond and hexagonal boron nitride possess a unique combination of spin and optical properties that make them prototypical solid-state qubits. Despite the coherence of these spin qubits being critically limited by spin-phonon relaxation, a full understanding of this process is not yet available. Here we apply ab initio spin dynamics simulations to this problem and quantitatively reproduce the experimental temperature dependence of spin relaxation time and spin coherence time. We demonstrate that low-frequency two-phonon modulations of the zero-field splitting are responsible for spin relaxation and decoherence, and point to the nature of vibrations in 2-dimensional materials as the culprit for their shorter coherence time. These results provide a novel interpretation to spin-phonon decoherence in solid-state paramagnetic defects, offer a new strategy to correctly interpret experimental results, and pave the way for the accelerated design of new spin qubits.

quant-ph↗

arXiv2022

A self-consistent field approach for the variational quantum eigensolver: orbital optimization goes adaptive

We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Tailored Ansatz Variational Quantum Eigensolver (ADAPT-VQE) framework for efficient quantum simulations of chemical systems on near-term quantum computers. To this end, our ADAPT-VQE-SCF approach combines the idea of generating an ansatz with a small number of parameters, resulting in shallow-depth quantum circuits with a direct minimization of an energy expression which is correct to second order with respect to changes in the molecular orbital basis. Our numerical analysis, including calculations for the transition metal complex ferrocene (Fe$\rm (C_5H_5)_2$), indicates that convergence in the self-consistent orbital optimization loop can be reached without a considerable increase in the number of two-qubit gates in the quantum circuit by comparison to a VQE optimization in the initial molecular orbital basis. Moreover, the orbital optimization can be carried out simultaneously within each iteration of the ADAPT-VQE cycle. ADAPT-VQE-SCF thus allows us to implement a routine analogous to CASSCF, a cornerstone of state-of-the-art computational chemistry, in a hardware-efficient manner on near-term quantum computers. Hence, ADAPT-VQE-SCF paves the way towards a paradigm shift for quantitative quantum-chemistry simulations on quantum computers by requiring fewer qubits and opening up for the use of large and flexible atomic orbital basis sets in contrast to earlier methods that are predominantly based on the idea of full active spaces with minimal basis sets.

quant-ph↗

arXiv2022

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

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 structure and molecular composition. Despite its importance for several disciplines, ranging from magnetic resonance to quantum technologies, a convincing interpretation of spin dynamics in crystals of magnetic molecules is still lacking due to the challenging experimental determination of the correct spin relaxation mechanism. We apply ab initio spin dynamics to a series of twelve coordination complexes of Co(II) and Dy(III) ions selected among $\sim$240 compounds that largely cover the literature on single-molecule magnets and well represent different regimes of spin relaxation. Simulations reveal that the Orbach spin relaxation rate of known compounds mostly depends on the ions' zero-field splitting and little on the details of molecular vibrations. Raman relaxation is instead found to be also significantly affected by the features of low-energy phonons. These results provide a complete understanding of the factors limiting spin lifetime in single-molecule magnets and revisit years of experimental investigations by making it possible to transparently distinguish Orbach and Raman relaxation mechanisms.

cond-mat.mtrl-sci↗

arXiv2022

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

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 such as magnetic resonance, magnetism, spintronics, and quantum technologies. Crucially, a long spin lifetime well above cryogenic temperature is a stringent requirement for all these applications. In this chapter we review the foundations of spin relaxation theory and provide a detailed overview of first-principles strategies applied to the problem of spin-phonon relaxation in magnetic molecules. Firstly, we present a rigorous formalism of spin-phonon relaxation based on open quantum systems theory. These results are then used to derive classical phenomenological relations based on the Debye model. Finally, we provide a prescription of how to map the relaxation formalism onto existing electronic structure methods to obtain a quantitative picture of spin-phonon relaxation. Examples from the literature, including both transition metals and lanthanides compounds, will be discussed in order to illustrate how Direct, Orbach and Raman relaxation mechanisms can affect spin dynamics for this class of compounds.

cond-mat.mtrl-sci↗

arXiv2022

Predicting tensorial molecular properties with equivariant machine-learning models

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 strategy to tensorial quantities exists. Here we formulate a scalable equivariant machine-learning model based on local atomic environment descriptors. We apply it to a series of molecules and show that accurate predictions can be achieved for a comprehensive list of dielectric and magnetic tensorial properties of different ranks. These results show that equivariant models are a promising platform to extend the scope of machine learning in materials modelling.

cond-mat.mtrl-sci↗

arXiv2021

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

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 many disciplines, ranging from magnetic resonance to quantum technologies. Spin relaxation theories have been developed for almost a century but often employ a phenomenological description of phonons and their coupling to spin, resulting in a non-predictive tool and hindering our detailed understanding of spin dynamics. Here we combine fourth-order time-local quantum master equations with advanced electronic structure methods and perform predictions of spin-phonon relaxation time for a series of solid-state coordination compounds based on both transition metals and lanthanide Kramers ions. The agreement between experiments and simulations demonstrates that an accurate, universal and fully ab initio implementation of spin relaxation theory is possible, thus paving the way to a systematic study of spin-phonon relaxation in solid-state materials.

cond-mat.mtrl-sci↗

arXiv2021

Stiffness and atomic-scale friction in superlubricant MoS$_2$ bilayers

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-dimensional van der Waals heterostructures. These are engineered to have identical inter-layer sliding energy surfaces, but layers of different rigidity, so that the effects of the stiffness on the microscopic friction in the superlubricant state can be isolated. A twofold increase in the intra-layer stiffness reduces the friction by approximately a factor six. Most importantly, we find two sliding regimes as a function of the sliding velocity. At low velocity the heat generated by the motion is efficiently exchanged between the layers and the friction is independent on whether the sliding layer is softer or harder than the substrate. In contrast, at high velocity the friction heat flux cannot be exchanged fast enough, and the build up of significant temperature gradients between the layers is observed. In this situation the temperature profile depends on whether the slider is softer than the substrate.

cond-mat.mtrl-sci↗

arXiv2021

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

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 quantum bits. The design of compounds of this class has so far been almost exclusively driven by static crystal field considerations, with emphasis on increasing the magnetic anisotropy barrier. This guideline has now reached its maximum potential and new progress can only come from a deeper understanding of spin-phonon relaxation mechanisms. In this work we compute relaxation times fully ab initio and unveil the nature of all spin-phonon relaxation mechanisms, namely Orbach and Raman pathways, in a prototypical Dy single-ion magnet. Computational predictions are in agreement with the experimental determination of spin relaxation time and crystal field anisotropy, and show that Raman relaxation, dominating at low temperature, is triggered by low-energy phonons and little affected by further engineering of crystal field axiality. A comprehensive analysis of spin-phonon coupling mechanism reveals that molecular vibrations beyond the ion's first coordination shell can also assume a prominent role in spin relaxation through an electrostatic polarization effect. Therefore, this work shows the way forward in the field by delivering a novel and complete set of chemically-sound design rules tackling every aspect of spin relaxation at any temperature

cond-mat.mtrl-sci↗

arXiv2020

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

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 machine-learning force fields and unravels the nature of both the Orbach and the Raman relaxation channels in terms of atomistic processes. We find that although both mechanisms are mediated by the excited spin states, the low temperature spin dynamics is dominated by phonons in the THz energy range, which partially suppress the benefit of having a large magnetic anisotropy. This study also determines the importance of intra-molecular motions for both the relaxation mechanisms and paves the way to the rational design of a new generation of single-ion magnets with tailored spin-phonon coupling.

cond-mat.mtrl-sci↗

arXiv2020

The limit of spin lifetime in solid-state electronic spins

The development of spin qubits for quantum technologies requires their protection from the main source of finite-temperature decoherence: atomic vibrations. Here we eliminate one of the main barriers to the progress in this field by providing a complete first-principles picture of spin relaxation that includes up to two-phonon processes. Our method is based on machine learning and electronic structure theory and makes the prediction of spin lifetime in realistic systems feasible. We study a prototypical vanadium-based molecular qubit and reveal that the spin lifetime at high temperature is limited by Raman processes due to a small number of THz intra-molecular vibrations. These findings effectively change the conventional understanding of spin relaxation in this class of materials and open new avenues for the rational design of long-living spin systems.

cond-mat.mes-hall↗

arXiv2019

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

Molecular electronic spins represent one of the most promising building blocks for the design of quantum computing architectures. However, the advancement of this technology requires the increase of spin lifetime at ambient temperature. Spin-phonon coupling has been recognized as the key interaction dictating spin relaxation at high temperature in molecular crystals and the search for chemical-design principles to control such interaction are a fundamental challenge in the field. Here we present a multi-reference first-principles analysis of the g-tensor and the spin-phonon coupling in a series of four exa-coordinate Vanadium(IV) molecular complexes, where the catecholate ligand donor atom is progressively changed from Oxygen to Sulphur, Selenium and Tellurium. A ligand field interpretation of the multi-reference electronic structure theory results made it possible to rationalize the correlation between the molecular g-shifts and the average spin-phonon coupling coefficients, revealing the role of spin-orbit coupling, chemical bond covalency and energy splitting of d-like orbitals in spin relaxation. Our study reveals the simultaneous increase of metal-ligand covalency and electronic excited state energy separation as key elements of an optimal strategy towards long spin-lattice lifetimes in molecular qubits.

cond-mat.mtrl-sci↗

arXiv2019

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

Determining thermal and physical quantities across a broad temperature domain, especially up to the ultra-high temperature region, is a formidable theoretical and experimental challenge. At the same time it is essential for understanding the performance of ultra-high temperature ceramic (UHTC) materials. Here we present the development of a machine-learning force field for ZrB2, one of the primary members of the UHTC family with a complex bonding structure. The force field exhibits chemistry accuracy for both energies and forces and can reproduce structural, elastic and phonon properties, including thermal expansion and thermal transport. A thorough comparison with available empirical potentials shows that our force field outperforms the competitors. Most importantly, its effectiveness is extended from room temperature to the ultra-high temperature region (up to ~ 2,500 K), where measurements are very difficult, costly and some time impossible. Our work demonstrates that machine-learning force fields can be used for simulations of materials in a harsh environment, where no experimental tools are available, but crucial for a number of engineering applications, such as in aerospace, aviation and nuclear.

cond-mat.mtrl-sci↗

arXiv2019

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

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 computational science does not only provide a sound understanding of experiments, but also can directly design the best compound for specific applications. This approach, known as reverse engineering, requires the construction of models able to efficiently predict continuous structure-property maps. Here we show that reverse engineering can be used to tune the magnetic properties of a single-ion molecular magnet in an automated intelligent fashion. We design a machine learning model to predict both the energy and magnetic properties as function of the chemical structure. Then, a particle-swarm optimization algorithm is used to explore the conformational landscapes in the search for new molecular structures leading to an enhanced magnetic anisotropy. We find that a 5% change in one of the coordination angles leads to a 50% increase in the anisotropy. Our approach paves the way for a machine-learning-driven exploration of the chemical space of general classes of magnetic materials. Most importantly, it can be applied to any structure-property relation and offers an effective way to automatically generate new materials with target properties starting from the knowledge of previously synthesized ones.

cond-mat.mtrl-sci↗

arXiv2019

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

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 challenge towards achieving long coherence times over a wide temperature range in soft molecular lattices. The lack of a microscopic understanding about the role of vibrations in spin relaxation strongly undermines the possibility to chemically design better performing molecular qubits. Here we report a first-principles characterization of the main mechanism contributing to the spin-phonon coupling for a class of vanadium(IV) molecular qubits. Post Hartree Fock and Density Functional Theory are used to determine the effect of both reticular and intra-molecular vibrations on the modulation of the Zeeman energy for four molecules showing different coordination geometries and ligands. This comparative study provides the first insight into the role played by coordination geometry and ligand field strength in determining the spin-lattice relaxation time of molecular qubits, opening the avenue to a rational design of new compounds.

cond-mat.mtrl-sci↗

arXiv2019

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

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 different microscopic pathways, active at the same time and in different regimes. This makes the rationalisation of the dephasing process not straightforward. Here we present a computational methodology able to address spin decoherence processes for a general ensemble of spins. The method consists in the propagation of the unitary quantum spin dynamics on a reduced Hilbert space. Then we study the dependence of spin dephasing over the magnetic dilution for a crystal of Vanadyl-based molecular qubits. Our results show the importance of long-range electronic spin-spin interactions and their effect on the shape of the spin-echo signal.

cond-mat.mtrl-sci↗

arXiv2019

Spin-Phonon Relaxation in Molecular Qubits from First Principles Spin Dynamics

The coupling between electronic spins and lattice vibrations is fundamental for driving relaxation in magnetic materials. The debate over the nature of spin-phonon coupling dates back to the 40's, but the role of spin-spin, spin-orbit and hyperfine interactions, has never been fully established. Here we present a comprehensive study of the spin dynamics of a crystal of Vanadyl-based molecular qubits by means of first-order perturbation theory and first-principles calculations. We quantitatively determine the role of the Zeeman, hyperfine and electronic spin dipolar interactions in the direct mechanism of spin relaxation. We show that, in a high magnetic field regime, the modulation of the Zeeman Hamiltonian by the intra-molecular components of the acoustic phonons dominates the relaxation mechanism. In low fields, hyperfine coupling takes over, with the role of spin-spin dipolar interaction remaining the less important for the spin relaxation.

quant-ph↗