arXiv subjects

Stefano Sanvito

Publications and source records attributed to Stefano Sanvito.

At least 55 records · Page 3Linked to original sources

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

Co/AlP/Co, Co/GaN/Co as magnetic tunnel junctions

AlP and GaN are wide band-gap semiconductors (SC) uses in opto-electronic industry as light emitting diodes. Here we investigate it as future perspective candidate for insulating barrier in magnetic tunnel junctions. We employ density functional theory for ground state electronic properties and non-equilibrium Green's function method for quantum transport and examined Co/AlP/Co and Co/GaN/Co MTJs. We find that both AlP and GaN valance band maxima are predominantly made with $p_z$-type orbitals while conduction band minima are $s$-type symmetry. We find that both AlP and GaN filter $Δ_1$ symmetry of Bloch states at $Γ$-point and transmission coefficient at any energy level in-between the band-gap of materials, is mostly driven by $Δ_1$ symmetry of Bloch states tunnel via $Γ$-point in first Brillouin zones. We find large magneto-resistance $\sim$300\% in Co/AlP/Co MTJs at zero-bias. In Co/GaN/Co MTJs we find $\sim$300\% TMR at 1.25 eV below the Fermi energy ($E_{F}-1.25$)~eV, while $\sim$10\% TMR around $E_F$ in zero-bias calculations. We notice that both majority and minority $Δ_{2'}$ symmetry of Bloch states with rather different $spd$-orbitals compositions tunnel in Co[0001]/AlP[0001] MTJs and exhibit non-zero TMR, whereas in Co[111]/GaN[0001] MTJs, the both majority and minority $Δ_1$ symmetry of Bloch states with different energy-gradient tunnels at Fermi energy level along [111] transport direction. Our work accentuate the process for systematic, efficient, accurate and versatile framework to design the semiconductors based MTJs for low power electronics.

cond-mat.mtrl-sci↗

arXiv2021

Machine-learning semi-local density functional theory for many-body lattice models at zero and finite temperature

We introduce a machine-learning density-functional-theory formalism for the spinless Hubbard model in one dimension at both zero and finite temperature. In the zero-temperature case this establishes a one-to-one relation between the site occupation and the total energy, which is then minimised at the ground-state occupation. In contrast, at finite temperature the same relation is defined between the Helmholtz free energy and the equilibrium site occupation. Most importantly, both functionals are semi-local, so that they are independent from the size of the system under investigation and can be constructed over exact data for small systems. These 'exact' functionals are numerically defined by neural networks. We also define additional neural networks for finite-temperature thermodynamical quantities, such as the entropy and heat capacity. These can be either a functional of the ground-state site occupation or of the finite-temperature equilibrium site occupation. In the first case their equilibrium value does not correspond to an extremal point of the functional, while it does in the second case. Our work gives us access to finite-temperature properties of many-body systems in the thermodynamic limit.

cond-mat.str-el↗

arXiv2021

On the conservation of the angular momentum in ultrafast spin dynamics

The total angular momentum of a close system is a conserved quantity, which should remain constant in time for any excitation experiment once the pumping signal has extinguished. Such conservation, however, is never satisfied in practice in any real-time first principles description of the demagnetization process. Furthermore, there is a growing experimental evidence that the same takes place in experiments. The missing angular momentum is usually associated to lattice vibrations, which are not measured experimentally and are never considered in real-time simulations. Here we critically analyse the issue and conclude that current state-of-the-art simulations violate angular momentum conservation already at the electronic level of description. This shortcoming originates from an oversimplified description of the spin-orbit coupling, which includes atomic contributions but neglects completely that of itinerant electrons. We corroborate our findings with time-dependent simulations using model tight-binding Hamiltonians, and show that indeed such conservation can be re-introduced by an appropriate choice of spin-orbit coupling. The consequences of our findings on recent experiments are also discussed.

cond-mat.mes-hall↗

arXiv2021

Atomistic simulations of surface reactions in ultra-high-temperature ceramics: O2, H2O and CO adsorption and dissociation on ZrB2 (0001) surfaces

Understanding surface reactivity is crucial in many fields, going from heterogeneous catalysis to materials oxidation and corrosion. In order to decipher the surface reactions of ZrB2 exposed to the harsh environment of aerospace components, the chemical activity of both Zr- and B-surfaces is predicted and compared by using density functional theory and nudged elastic band methods. In particular the adsorption, dissociation and diffusion of O2, CO and H2O are extensively examined through the calculation of surface adsorption energies and reaction pathways. We find the dissociative adsorption of O2 dominating the reactivity of ZrB2 surfaces, while the dissociation of H2O and CO is weakly active on Zr-surfaces, and even less activated on B-terminated ones. Importantly, we discover that the reaction of O2 and H2O can trigger strong surface reconstruction at B-surfaces. Our work thus provides significant insights into the diverse adsorption and reaction mechanisms of ZrB2 surfaces.

cond-mat.mtrl-sci↗

arXiv2020

Edge superconductivity in Multilayer WTe2 Josephson junction

WTe2, as a type-II Weyl semimetal, has 2D Fermi arcs on the (001) surface in the bulk and 1D helical edge states in its monolayer. These features have recently attracted wide attention in condensed matter physics. However, in the intermediate regime between the bulk and monolayer, the edge states have not been resolved owing to its closed band gap which makes the bulk states dominant. Here, we report the signatures of the edge superconductivity by superconducting quantum interference measurements in multilayer WTe2 Josephson junctions and we directly map the localized supercurrent. In thick WTe2 (~60 nm), the supercurrent is uniformly distributed by bulk states with symmetric Josephson effect ($\left|I_c^+(B)\right|=\left|I_c^-(B)\right|$). In thin WTe2 (10 nm), however, the supercurrent becomes confined to the edge and its width reaches up to 1.4 um and exhibits non-symmetric behavior $\left|I_c^+(B)\right|\neq \left|I_c^-(B)\right|$. The ability to tune the edge domination by changing thickness and the edge superconductivity establishes WTe2 as a promising topological system with exotic quantum phases and a rich physics.

cond-mat.supr-con↗

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↗

arXiv2020

Role of longitudinal fluctuations in L$1_0$ FePt

L$1_0$ FePt is a technologically important material for a range of novel data storage applications. In the ordered FePt structure the normally non-magnetic Pt ion acquires a magnetic moment, which depends on the local field originating from the neighboring Fe atoms. In this work a model of FePt is constructed, where the induced Pt moment is simulated by using combined longitudinal and rotational spin dynamics. The model is parameterized to include a linear variation of the moment with the exchange field, so that at the Pt site the magnetic moment depends on the Fe ordering. The Curie temperature of FePt is calculated and agrees well with similar models that incorporate the Pt dynamics through an effective Fe-only Hamiltonian. By computing the dynamic correlation function the anisotropy field and the Gilbert damping are extracted over a range of temperatures. The anisotropy exhibits a power-law dependence with temperature with exponent $n\approx2.1$. This agrees well with what observed experimentally and it is obtained without including a two-ion anisotropy term as in other approaches. Our work shows that incorporating longitudinal fluctuations into spin dynamics calculations is crucial for understanding the properties of materials with induced moments.

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

Predicting the Curie temperature of ferromagnets using machine learning

The magnetic properties of a material are determined by a subtle balance between the various interactions at play, a fact that makes the design of new magnets a daunting task. High-throughput electronic structure theory may help to explore the vast chemical space available and offers a design tool to the experimental synthesis. This method efficiently predicts the elementary magnetic properties of a compound and its thermodynamical stability, but it is blind to information concerning the magnetic critical temperature. Here we introduce a range of machine-learning models to predict the Curie temperature, $T_\mathrm{C}$, of ferromagnets. The models are constructed by using experimental data for about 2,500 known magnets and consider the chemical composition of a compound as the only feature determining $T_\mathrm{C}$. Thus, we are able to establish a one-to-one relation between the chemical composition and the critical temperature. We show that the best model can predict $T_\mathrm{C}$'s with an accuracy of about 50K. Most importantly our model is able to extrapolate the predictions to regions of the chemical space, where only a little fraction of the data was considered for training. This is demonstrated by tracing the $T_\mathrm{C}$ of binary intermetallic alloys along their composition space and for the Al-Co-Fe ternary system.

cond-mat.mtrl-sci↗

arXiv2019

The nanoscale structure of the Pt-water double layer under bias revealed

The nanoscopic mass and charge distribution within the double layer at electrified interfaces plays a key role in electrochemical phenomena of huge technological relevance for energy production and conversion. However, in spite of its importance, the nanoscopic structure of the double layer and its response to an applied potential is still almost entirely unknown, even for Pt-water, the most fundamental electrochemical interface. Using a general ab initio methodology which advances previous models towards a dynamic and more realistic description of an electrode/electrolyte interface, we simulate for the first time the nanoscopic structure of the Pt-water double layer and its response to an applied potential, in realistic solution conditions. We reveal that the nanoscopic metal/surface structure and charging are not captured by traditional capacitor models, as the electrode polarization is associated with a charge oscillation within the double layer and a densification of the water layer in contact with the electrode, both of which strongly depend on the applied potential. Furthermore, we demonstrate that the interface dipole is not determined by the reorientation of the first water layer in contact with the electrode, but by its charging state in combination with its number density, while water reorientation becomes relevant only in the second water layer. Our findings will be essential to develop highly realistic models for the catalytic processes at the Pt-water interface.

physics.chem-ph↗

arXiv2019

Interface engineering of graphene nanosheet reinforced ZrB$_2$ composites by tuning surface contacts

The mechanical properties of heterophase interfaces are critically important for the behaviour of graphene-reinforced composites. In this work, the structure, adhesion, cleavage and sliding of heterophase interfaces, formed between a ZrB$_2$ matrix and graphene nanosheets, are systematically investigated by density functional theory, and compared to available experimental data. We demonstrate that the surface chemistry of the ZrB$_2$ matrix material largely shapes the interface structures (of either Zr-C-Zr or B-C-B type) and the nature of the interfacial interaction. The Zr-C-Zr interfaces present strong chemical bonding and their response to mechanical stress is significantly influenced by graphene corrugation. In contrast B-C-B interfaces, interacting through the relatively weak $π$-$π$ stacking, show attributes similar to 2D materials heterostructures. Our theoretical results provide insights into the interface bonding mechanisms in graphene/ceramic composites, and emphasize the prospect for their design via interface engineering enabled by surface contacts.

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↗

arXiv2018

Machine learning density functional theory for the Hubbard model

The solution of complex many-body lattice models can often be found by defining an energy functional of the relevant density of the problem. For instance, in the case of the Hubbard model the spin-resolved site occupation is enough to describe the system total energy. Similarly to standard density functional theory, however, the exact functional is unknown and suitable approximations need to be formulated. By using a deep-learning neural network trained on exact-diagonalization results we demonstrate that one can construct an exact functional for the Hubbard model. In particular, we show that the neural network returns a ground-state energy numerically indistinguishable from that obtained by exact diagonalization and, most importantly, that the functional satisfies the two Hohenberg-Kohn theorems: for a given ground-state density it yields the external potential and it is fully variational in the site occupation.

cond-mat.str-el↗