arXiv subjects

A. H. Castro Neto

Publications and source records attributed to A. H. Castro Neto.

At least 19 recordsLinked to original sources

arXiv2025

Predicting ionic conductivity in solids from the machine-learned potential energy landscape

Discovering new superionic materials is essential for advancing solid-state batteries, which offer improved energy density and safety compared to the traditional lithium-ion batteries with liquid electrolytes. Conventional computational methods for identifying such materials are resource-intensive and not easily scalable. Recently, universal interatomic potential models have been developed using equivariant graph neural networks. These models are trained on extensive datasets of first-principles force and energy calculations. One can achieve significant computational advantages by leveraging them as the foundation for traditional methods of assessing the ionic conductivity, such as molecular dynamics or nudged elastic band techniques. However, the generalization error from model inference on diverse atomic structures arising in such calculations can compromise the reliability of the results. In this work, we propose an approach for the quick and reliable screening of ionic conductors through the analysis of a universal interatomic potential. Our method incorporates a set of heuristic structure descriptors that effectively employ the rich knowledge of the underlying model while requiring minimal generalization capabilities. Using our descriptors, we rank lithium-containing materials in the Materials Project database according to their expected ionic conductivity. Eight out of the ten highest-ranked materials are confirmed to be superionic at room temperature in first-principles calculations. Notably, our method achieves a speed-up factor of approximately 50 compared to molecular dynamics driven by a machine-learning potential, and is at least 3,000 times faster compared to first-principles molecular dynamics.

cond-mat.mtrl-sci↗

arXiv2024

Diagonalization without Diagonalization: A Direct Optimization Approach for Solid-State Density Functional Theory

We present a novel approach to address the challenges of variable occupation numbers in direct optimization of density functional theory (DFT). By parameterizing both the eigenfunctions and the occupation matrix, our method minimizes the free energy with respect to these parameters. As the stationary conditions require the occupation matrix and the Kohn-Sham Hamiltonian to be simultaneously diagonalizable, this leads to the concept of ``self-diagonalization,'' where, by assuming a diagonal occupation matrix without loss of generality, the Hamiltonian matrix naturally becomes diagonal at stationary points. Our method incorporates physical constraints on both the eigenfunctions and the occupations into the parameterization, transforming the constrained optimization into an fully differentiable unconstrained problem, which is solvable via gradient descent. Implemented in JAX, our method was tested on aluminum and silicon, confirming that it achieves efficient self-diagonalization, produces the correct Fermi-Dirac distribution of the occupation numbers and yields band structures consistent with those obtained with SCF methods in Quantum Espresso.

physics.chem-ph↗

arXiv2023

Theory of defect-mediated ionic transport in Li, Na and K beta and beta prime prime aluminas

Alkali metal $β$/$β^{\prime\prime}$ aluminas are among the fastest ionic conductors, yet little is understood about the role of defects in the ion transport mechanism. Here, we use density functional theory (DFT) to investigate the crystal structures of $β$ and $β^{\prime\prime}$ phases, and vacancy and interstitial defects in these materials. We find that charge transport is likely to be dominated by alkali metal interstitials in $β$-aluminas and by vacancies in $β^{\prime\prime}$ aluminas. Lower bounds for the activation energy for diffusion are found by determining the minimum energy paths for defect migration. The resulting migration barriers are lower than the experimental activation energies for conduction in Na $β$ and $β^{\prime\prime}$ aluminas, suggesting a latent potential for optimization. The lowest activation energy of about 20 meV is predicted for correlated vacancy migration in K $β^{\prime\prime}$ alumina.

cond-mat.mtrl-sci↗

arXiv2023

Two-dimensional non-linear hydrodynamics and nanofluidics

A water monolayer squeezed between two solid planes experiences strong out-of-plane confinement effects while expanding freely within the plane. As a consequence, the transport of such two-dimensional water combines hydrodynamic and nanofluidic features, intimately linked with each other. In this paper, we propose and explicitly solve a non-linear hydrodynamic equation describing two-dimensional water flow with viscosity parameters deduced from molecular dynamic simulations. We demonstrate that the very ability of two-dimensional water to flow in short channels is governed by the second (dilatational) viscosity coefficient, leading to flow compression and velocity saturation in the high-pressure limit. The viscosity parameter values depend strongly on whether graphene or hexoganal boron nitride layers are used to confine 2D water that offers an interesting opportunity to obtain various nanofluids out of the same water molecules just by using alternate materials to fabricate the 2D channels.

cond-mat.mtrl-sci↗

arXiv2023

D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory

Kohn-Sham Density Functional Theory (KS-DFT) has been traditionally solved by the Self-Consistent Field (SCF) method. Behind the SCF loop is the physics intuition of solving a system of non-interactive single-electron wave functions under an effective potential. In this work, we propose a deep learning approach to KS-DFT. First, in contrast to the conventional SCF loop, we propose to directly minimize the total energy by reparameterizing the orthogonal constraint as a feed-forward computation. We prove that such an approach has the same expressivity as the SCF method, yet reduces the computational complexity from O(N^4) to O(N^3). Second, the numerical integration which involves a summation over the quadrature grids can be amortized to the optimization steps. At each step, stochastic gradient descent (SGD) is performed with a sampled minibatch of the grids. Extensive experiments are carried out to demonstrate the advantage of our approach in terms of efficiency and stability. In addition, we show that our approach enables us to explore more complex neural-based wave functions.

cs.LG↗

arXiv2022

Unveiling the complex structure-property correlation of defects in 2D materials based on high throughput datasets

Modification of physical properties of materials and design of materials with on-demand characteristics is at the heart of modern technology. Rare application relies on pure materials--most devices and technologies require careful design of materials properties through alloying, creating heterostructures of composites or controllable introduction of defects. At the same time, such designer materials are notoriously difficult for modelling. Thus, it is very tempting to apply machine learning methods for such systems. Unfortunately, there is only a handful of machine learning-friendly material databases available these days. We develop a platform for easy implementation of machine learning techniques to materials design and populate it with datasets on pristine and defected materials. Here we describe datasets of defects in represented 2D materials such as MoS2, WSe2, hBN, GaSe, InSe, and black phosphorous, calculated using DFT. Our study provides a data-driven physical understanding of complex behaviors of defect properties in 2D materials, holding promise for a guide to the development of efficient machine learning models. In addition, with the increasing enrollment of datasets, our database could provide a platform for designing of materials with predetermined properties.

cond-mat.mtrl-sci↗

arXiv2022

Edge-Driven Phase Transitions in 2D Ice

2D water, confined by atomically flat layered materials, may transit into various crystalline phases even at room temperature. However, to gain full control over the crystalline state, we should not only confine water in the out of plane direction but also restrict its in plane motion, forming 2D water clusters or ribbons. One way to do this is by using an electric field, in particular the intrinsic electric field of an adjacent polar material. We have found that the crystalline phases of 2D water clusters placed between two hexagonal boron nitride hBN nanoribbons are crucially determined by the nanoribbons edges, the resulting polarity of the nanoribbons, and their interlayer distance. We make use of density functional theory with further assistance of molecular dynamics simulations to establish the comprehensive phase diagrams demonstrating transitions between liquid and solid phases and between the states of different crystalline orders. We also show that the crystalline orders are maintained when water flows between hBN channels under external pressure. Our results open a promising pathway towards the control of water structure and its flow by the use of the microscopic electric field of polar materials.

cond-mat.mtrl-sci↗

arXiv2021

Stability of a Rolled-Up Conformation State for Two-Dimensional Materials in Aqueous Solutions

Two-dimensional (2D) materials can roll up, forming stable scrolls under suitable conditions. However, the great diversity of materials and fabrication techniques has resulted in a huge parameter space significantly complicating the theoretical description of scrolls. In this Letter, we describe a universal binding energy of scrolls determined solely by their material parameters, the bending stiffness, and the Hamaker coefficient. Aiming to predict the stability of functionalized scrolls in water solutions, we consider the electrostatic double-layer repulsion force that may overcome the binding energy and flatten the scrolls. Our predictions are represented as comprehensive maps indicating the stable and unstable regions of a rolled-up conformation state in the space of material and external parameters. While focusing mostly on functionalized graphene in this work, our approach is applicable to the whole range of 2D materials able to form scrolls.

cond-mat.mtrl-sci↗

arXiv2021

Computational methods for 2D materials modelling

Materials with thickness ranging from a few nanometers to a single atomic layer present unprecedented opportunities to investigate new phases of matter constrained to the two-dimensional plane.Particle-particle Coulomb interaction is dramatically affected and shaped by the dimensionality reduction, driving well-established solid state theoretical approaches to their limit of applicability. Methodological developments in theoretical modelling and computational algorithms, in close interaction with experiments, led to the discovery of the extraordinary properties of two-dimensional materials, such as high carrier mobility, Dirac cone dispersion and bright exciton luminescence, and inspired new device design paradigms. This review aims to describe the computational techniques used to simulate and predict the optical, electronic and mechanical properties of two-dimensional materials, and to interpret experimental observations. In particular, we discuss in detail the particular challenges arising in the simulation of two-dimensional constrained fermions, and we offer our perspective on the future directions in this field.

cond-mat.mes-hall↗

arXiv2021

Collective Excitations in 2D Materials

Research on 2D materials has been one of the fastest-growing fields in condensed matter physics and materials science in the past 10 years. The low dimensionality and strong correlations of 2D systems give rise to electronic and structural properties, in the form of collective excitations, that do not have counterparts in ordinary 3D materials used in modern technology. These 2D materials present extraordinary opportunities for new technologies, such as in flexible electronics. In this Review, we focus on plasmons, excitons, phonons and magnons in 2D materials. We discuss the theoretical formalism of these collective excitations and elucidate how they differ from their 3D counterparts.

cond-mat.mes-hall↗

arXiv2020

Correlated states of a triangular net of coupled quantum wires: Implications for the phase diagram of marginally twisted bilayer graphene

We explore in detail the electronic phases of a system consisting of three non-colinear arrays of coupled quantum wires, each rotated 120 degrees with respect to the next. A perturbative renormalization-group analysis reveals that multiple correlated states can be stabilized: a $s$-wave or $d \pm id$ superconductor, a charge density wave insulator, a two-dimensional Fermi liquid, and a 2D Luttinger liquid (also known as smectic metal or sliding Luttinger liquid). The model provides an effective description of electronic interactions in small-angle twisted bilayer graphene and we discuss its implications in relation to the recent observation of correlated and superconducting groundstates near commensurate densities in magic-angle twisted samples, as well as the ``strange metal'' behavior at finite temperatures as a natural outcome of the 2D Luttinger liquid phase.

cond-mat.str-el↗

arXiv2019

Discommensuration-enhanced superconductivity in the charge density wave phases of transition-metal dichalcogenides

We introduce a McMillan-Ginzburg-Landau theory to describe the cooperative coexistence of charge-density and superconducting order in two-dimensional crystals. With a free-energy that explicitly accounts for the competition between commensurate and incommensurate ground states, we are able to map the transition between these phases and monitor the development of discommensurations in the near-commensurate regime. Attributing the enhancement of superconducting order to density-wave fluctuations, we propose a coupling scheme that yields a phase diagram in qualitative agreement with experiments in conducting transition metal dichalcogenides. The model predicts the development of non-uniform superconductivity similar to that arising from a pair-density wave, with a spatial texture driven by the underlying charge-density wave fluctuations.

cond-mat.mes-hall↗

arXiv2018

Strain-induced gauge and Rashba fields in ferroelectric Rashba lead chalcogenide PbX monolayers (X = S, Se, Te)

One of the exciting features of two-dimensional (2D) materials is their electronic and optical tunability through strain engineering. Previously, we found a class of 2D ferroelectric Rashba semiconductors PbX (X = S, Se, Te) with tunable spin-orbital properties. In this work, based on our previous tight-binding (TB) results, we derive an effective low-energy Hamiltonian around the symmetry points that captures the effects of strain on the electronic properties of PbX. We find that strains induce gauge fields which shift the Rashba point and modify the Rashba parameter. This effect is equivalent to the application of in-plane magnetic fields. The out-of-plane strain, which is proportional to the electric polarization, is also shown to modify the Rashba parameter. Overall, our theory connects strain and spin splitting in ferroelectric Rashba materials, which will be important to understand the strain-induced variations in local Rashba parameters that will occur in practical applications.

cond-mat.mtrl-sci↗

arXiv2017

Two-dimensional Square Buckled Rashba Lead Chalcogenides

We propose the lead sulphide (PbS) monolayer as a 2D semiconductor with a large Rashba-like spin-orbit effect controlled by the out-of-plane buckling. The buckled PbS conduction band is found to possess Rashba-like dispersion and spin texture at the $M$ and $Γ$ points, with large effective Rashba parameters of $λ\sim5~$eV$Å~$ and $λ\sim1~$eV$~Å$, respectively. Using a tight-binding formalism, we show that the Rashba effect originates from the very large spin-orbit interaction and the hopping term that mixes the in-plane and out-of-plane $p$ orbitals of Pb and S atoms. The latter, which depends on the buckling angle, can be controlled by applying strain to vary the spin texture as well as the Rashba parameter at $Γ$ and $M$. Our density functional theory results together with tight-binding formalism provide a unifying framework for designing Rashba monolayers and for manipulating their spin properties.

cond-mat.mtrl-sci↗

arXiv2017

Quantized transport, strain-induced perfectly conducting modes and valley filtering on shape-optimized graphene Corbino devices

The extreme mechanical resilience of graphene and the peculiar coupling it hosts between lattice and electronic degrees of freedom have spawned a strong impetus towards strain-engineered graphene where, on the one hand, strain augments the richness of its phenomenology and makes possible new concepts for electronic devices and, on the other hand, new and extreme physics might take place. Here, we demonstrate that the shape of substrates supporting graphene sheets can be optimized for approachable experiments where strain-induced pseudomagnetic fields (PMF) can be tailored by pressure for directionally selective electronic transmission and pinching-off of current flow down to the quantum channel limit. The Corbino-type layout explored here furthermore allows filtering of charge carriers according to valley and current direction, which can be used to inject or collect valley-polarized currents, thus realizing one of the basic elements required for valleytronics. Our results are based on a framework developed to realistically determine the combination of strain, external parameters, and geometry optimally compatible with the target spatial profile of a desired physical property --- the PMF in this case. Characteristic conductance profiles are analyzed through quantum transport calculations on large graphene devices having the optimal shape.

cond-mat.mes-hall↗

arXiv2017

Oxygen passivation mediated tunability of trion and excitons in MoS$_2$

Using wide spectral range in situ spectroscopic ellipsometry with systematic ultra high vacuum annealing and in situ exposure to oxygen, we report the complex dielectric function of MoS$_2$ isolating the environmental effects and revealing the crucial role of unpassivated and passivated sulphur vacancies. The spectral weights of the A ($1.92$ eV) and B ($2.02$ eV) exciton peaks in the dielectric function reduce significantly upon annealing, accompanied by spectral weight transfer in a broad energy range. Interestingly, the original spectral weights are recovered upon controlled oxygen exposure. This tunability of the excitonic effects is likely due to passivation and reemergence of the gap states in the bandstructure during oxygen adsorption and desorption, respectively, as indicated by ab initio density functional theory calculation results. This work unravels and emphasizes the important role of adsorbed oxygen in the optical spectra and many-body interactions of MoS$_2$.

cond-mat.mes-hall↗

arXiv2016

2D materials and van der Waals heterostructures

The physics of two-dimensional (2D) materials and heterostructures based on such crystals has been developing extremely fast. With new 2D materials, truly 2D physics has started to appear (e.g. absence of long-range order, 2D excitons, commensurate-incommensurate transition, etc). Novel heterostructure devices are also starting to appear - tunneling transistors, resonant tunneling diodes, light emitting diodes, etc. Composed from individual 2D crystals, such devices utilize the properties of those crystals to create functionalities that are not accessible to us in other heterostructures. We review the properties of novel 2D crystals and how their properties are used in new heterostructure devices.

cond-mat.mtrl-sci↗

arXiv2016

Strongly bound Mott-Wannier Excitons in GeS and GeSe monolayers

The excitonic spectra of single layer GeS and GeSe are predicted by ab initio GW-Bethe Salpeter equation calculations. G 0 W 0 calculations for the band structures find a fundamental band gap of 2.85 eV for GeS and 1.70 eV for GeSe monolayer. However, excitons are tightly bound, specially in GeS at the Γ point, where the quasi-particle interactions are so strong that they shift the Γ exciton peak energy into the visible range and below the off-Γ exciton peak. The lowest energy excitons in both materials are excited by light along the zigzag direction and have exciton binding energies of 1.05 eV and 0.4 eV, respectively, but despite the strong binding, the calculated binding energies are in agreement with a Mott-Wannier model.

cond-mat.mes-hall↗