arXiv subjects

Nicola Marzari

Publications and source records attributed to Nicola Marzari.

At least 145 records · Page 8Linked to original sources

arXiv2021

Ab initio electron-phonon interactions in correlated electron systems

Electron-phonon ($e$-ph) interactions are pervasive in condensed matter, governing phenomena such as transport, superconductivity, charge-density waves, polarons and metal-insulator transitions. First-principles approaches enable accurate calculations of $e$-ph interactions in a wide range of solids. However, they remain an open challenge in correlated electron systems (CES), where density functional theory often fails to describe the ground state. Therefore reliable $e$-ph calculations remain out of reach for many transition metal oxides, high-temperature superconductors, Mott insulators, planetary materials and multiferroics. Here we show first-principles calculations of $e$-ph interactions in CES, using the framework of Hubbard-corrected density functional theory (DFT+$U$ ) and its linear response extension (DFPT+$U$), which can describe the electronic structure and lattice dynamics of many CES. We showcase the accuracy of this approach for a prototypical Mott system, CoO, carrying out a detailed investigation of its $e$-ph interactions and electron spectral functions. While standard DFPT gives unphysically divergent and short-ranged $e$-ph interactions, DFPT+$U$ is shown to remove the divergences and properly account for the long-range Fröhlich interaction, allowing us to model polaron effects in a Mott insulator. Our work establishes a broadly applicable and affordable approach for quantitative studies of e-ph interactions in CES, a novel theoretical tool to interpret experiments in this broad class of materials.

cond-mat.mtrl-sci↗

arXiv2021

Self-consistent Hubbard parameters from density-functional perturbation theory in the ultrasoft and projector-augmented wave formulations

The self-consistent evaluation of Hubbard parameters using linear-response theory is crucial for quantitatively predictive calculations based on Hubbard-corrected density-functional theory. Here, we extend a recently-introduced approach based on density-functional perturbation theory (DFPT) for the calculation of the on-site Hubbard $U$ to also compute the inter-site Hubbard $V$. DFPT allows to reduce significantly computational costs, improve numerical accuracy, and fully automate the calculation of the Hubbard parameters by recasting the linear response of a localized perturbation into an array of monochromatic perturbations that can be calculated in the primitive cell. In addition, here we generalize the entire formalism from norm-conserving to ultrasoft and projector-augmented wave formulations, and to metallic ground states. After benchmarking DFPT against the conventional real-space Hubbard linear response in a supercell, we demonstrate the effectiveness of the present extended Hubbard formulation in determining the equilibrium crystal structure of Li$_x$MnPO$_4$ (x=0,1) and the subtle energetics of Li intercalation.

cond-mat.mtrl-sci↗

arXiv2020

Prediction of phonon-mediated superconductivity with high critical temperature in the two-dimensional topological semimetal W2N3

Two-dimensional superconductors attract great interest both for their fundamental physics and for their potential applications, especially in the rapidly growing field of quantum computing. Despite intense theoretical and experimental efforts, materials with a reasonably high transition temperature are still rare. Even more rare are those that combine superconductivity with a non-trivial band topology, to potentially host exotic states of matter such as Majorana fermions. Here, we predict a remarkably high superconducting critical temperature of 21-28 K in the easily exfoliable, topologically non-trivial 2D semimetal W2N3 . By studying its electronic and superconducting properties as a function of doping and strain, we find large changes in the electron-phonon interactions that make this material a unique platform to study different coupling regimes and test the limits of current theories of superconductivity. Last, we discuss the possibility of tuning the material to achieve coexistence of superconductivity and topologically non-trivial edge states.

cond-mat.supr-con↗

arXiv2020

Highly Active Nanoperovskite Catalysts for Oxygen Evolution Reaction: Insights into Activity and Stability of Ba0.5Sr0.5Co0.8Fe0.2O3 and PrBaCo2O6

It is shown that producing PrBaCo2O5 and Ba0.5Sr0.5Co0.8Fe0.2O3 nanoparticle by a scalable synthesis method leads to high mass activities for the oxygen evolution reaction with outstanding improvements by 10 and 50 times, respectively, compared to those prepared via the state of the art synthesis method. Here, detailed comparisons at both laboratory and industrial scales show that Ba0.5Sr0.5Co0.8Fe0.2O3 appears to be the most active and stable perovskite catalyst under alkaline conditions, while PrBaCo2O6 reveals thermodynamic instability described by the density functional theory based Pourbaix diagrams highlighting cation dissolution under oxygen evolution conditions. Operando Xray absorption spectroscopy is used in parallel to monitor electronic and structural changes of the catalysts during oxygen evolution reaction. The exceptional BSCF functional stability can be correlated to its thermodynamic metastability under oxygen evolution conditions as highlighted by Pourbaix diagram analysis. BSCF is able to dynamically self reconstruct its surface, leading to formation of Co based oxyhydroxide layers while retaining its structural stability. Differently, PBCO demonstrates a high initial oxygen evolution reaction activity while it undergoes a degradation process considering its thermodynamic instability under oxygen evolution conditions as anticipated by its Pourbaix diagram. Overall, this work demonstrates a synergetic approach of using both experimental and theoretical studies to understand the behavior of perovskite catalysts.

cond-mat.mtrl-sci↗

arXiv2020

Ab initio simulation of band-to-band tunneling FETs with single- and few-layer 2-D materials as channels

Full-band atomistic quantum transport simulations based on first principles are employed to assess the potential of band-to-band tunneling FETs (TFETs) with a 2-D channel material as future electronic circuit components. We demonstrate that single-layer (SL) transition metal dichalcogenides are not well suited for TFET applications. There might, however, exist a great variety of 2-D semiconductors that have not even been exfoliated yet; this paper pinpoints some of the most promising candidates among them to realize highly efficient TFETs. SL SnTe, As, TiNBr, and Bi are all found to ideally deliver ON-currents larger than 100μA/μm at 0.5-V supply voltage and 0.1 nA/μm OFF-current value. We show that going from single to multiple layers can boost the TFET performance as long as the gain from a narrowing bandgap exceeds the loss from the deteriorating gate control. Finally, a 2-D van der Waals heterojunction TFET is revealed to perform almost as well as the best SL homojunction, paving the way for research in optimal 2-D material combinations.

cond-mat.mes-hall↗

arXiv2020

Shear and breathing modes of layered materials

Layered materials (LMs), such as graphite, hexagonal boron nitride, and transition-metal dichalcogenides, are at the centre of an ever increasing research effort, due to their scientific and technological relevance. Raman and infrared spectroscopies are accurate, non-destructive, approaches to determine a wide range of properties, including the number of layers and the strength of the interlayer interactions. Here, we present a general approach to predict the complete spectroscopic fan diagrams, i.e., the relations between frequencies and number of layers, $N$, for the optically-active shear and layer-breathing modes of any multilayer comprising $N \geq 2$ identical layers. In order to achieve this, we combine a description of the normal modes in terms of a one-dimensional mechanical model, with symmetry arguments that describe the evolution of the point group as a function of $N$. Group theory is then used to identify which modes are Raman and/or infrared active, and to provide diagrams of the optically-active modes for any stack composed of identical layers. We implement the method and algorithms in an open-source tool directly available on the Materials Cloud portal, to assist any researcher in the prediction and interpretation of such diagrams. Our work will underpin all future efforts on Raman and Infrared characterization of known, and yet not investigated, LMs.

cond-mat.mtrl-sci↗

arXiv2020

Thermomechanical properties of honeycomb lattices from internal-coordinates potentials: the case of graphene and hexagonal boron nitride

Lattice dynamics in low-dimensional materials and, in particular, the quadratic behaviour of the flexural acoustic modes play a fundamental role in their thermomechanical properties. A first-principles evaluation of these can be very demanding, and can be affected by numerical noise that breaks translational or rotational invariance. In order to overcome these challenges, we study the Gartstein internal-coordinate potential and tune its 13 parameters on the first-principles interatomic force constants for graphene. We show that the resulting potential not only reproduces very well the phonon dispersions of graphene, but also those of carbon nanotubes of any diameter and chirality. The addition of a cubic term allows also to reproduce the dominant anharmonic terms, leading to a very good estimate of the lattice thermal conductivity. Finally, this potential form works very well also for boron nitride, provided it is fitted on the short-range (analytical) part of the interatomic force constants, and augmented thereafter with the long-range dielectric contribution. This consideration underscores how potentials based on short-ranged descriptors should be fit, in polar materials, to the short-range part of the first-principles interactions, and complemented by long-range analytical dielectric models parametrized on the same first-principles calculations.

cond-mat.mtrl-sci↗

arXiv2020

Electrolytes for Li-ion all-solid-state batteries: a first-principles comparative study of Li10GeP2O12 and Li10GeP2S12 in the LISICON and LGPS phases

In this work we address Li-ion diffusion in thio-LISICON materials and in their oxide counterparts, exploring both the orthorhombic and tetragonal phases of Li10GeP2S12(LGPS) and Li10GeP2O12(LGPO) through extended Car-Parrinello molecular dynamics in the canonical and isobaric-isothermal ensemble. The (quasi-)orthorhombic and tetragonal phases are studied both for the oxide and for the sulfide, with the aim of comparing their conductivity with the same approach; out of these four case studies, tetragonal LGPO has not been reported and, while dynamically stable, it sits (0.04 Ha/formula unit) above orthorhombic LGPO. We calculate activation energies for diffusion of 0.18 eV and 0.23 eV for tetragonal and orthorhombic LGPS, and of 0.22 eV and 0.34eV for tetragonal and orthorhombic LGPO. In line with experiments, we find orthorhombic LGPO orders of magnitude less conductive, at room temperature, than the two sulfide systems. However, this is not the case for tetragonal LGPO, which, although less stable than its orthorhombic allotrope, shows at room temperature a conductivity comparable to orthorhombic and tetragonal LGPS, and, if synthesized, could make a very attractive Li-ion conductor.

cond-mat.mtrl-sci↗

arXiv2020

AiiDAlab -- an ecosystem for developing, executing, and sharing scientific workflows

Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited experience in (and time for) user interface design, which can make research software difficult to install and use for novices. When combined with the increasing complexity of scientific workflows (involving many steps and software packages), setting up a computational research environment becomes a major entry barrier. AiiDAlab is a web platform that enables computational scientists to package scientific workflows and computational environments and share them with their collaborators and peers. By leveraging the AiiDA workflow manager and its plugin ecosystem, developers get access to a growing range of simulation codes through a python API, coupled with automatic provenance tracking of simulations for full reproducibility. Computational workflows can be bundled together with user-friendly graphical interfaces and made available through the AiiDAlab app store. Being fully compatible with open-science principles, AiiDAlab provides a complete infrastructure for automated workflows and provenance tracking, where incorporating new capabilities becomes intuitive, requiring only Python knowledge.

cond-mat.mtrl-sci↗

arXiv2020

Electronic structure of pristine and Ni-substituted LaFeO$_3$ from near edge x-ray absorption fine structure experiments and first-principles simulations

We present a joint theoretical and experimental study of the oxygen $K$-edge spectra for LaFeO$_3$ and homovalent Ni-substituted LaFeO$_3$ (LaFe$_{0.75}$Ni$_{0.25}$O$_3$), using first-principles simulations based on density-functional theory with extended Hubbard functionals and x-ray absorption near edge structure (XANES) measurements. Ground-state and excited-state XANES calculations employ Hubbard on-site $U$ and inter-site $V$ parameters determined from first principles and the Lanczos recursive method to obtain absorption cross sections, which allows for a reliable description of XANES spectra in transition-metal compounds in a very broad energy range, with an accuracy comparable to that of hybrid functionals but at a substantially lower cost. We show that standard gradient-corrected exchange-correlation functionals fail in capturing accurately the electronic properties of both materials. In particular, for LaFe$_{0.75}$Ni$_{0.25}$O$_3$ they do not reproduce its semiconducting behaviour and provide a poor description of the pre-edge features at the O $K$ edge. The inclusion of Hubbard interactions leads to a drastic improvement, accounting for the semiconducting ground state of LaFe$_{0.75}$Ni$_{0.25}$O$_3$ and for a good agreement between calculated and measured XANES spectra. We show that the partial substitution of Fe for Ni affects the conduction-band bottom by generating a strongly hybridized O($2p$)-Ni($3d$) minority-spin empty electronic state. The present work, based on a consistent correction of self-interaction errors, outlines the crucial role of extended Hubbard functionals to describe the electronic structure of complex transition-metal oxides such as LaFeO$_3$ and LaFe$_{0.75}$Ni$_{0.25}$O$_3$ and paves the way to future studies on similar systems.

cond-mat.str-el↗

arXiv2020

Profiling novel high-conductivity 2D semiconductors

When complex mechanisms are involved, pinpointing high-performance materials within large databases is a major challenge in materials discovery. We focus here on phonon-limited conductivities, and study 2D semiconductors doped by field effects. Using state-of-the-art density-functional perturbation theory and Boltzmann transport equation, we discuss 11 monolayers with outstanding transport properties. These materials are selected from a computational database of exfoliable materials providing monolayers that are dynamically stable and that do not have more than 6 atoms per unit cell. We first analyse electron-phonon scattering in two well-known systems: electron-doped InSe and hole-doped phosphorene. Both are single-valley systems with weak electron-phonon interactions, but they represent two distinct pathways to fast transport: a steep and deep isotropic valley for the former and strongly anisotropic electron-phonon physics for the latter. We identify similar features in the database and compute the conductivities of the relevant monolayers. This process yields several high-conductivity materials, some of them only very recently emerging in the literature (GaSe, Bi$_2$SeTe$_2$, Bi$_2$Se$_3$, Sb$_2$SeTe$_2$), others never discussed in this context (AlLiTe$_2$, BiClTe, ClGaTe, AuI). Comparing these 11 monolayers in detail, we discuss how the strength and angular dependency of the electron-phonon scattering drives key differences in the transport performance of materials despite similar valley structure. We also discuss the high conductivity of hole-doped WSe$_2$, and how this case study shows the limitations of a selection process that would be based on band properties alone.

cond-mat.mtrl-sci↗

arXiv2020

Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

We search for novel two-dimensional materials that can be easily exfoliated from their parent compounds. Starting from 108423 unique, experimentally known three-dimensional compounds we identify a subset of 5619 that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van-der-Waals density-functional theory, validated against experimental structural data and calculated random-phase-approximation binding energies, allow to identify 1825 compounds that are either easily or potentially exfoliable, including all that are commonly exfoliated experimentally. In particular, the subset of 1036 easily exfoliable cases---layered materials held together mostly by dispersion interactions and with binding energies up to $30-35$ meV$\cdot\textÅ^{-2}$---provides a wealth of novel structural prototypes and simple ternary compounds, and a large portfolio to search materials for optimal properties. For the 258 compounds with up to 6 atoms per primitive cell we comprehensively explore vibrational, electronic, magnetic, and topological properties, identifying in particular 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors.

cond-mat.mtrl-sci↗

arXiv2020

Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows

Over the last two decades, the field of computational science has seen a dramatic shift towards incorporating high-throughput computation and big-data analysis as fundamental pillars of the scientific discovery process. This has necessitated the development of tools and techniques to deal with the generation, storage and processing of large amounts of data. In this work we present an in-depth look at the workflow engine powering AiiDA, a widely adopted, highly flexible and database-backed informatics infrastructure with an emphasis on data reproducibility. We detail many of the design choices that were made which were informed by several important goals: the ability to scale from running on individual laptops up to high-performance supercomputers, managing jobs with runtimes spanning from fractions of a second to weeks and scaling up to thousands of jobs concurrently, and all this while maximising robustness. In short, AiiDA aims to be a Swiss army knife for high-throughput computational science. As well as the architecture, we outline important API design choices made to give workflow writers a great deal of liberty whilst guiding them towards writing robust and modular workflows, ultimately enabling them to encode their scientific knowledge to the benefit of the wider scientific community.

cs.DC↗

arXiv2020

Automated high-throughput Wannierisation

Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high-throughput (HT) computational materials design is an emergent field that promises to accelerate the reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method (SCDM) and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space. We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations. Finally, we provide a downloadable virtual machine that can be used to reproduce the results of this paper, including all first-principles and atomistic simulations as well as the computational workflows.

physics.comp-ph↗

arXiv2020

Equipartition of Energy Defines the Size-Thickness Relationship in Liquid-Exfoliated Nanosheets

Liquid phase exfoliation is a commonly used method to produce 2D nanosheets from a range of layered crystals. However, such nanosheets display broad size and thickness distributions and correlations between area and thickness, issues that limit nanosheet application potential. To understand the factors controlling the exfoliation process, we have liquid-exfoliated 11 different layered materials, size-selecting each into fractions before using AFM to measure the nanosheet length, width, and thickness distributions for each fraction. The resultant data show a clear power-law scaling of nanosheet area with thickness for each material. We have developed a simple nonequilibrium thermodynamics-based model predicting that the power-law prefactor is proportional to both the ratios of in-plane-tearing/out-of-plane-peeling energies and in-plane/out-of-plane moduli. By comparing the experimental data with the modulus ratio calculated from first-principles, we find close agreement between experiment and theory. This supports our hypothesis that energy equipartition holds between nanosheet tearing and peeling during sonication-assisted exfoliation.

physics.chem-ph↗

arXiv2020

2-D materials for ultra-scaled field-effect transistors: hundred candidates under the ab initio microscope

Thanks to their unique properties single-layer 2-D materials appear as excellent candidates to extend Moore's scaling law beyond the currently manufactured silicon FinFETs. However, the known 2-D semiconducting components, essentially transition metal dichalcogenides, are still far from delivering the expected performance. Based on a recent theoretical study that predicts the existence of more than 1,800 exfoliable 2-D materials, we investigate here the 100 most promising contenders for logic applications. Their "current vs. voltage" characteristics are simulated from first-principles, combining density-functional theory and advanced quantum transport calculations. Both n- and p-type configurations are considered, with gate lengths ranging from 15 down to 5 nm. From this unprecedented collection of electronic materials, we identify 13 compounds with electron and hole currents potentially much higher than in future Si FinFETs. The resulting database widely expands the design space of 2-D transistors and provides original guidelines to the materials and device engineering community.

cond-mat.mes-hall↗

arXiv2020

Materials Cloud, a platform for open computational science

Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts 1) archival and dissemination services for raw and curated data, together with their provenance graph, 2) modelling services and virtual machines, 3) tools for data analytics, and pre-/post-processing, and 4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of the FAIR principles that extends to computational workflows. Materials Cloud leverages the AiiDA framework to record the provenance of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow to retrace and reproduce any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain.

cond-mat.mtrl-sci↗

arXiv2020

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (http://www.aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with any simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.

cs.DC↗