Ab initio Description of Bond-Breaking in Large Electric Fields

Strong ($10^{10}$ V/m) electric fields capable of inducing atomic bond-breaking represent a powerful tool for surface chemistry. However, their exact effects are difficult to predict due to a lack of suitable tools to probe their associated atomic-scale mechanisms. Here we introduce a generalized dipole correction for charged repeated-slab models that controls the electric field on both sides of the slab, thereby enabling direct theoretical treatment of field-induced bond-breaking events. As a prototype application, we consider field evaporation from a kinked W surface. We reveal two qualitatively different desorption mechanisms that can be selected by the magnitude of the applied field

Stability of charged sulfur vacancies in 2D and bulk MoS2_2 from plane-wave density functional theory with electrostatic corrections

Two-dimensional (2D) semiconducting transition metal dichalcogenides such as MoS$_2$ have attracted extensive research interests for potential applications in optoelectronics, spintronics, photovoltaics, and catalysis. To harness the potential of these materials for electronic devices requires a better understanding of how defects control the carrier concentration, character, and mobility. Utilizing a correction scheme developed by Freysoldt and Neugebauer to ensure the appropriate electrostatic boundary conditions for charged defects in 2D materials, we perform density functional theory calculations to compute formation energies and charge transition levels associated with sulfur vacancies in monolayer and layered bulk MoS$_2$. We investigate the convergence of these defect properties with respect to vacuum spacing, in-plane supercell dimensions, and different levels of theory. We also analyze the electronic structures of the defects in different charge states to gain insights into the effect of defects on bonding and magnetism. We predict that both vacancy structures undergo a Jahn-Teller distortion, which helps stabilize the sulfur vacancy in the $-1$ charged state.Comment: 10 pages, 6 figures. Submitted to Physical Review Materials journa

Ultrathin oxides: bulk-oxide-like model surfaces or unique films?

To better understand the electronic and chemical properties of wide-gap oxide surfaces at the atomic scale, experimental work has focused on epitaxial films on metal substrates. Recent findings show that these films are considerably thinner than previously thought. This raises doubts about the transferability of the results to surface properties of thicker films and bulk crystals. By means of density-functional theory and approximate GW corrections for the electronic spectra we demonstrate for three characteristic wide-gap oxides (silica, alumina, and hafnia) the influence of the substrate and highlight critical differences between the ultrathin films and surfaces of bulk materials. Our results imply that monolayer-thin oxide films have rather unique properties.Comment: 5 pages, 3 figures, accepted by PR

Ab initio vibrational free energies including anharmonicity for multicomponent alloys

A density-functional-theory based approach to efficiently compute numerically exact vibrational free energies - including anharmonicity - for chemically complex multicomponent alloys is developed. It is based on a combination of thermodynamic integration and a machine-learning potential. We demonstrate the performance of the approach by computing the anharmonic free energy of the prototypical five-component VNbMoTaW refractory high entropy alloy

Understanding atom probe's analytical performance for iron oxides using correlation histograms and ab initio calculations

Field evaporation from ionic or covalently bonded materials often leads to the emission of molecular ions. The metastability of these molecular ions, particularly under the influence of the intense electrostatic field (1010 Vm-1), makes them prone to dissociation with or without an exchange of energy amongst them. These processes can affect the analytical performance of atom probe tomography (APT). For instance, neutral species formed through dissociation may not be detected at all or with a time of flight no longer related to their mass, causing their loss from the analysis. Here, we evaluated the changes in the measured composition of FeO, Fe2O3 and Fe3O4 across a wide range of analysis conditions. Possible dissociation reactions are predicted by density-functional theory (DFT) calculations considering the spin states of the molecules. The energetically favoured reactions are traced on to the multi-hit ion correlation histograms, to confirm their existence within experiments, using an automated Python-based routine. The detected reactions are carefully analysed to reflect upon the influence of these neutrals from dissociation reactions on the performance of APT for analysing iron oxides

Reflections on the spatial performance of atom probe tomography in the analysis of atomic neighbourhoods

Atom probe tomography is often introduced as providing "atomic-scale" mapping of the composition of materials and as such is often exploited to analyse atomic neighbourhoods within a material. Yet quantifying the actual spatial performance of the technique in a general case remains challenging, as they depend on the material system being investigated as well as on the specimen's geometry. Here, by using comparisons with field-ion microscopy experiments and field-ion imaging and field evaporation simulations, we provide the basis for a critical reflection on the spatial performance of atom probe tomography in the analysis of pure metals, low alloyed systems and concentrated solid solutions (i.e. akin to high-entropy alloys). The spatial resolution imposes strong limitations on the possible interpretation of measured atomic neighbourhoods, and directional neighbourhood analyses restricted to the depth are expected to be more robust. We hope this work gets the community to reflect on its practices, in the same way, it got us to reflect on our work.Comment: Submitted to Microscopy & Microanalysis to be part of the special issue assocaited to the APT&M 2020 conferenc

A machine learning framework for quantifying chemical segregation and microstructural features in atom probe tomography data

Atom probe tomography (APT) is ideally suited to characterize and understand the interplay of chemical segregation and microstructure in modern multicomponent materials. Yet, the quantitative analysis typically relies on human expertise to define regions of interest. We introduce a computationally efficient, multistage machine learning strategy to identify chemically distinct domains in a semi automated way, and subsequently quantify their geometric and compositional characteristics. In our algorithmic pipeline, we first coarse grain the APT data into voxels, collect the composition statistics, and decompose it via clustering in composition space. The composition classification then enables the real space segmentation via a density based clustering algorithm, thus revealing the microstructure at voxel resolution. Our approach is demonstrated for a Sm(Co,Fe)ZrCu alloy. The alloy exhibits two precipitate phases with a plate-like, but intertwined morphology. The primary segmentation is further refined to disentangle these geometrically complex precipitates into individual plate like parts by an unsupervised approach based on principle component analysis, or a U-Net based semantic segmentation trained on the former. Following the chemical and geometric analysis, detailed chemical distribution and segregation effects relative to the predominant plate-like geometry can be readily mapped without resorting to the initial voxelization

Revealing atomic-scale vacancy-solute interaction in nickel

Imaging individual vacancies in solids and revealing their interactions with solute atoms remains one of the frontiers in microscopy and microanalysis. Here we study a creep-deformed binary Ni-2 at.% Ta alloy. Atom probe tomography reveals a random distribution of Ta. Field ion microscopy, with contrast interpretation supported by density-functional theory and time-of-flight mass spectrometry, evidences a positive correlation of tantalum with vacancies. Our results support solute-vacancy binding, which explains improvement in creep resistance of Ta-containing Ni-based superalloys and helps guide future material design strategies.Comment: Submitted to Physics Review Lette

Dielectric anisotropy in the GW space-time method

Excited-state calculations, notably for quasiparticle band structures, are nowadays routinely performed within the GW approximation for the electronic self-energy. Nevertheless, certain numerical approximations and simplifications are still employed in practice to make the computations feasible. An important aspect for periodic systems is the proper treatment of the singularity of the screened Coulomb interaction in reciprocal space, which results from the slow 1/r decay in real space. This must be done without introducing artificial interactions between the quasiparticles and their periodic images in repeated cells, which occur when integrals of the screened Coulomb interaction are discretised in reciprocal space. An adequate treatment of both aspects is crucial for a numerically stable computation of the self-energy. In this article we build on existing schemes for isotropic screening and present an extension for anisotropic systems. We also show how the contributions to the dielectric function arising from the non-local part of the pseudopotentials can be computed efficiently. These improvements are crucial for obtaining a fast convergence with respect to the number of points used for the Brillouin zone integration and prove to be essential to make GW calculations for strongly anisotropic systems, such as slabs or multilayers, efficient. (C) 2006 Elsevier B.V. All rights reserved

Advances in Density-Functional Calculations for Materials Modeling

During the past two decades, density-functional (DF) theory has evolved from niche applications for simple solid-state materials to become a workhorse method for studying a wide range of phenomena in a variety of system classes throughout physics, chemistry, biology, and materials science. Here, we review the recent advances in DF calculations for materials modeling, giving a classification of modern DF-based methods when viewed from the materials modeling perspective. While progress has been very substantial, many challenges remain on the way to achieving consensus on a set of universally applicable DF-based methods for materials modeling. Hence, we focus on recent successes and remaining challenges in DF calculations for modeling hard solids, molecular and biological matter, low-dimensional materials, and hybrid organic-inorganic materials