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 segregation and microstructure in modern multi-component materials. Yet, the quantitative analysis typically relies on human expertise to define regions of interest. We introduce a computationally efficient, multi-stage machine learning strategy to identify compositionally 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)-Zr-Cu 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 composition and geometric analysis, detailed composition distribution and segregation effects relative to the predominant plate-like geometry can be readily mapped from the point cloud, without resorting to the voxel compositions.

Impact of metastable defect structures on carrier recombination in solar cells.

The efficiency of a solar cell is often limited by electron-hole recombination mediated by defect states within the band gap of the photovoltaic (PV) semiconductor. The Shockley-Read-Hall (SRH) model considers a static trap that can successively capture electrons and holes. In reality however, true trap levels vary with both the defect charge state and local structure. Here we consider the role of metastable structural configurations in capturing electrons and holes, taking the tellurium interstitial in CdTe as an illustrative example. Consideration of the defect dynamics, and symmetry-breaking, changes the qualitative behaviour and activates new pathways for carrier capture. Our results reveal the potential importance of metastable defect structures in non-radiative recombination, in particular for semiconductors with anharmonic/ionic-covalent bonding, multinary compositions, low crystal symmetries or highly-mobile defects.

Status and Direction of Atom Probe Analysis of Frozen Liquids.

Imaging of liquids and cryogenic biological materials by electron microscopy has been recently enabled by innovative approaches for specimen preparation and the fast development of optimized instruments for cryo-enabled electron microscopy (cryo-EM). Yet, cryo-EM typically lacks advanced analytical capabilities, in particular for light elements. With the development of protocols for frozen wet specimen preparation, atom probe tomography (APT) could advantageously complement insights gained by cryo-EM. Here, we report on different approaches that have been recently proposed to enable the analysis of relatively large volumes of frozen liquids from either a flat substrate or the fractured surface of a wire. Both allowed for analyzing water ice layers which are several micrometers thick consisting of pure water, pure heavy water, and aqueous solutions. We discuss the merits of both approaches and prospects for further developments in this area. Preliminary results raise numerous questions, in part concerning the physics underpinning field evaporation. We discuss these aspects and lay out some of the challenges regarding the APT analysis of frozen liquids.

Reflections on the Spatial Performance of Atom Probe Tomography in the Analysis of Atomic Neighborhoods.

Atom probe tomography (APT) is often introduced as providing "atomic-scale" mapping of the composition of materials and as such is often exploited to analyze atomic neighborhoods within a material. Yet quantifying the actual spatial performance of the technique in a general case remains challenging, as it depends on the material system being investigated as well as on the specimen's geometry. Here, by using comparisons with field-ion microscopy experiments, field-ion imaging and field evaporation simulations, we provide the basis for a critical reflection on the spatial performance of APT 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 neighborhoods, and directional neighborhood 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.

Segmentation of Static and Dynamic Atomic-Resolution Microscopy Data Sets with Unsupervised Machine Learning Using Local Symmetry Descriptors.

We present an unsupervised machine learning approach for segmentation of static and dynamic atomic-resolution microscopy data sets in the form of images and video sequences. In our approach, we first extract local features via symmetry operations. Subsequent dimension reduction and clustering analysis are performed in feature space to assign pattern labels to each pixel. Furthermore, we propose the stride and upsampling scheme as well as separability analysis to speed up the segmentation process of image sequences. We apply our approach to static atomic-resolution scanning transmission electron microscopy images and video sequences. Our code is released as a python module that can be used as a standalone program or as a plugin to other microscopy packages.

Atom probe tomography.

Atom probe tomography (APT) provides three-dimensional compositional mapping with sub-nanometre resolution. The sensitivity of APT is in the range of parts per million for all elements, including light elements such as hydrogen, carbon or lithium, enabling unique insights into the composition of performance-enhancing or lifetime-limiting microstructural features and making APT ideally suited to complement electron-based or X-ray-based microscopies and spectroscopies. Here, we provide an introductory overview of APT ranging from its inception as an evolution of field ion microscopy to the most recent developments in specimen preparation, including for nanomaterials. We touch on data reconstruction, analysis and various applications, including in the geosciences and the burgeoning biological sciences. We review the underpinnings of APT performance and discuss both strengths and limitations of APT, including how the community can improve on current shortcomings. Finally, we look forwards to true atomic-scale tomography with the ability to measure the isotopic identity and spatial coordinates of every atom in an ever wider range of materials through new specimen preparation routes, novel laser pulsing and detector technologies, and full interoperability with complementary microscopy techniques.

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.

Discovery of Elusive K4 O6 , a Compound Stabilized by Configurational Entropy of Polarons.

Synthesis of elusive K4 O6 has disclosed implications of crucial relevance for new solid materials discovery. K4 O6 forms in equilibrium from K2 O2 and KO2 , in an all-solid state, endothermic reaction at elevated temperature, undergoing back reaction upon cooling to ambient conditions. This tells that the compound is stabilized by entropy alone. Analyzing possible entropic contributions reveals that the configurational entropy of "localized" electrons, i.e., of polaronic quasi-particles, provides the essential contribution to the stabilization. We corroborate this assumption by measuring the relevant heats of transformation and tracking the origin of entropy of formation computationally. These findings challenge current experimental and computational approaches towards exploring chemical systems for new materials by searching the potential energy landscape: one would fail in detecting candidates that are crucially stabilized by the configurational entropy of localized polarons.

Negatively charged ions on Mg(0001) surfaces: appearance and origin of attractive adsorbate-adsorbate interactions.

Adsorption of electronegative elements on a metal surface usually leads to an increase in the work function and decrease in the binding energy as the adsorbate coverage rises. Using density-functional theory calculations, we show that Cl adsorbed on a Mg(0001) surface complies with these expectations, but adsorption of {N,O,F} causes a decrease in the work function and an increase in the binding energy. Analyzing the electronic structure, we show that the presence of a highly polarizable electron spill-out in front of Mg(0001) causes this unusual adsorption behavior and is responsible for the appearance of a hitherto unknown net-attractive lateral electrostatic interaction between same charged adsorbates.

Interfacial structure and chemistry of GaN on Ge(111).

The interface of GaN grown on Ge(111) by plasma-assisted molecular beam epitaxy is resolved by aberration corrected scanning transmission electron microscopy. A novel interfacial structure with a 5∶4 closely spaced atomic bilayer is observed that explains why the interface is flat, crystalline, and free of GeN(x). Density functional theory based total energy calculations show that the interface bilayer contains Ge and Ga atoms, with no N atoms. The 5∶4 bilayer at the interface has a lower energy than a direct stacking of GaN on Ge(111) and enables the 5∶4 lattice-matching growth of GaN.

Controlling polarization at insulating surfaces: quasiparticle calculations for molecules adsorbed on insulator films.

By means of quasiparticle-energy calculations in the G0W0 approach, we show for the prototypical insulator-semiconductor system NaCl/Ge(001) that polarization effects at the interfaces noticeably affect the excitation spectrum of molecules adsorbed on the surface of the NaCl films. The magnitude of the effect can be controlled by varying the thickness of the film, offering new opportunities for tuning electronic excitations in, e.g., molecular electronics or quantum transport. Polarization effects are visible even for the excitation spectrum of the NaCl films themselves, which has important implications for the interpretation of surface science experiments for the characterization of insulator surfaces.

Fully ab initio finite-size corrections for charged-defect supercell calculations.

In ab initio theory, defects are routinely modeled by supercells with periodic boundary conditions. Unfortunately, the supercell approximation introduces artificial interactions between charged defects. Despite numerous attempts, a general scheme to correct for these is not yet available. We propose a new and computationally efficient method that overcomes limitations of previous schemes and is based on a rigorous analysis of electrostatics in dielectric media. Its reliability and rapid convergence with respect to cell size is demonstrated for charged vacancies in diamond and GaAs.

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.