Spatial distribution maps for atom probe tomography

Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography

Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix to form particular atomic neighbourhoods. CSRO is typically characterized indirectly, using volume-averaged or through projection microscopy techniques that fail to capture the three-dimensional atomistic architectures. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography enabling three-dimensional imaging of multiple CSROs. We showcase our approach by addressing a long-standing question encountered in body-centred-cubic Fe-Al alloys that see anomalous property changes upon heat treatment. We use it to evidence non-statistical B2-CSRO instead of the generally-expected D03-CSRO. We introduce quantitative correlations among annealing temperature, CSRO, and nano-hardness and electrical resistivity. Our approach is further validated on modified D03-CSRO detected in Fe-Ga. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in different materials and help design future high-performance materials.

Characterising the performance of an ultrawide field-of-view 3D atom probe

The CAMECA Invizo 6000 atom probe microscope uses ion optics that differ significantly from the local electrode atom probe (LEAP). It uses dual antiparallel deep ultraviolet lasers, a flat counter electrode, and a series of accelerating and decelerating lenses to increase the field-of-view of the specimen without reducing the mass resolving power. In this work we characterise the performance of the Invizo 6000 using three material case studies: a model Al-Mg-Si alloy, a commercially-available Ni-based superalloy, and a Zr alloy, using a combination of air and vacuum-transfer between instruments. The ion optics of the Invizo 6000 significantly increase the field-of-view compared to the same specimen on a LEAP 4000 X Si. We also observe a significant increase in specimen yield, especially for the Zr alloy. These results combine to make the Invizo 6000 well-suited to research projects requiring large analysis volumes, particularly so for traditionally difficult samples such as oxides.

Grain Boundary Plane Measurement Using Transmission Electron Microscopy Automated Crystallographic Orientation Mapping for Atom Probe Tomography Specimens

Grain boundaries are critical in determining the properties of materials, including mechanical stability, conductivity, and corrosion resistance. The specific properties of materials depend not only on the misorientation of the crystals, the three most commonly characterized parameters, but also on the angle of the grain boundary plane between the two crystals, the final two parameters in the five-parameter macroscopic description of the grain boundary. The method presented here allows for the direct measurement of all five parameters of the grain boundary in a transmission electron microscopy specimen of various morphologies. This is especially applicable to atom probe specimens, where only a single-tilt axis is generally available, allowing the crystallographic description to be matched to the detailed chemical data available in the atom probe tomography. This method provides a platform for efficient grain boundary analysis in unique samples, saving operator time and allowing for ease of acquisition and interpretation in comparison with traditional electron diffraction methods.

Atomic-scale 3D imaging of individual dopant atoms in an oxide semiconductor

The physical properties of semiconductors are controlled by chemical doping. In oxide semiconductors, small variations in the density of dopant atoms can completely change the local electric and magnetic responses caused by their strongly correlated electrons. In lightly doped systems, however, such variations are difficult to determine as quantitative 3D imaging of individual dopant atoms is a major challenge. We apply atom probe tomography to resolve the atomic sites that donors occupy in the small band gap semiconductor Er(Mn,Ti)O₃ with a nominal Ti concentration of 0.04 at. %, map their 3D lattice positions, and quantify spatial variations. Our work enables atomic-level 3D studies of structure-property relations in lightly doped complex oxides, which is crucial to understand and control emergent dopant-driven quantum phenomena.

Small variations in the density of dopants change the physical properties of complex oxides. Here, the authors resolve doping levels in three dimension, imaging the atomic sites that donors occupy in the small band gap semiconductor Er(Mn,Ti)O₃.

3D Nanoscale Mapping of Short-Range Order in GeSn Alloys

GeSn on Si has attracted much research interest due to its tunable direct bandgap for mid-infrared applications. Recently, short-range order (SRO) in GeSn alloys has been theoretically predicted, which profoundly impacts the band structure. However, characterizing SRO in GeSn is challenging. Guided by physics-informed Poisson statistical analyses of k-nearest neighbors (KNN) in atom probe tomography (APT), a new approach is demonstrated here for 3D nanoscale SRO mapping and semi-quantitative strain mapping in GeSn. For GeSn with ≈14 at. % Sn, the SRO parameters of Sn-Sn 1NN in 10 × 10 × 10 nm³ nanocubes can deviate from that of the random alloys by ±15 %. The relatively large fluctuation of the SRO parameters contributes to band-edge softening observed optically. Sn-Sn 1NN also tends to be more favored toward the surface, less favored under strain relaxation or tensile strain, while almost independent of local Sn composition. An algorithm based on least square fit of atomic positions further verifies this Poisson-KNN statistical method. Compared to existing macroscopic spectroscopy or electron microscopy techniques, this new APT statistical analysis uniquely offers 3D SRO mapping at nanoscale resolution in a relatively large volume with millions of atoms. It can also be extended to investigate SRO in other alloy systems.

A Bottom-Up Volume Reconstruction Method for Atom Probe Tomography

This paper describes a reconstruction method for atom probe tomography based on a bottom-up approach accounting for (i) the final tip morphology (which is frequently induced by inhomogeneous evaporation probabilities across the tip surface due to laser absorption, heat diffusion effects, and inhomogeneous material properties), (ii) the limited (and changing) field of view, and (iii) the detector efficiency. The reconstruction starts from the final tip morphology and reverses the evaporation sequence through the pseudo-deposition of defined small reconstruction volumes, which are then stacked together to create the full three-dimensional (3D) tip. The subdivision in small reconstruction volumes allows the scheme to account for the changing tip shape and field of view as evaporation proceeds. Atoms within the same small reconstruction volume are reconstructed at once by placing atoms back onto their possible lattice sites through a trajectory-matching process involving simulated and experimental hit maps. As the ejected ion trajectories are simulated using detailed electrostatic modeling inside the chamber, no simplifications have been imposed on the shape of the trajectories, projection laws, or tip surface. We demonstrate the superior performance of our approach over the conventional reconstruction method (Bas) for an asymmetrical tip shape.

A Modular Atom Probe Concept: Design, Operational Aspects, and Performance of an Integrated APT-FIB/SEM Solution

Atomic probe tomography (APT) is able to generate three-dimensional chemical maps in atomic resolution. The required instruments for APT have evolved over the last 20 years from an experimental to an established method of materials analysis. Here, we describe the realization of a new modular instrument concept that allows the direct attachment of APT to a dual-beam SEM microscope with the main achievement of fast and direct sample transfer and high flexibility in chamber and component configuration. New operational modes are enabled regarding sample geometry, alignment of tips, and the microelectrode. The instrument is optimized to handle cryo-samples at all stages of preparation and storage. It comes with its own software for evaluation and reconstruction. The performance in terms of mass resolution, aperture angle, and detection efficiency is demonstrated with a few application examples.

Open and strong-scaling tools for atom-probe crystallography: high-throughput methods for indexing crystal structure and orientation

Volumetric crystal structure indexing and orientation mapping are key data processing steps for virtually any quantitative study of spatial correlations between the local chemical composition features and the microstructure of a material. For electron and X-ray diffraction methods it is possible to develop indexing tools which compare measured and analytically computed patterns to decode the structure and relative orientation within local regions of interest. Consequently, a number of numerically efficient and automated software tools exist to solve the above characterization tasks. For atom-probe tomography (APT) experiments, however, the strategy of making comparisons between measured and analytically computed patterns is less robust because many APT data sets contain substantial noise. Given that sufficiently general predictive models for such noise remain elusive, crystallography tools for APT face several limitations: their robustness to noise is limited, and therefore so too is their capability to identify and distinguish different crystal structures and orientations. In addition, the tools are sequential and demand substantial manual interaction. In combination, this makes robust uncertainty quantification with automated high-throughput studies of the latent crystallographic information a difficult task with APT data. To improve the situation, the existing methods are reviewed and how they link to the methods currently used by the electron and X-ray diffraction communities is discussed. As a result of this, some of the APT methods are modified to yield more robust descriptors of the atomic arrangement. Also reported is how this enables the development of an open-source software tool for strong scaling and automated identification of a crystal structure, and the mapping of crystal orientation in nanocrystalline APT data sets with multiple phases.

Development of Wide Field of View Three-Dimensional Field Ion Microscopy and High-Fidelity Reconstruction Algorithms to the Study of Defects in Nuclear Materials

This article presents a fast and highly efficient algorithm developed to reconstruct a three-dimensional (3D) volume with a high spatial precision from a set of field ion microscopy (FIM) images, and specific tools developed to characterize crystallographic lattice and defects. A set of FIM digital images and image processing algorithms allow the construction of a 3D reconstruction of the sample at the atomic scale. The capability of the 3D FIM to resolve the crystallographic lattice and the finest defects in metals opens a new way to analyze materials. This spatial precision was quantified on tungsten, analyzed at different analyzing conditions. A specific data mining tool, based on Fourier transforms, was also developed to characterize lattice distortions in the reconstructed volumes. This tool has been used in simulated and experimental volumes to successfully locate and characterize defects such as dislocations and grain boundaries.

Alpha Shape Analysis (ASA) Framework for Post- Clustering Property Determination in Atom Probe Tomographic Data

While application of clustering algorithms to atom probe tomography data have enabled quantification of solute clusters in terms of number density, size, and subcomposition there exist other properties (e.g., volume, surface area, and composition) that are better determined by defining an interface between the cluster and the surrounding matrix. The limitation in composition results from an ion selection step where the expected matrix ion types are omitted from the cluster search algorithm to enhance the contrast between the matrix and cluster and to reduce the complexity of the search. Previously, composition determination within solute clusters has utilized a secondary envelopment and erosion step on top of conventional methods such as maximum separation. In this work, we present a novel stochastic method that combines the particle identification fidelity of a conventional clustering algorithm with the analytical flexibility of mesh-based approaches through the generation of alpha shapes for each identified cluster. The corresponding mesh accounts for concave components of the clusters and determines the volume and surface area of the clusters; additionally, the mesh boundary is utilized to update the total composition according to the internal ions.

Integrative Atom Probe Tomography Using Scanning Transmission Electron Microscopy-Centric Atom Placement as a Step Toward Atomic-Scale Tomography

Current reconstruction methodologies for atom probe tomography (APT) contain serious geometric artifacts that are difficult to address due to their reliance on empirical factors to generate a reconstructed volume. To overcome this limitation, a reconstruction technique is demonstrated where the analyzed volume is instead defined by the specimen geometry and crystal structure as determined by transmission electron microscopy (TEM) and diffraction acquired before and after APT analysis. APT data are reconstructed using a bottom-up approach, where the post-APT TEM image is used to define the substrate upon which APT detection events are placed. Transmission electron diffraction enables the quantification of the relationship between atomic positions and the evaporated specimen volume. Using an example dataset of ZnMgO:Ga grown epitaxially on c-plane sapphire, a volume is reconstructed that has the correct geometry and atomic spacings in 3D. APT data are thus reconstructed in 3D without using empirical parameters for the reverse projection reconstruction algorithm.

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.

Nanoscale light element identification using machine learning aided STEM-EDS

Light element identification is necessary in materials research to obtain detailed insight into various material properties. However, reported techniques, such as scanning transmission electron microscopy (STEM)-energy dispersive X-ray spectroscopy (EDS) have inadequate detection limits, which impairs identification. In this study, we achieved light element identification with nanoscale spatial resolution in a multi-component metal alloy through unsupervised machine learning algorithms of singular value decomposition (SVD) and independent component analysis (ICA). Improvement of the signal-to-noise ratio (SNR) in the STEM-EDS spectrum images was achieved by combining SVD and ICA, leading to the identification of a nanoscale N-depleted region that was not observed in as-measured STEM-EDS. Additionally, the formation of the nanoscale N-depleted region was validated using STEM–electron energy loss spectroscopy and multicomponent diffusional transformation simulation. The enhancement of SNR in STEM-EDS spectrum images by machine learning algorithms can provide an efficient, economical chemical analysis method to identify light elements at the nanoscale.

Probing Compositional Order in Atomic Columns: STEM Simulations Beyond the Virtual Crystal Approximation

Taking advantage of recent advances in parallel computing, we studied compositional disorder along metal-oxygen atomic columns in a complex Mo,V-oxide bronze using multislice frozen-phonon calculations. Commonly, the virtual crystal approximation (VCA) is used to model compositional disorder at crystallographic sites in a unit cell for a number of different theoretical and experimental techniques. In the VCA, a weighted linear sum of atomic properties is used to approximate the model structure. When using the VCA, the extracted V content of Mo,V-O columns from experimental high-angle annular dark-field (HAADF) images will be about half the V content estimated from simulations, considering the distinct cation ordering. This discrepancy is larger than the spread of HAADF signals of different configurational orders at a given V concentration, which can be up to 20%. Certain "isophilic" atomic arrangements along the column can be distinguished from more random ones using HAADF-STEM imaging. The trends and ratios of the simulated intensity spreads due to different compositional ordering along 11 M-O columns along the c-axis of the Mo,V oxide bronze qualitatively match those observed in experimental HAADF-STEM data. Instrumental and sample-based noise adds to the variability but does not significantly distort the relative ratios of column intensity variation. We observed that we only required seven random configurations to represent the intensity variations along columns.

Correlative study of lattice imperfections in long-range ordered, nano-scale domains in a Fe-Co-Mo alloy

Recent advancements in data mining methods in atom probe microscopy have enabled new quantitative chemical and microstructural characterization beyond the standard three-dimensional reconstruction. For example, spatial distribution maps have been developed to enable visualisation of the local lattice occupation of a selected region of interest. However, the precision of such studies yet remains unknown as correlation with complementary methods would be required. Therefore, a correlative study of atom probe microscopy, neutron diffraction and microstructural modelling of long-range ordered, nano-scale domains in a well-researched Fe-Co-Mo Maraging-type steel is presented here. Its microstructure consists of Mo-enriched µ-phase (Fe,Co)₇Mo₆ particles embedded into a body-centred cubic FeCo matrix. Previous research has shown that under slow cooling conditions, this matrix partially decomposes into nano-scale B2 long-range ordered domains surrounded by disordered regions, resulting in reduced toughness in potential cutting applications. Usually, a long-range order parameter S referring to ideal B2 long-range order is assumed within such domains according to neutron diffraction. However, atom probe microscopy and modelling results presented in the current study indicate lattice imperfections with a partial substitution of atoms on the Fe- and Co-sublattices. After considering preferential retention effects during the atom probe experiment, a model unit cell is presented to define the observed imperfect B2 long-range order as pseudo-D0₃ long-range order, and the potential impact on the materials properties is discussed.

Introducing a Crystallography-Mediated Reconstruction (CMR) Approach to Atom Probe Tomography

Current approaches to reconstruction in atom probe tomography produce results that exhibit substantial distortions throughout the analysis depth. This is largely because of the need to apply a multitude of assumptions when estimating the evolution of the tip shape, and other pseudo-empirical reconstruction factors, which vary both across the face of the tip and throughout the analysis depth. We introduce a new crystallography-mediated reconstruction to improve the spatial accuracy and dramatically reduce these in-depth variations. To achieve this, we developed a barycentric transform to directly relate atomic positions in detector space to real space. This is mediated by novel crystallographic analysis techniques, including: (1) calculating the orientation of a crystal directly from the field evaporation map, (2) tracking pole locations throughout the evaporation sequence, and (3) accounting for the evolving tip radius in a manner that removes the dependence on the geometric field factor. By improving the in-depth spatial accuracy of the atom probe reconstruction, a greater accuracy of the atomic neighborhood relationships is available. This is critical in modern materials science and engineering, where an understanding of the solid solution architecture, precipitate dispersions, and descriptions of the interfaces between phases or grains are key inputs to microstructure-property relationships.

Assessing the Spatial Accuracy of the Reconstruction in Atom Probe Tomography and a New Calibratable Adaptive Reconstruction

We define a measure for the accuracy of tomographic reconstruction in atom probe tomography, named here the spatial error index. We demonstrate that this index can be used to compare rigorously the spatial accuracy of various different approaches to the calculation of tomographic reconstruction. This is useful, for example, to evaluate the performance of alternate tomographic reconstruction approaches, and ensures that the comparisons are independent of individual data quality or other instrumental parameters. We then introduce a new "adaptive reconstruction" formalism that uses a progression of reconstruction parameters based on a per-atom correction from the cube root of the inverse of the voltage, along with linear correction factors linked to the evaporation sequence. We apply the measure for spatial accuracy to this new reconstruction protocol.

DF-Fit: A Robust Algorithm for Detection of Crystallographic Information in Atom Probe Tomography Data

We report on a new algorithm for the detection of crystallographic information in three-dimensional, as retained in atom probe tomography (APT), with improved robustness and signal detection performance. The algorithm is underpinned by one-dimensional distribution functions (DFs), as per existing algorithms, but eliminates an unnecessary parameter as compared to current methods.By examining traditional DFs in an automated fashion in real space, rather than using Fourier transform approaches, we utilize an error metric based upon the expected value for a spatially random distribution for detecting crystallography. We show cases where the metric is able to successfully obtain orientation information, and show that it can function with high levels of additive and displacive background noise. We additionally compare this metric to Fourier transform methods, showing fewer artifacts when examining simulated datasets. An extension of the approach is used to aid the automatic detection of high-quality data regions within an entire dataset, albeit with a large increase in computational cost.This extension is demonstrated on acquired aluminum and tungsten APT datasets, and shown to be able to discern regions of the data which have relatively improved spatial data quality. Finally, this program has been made available for use in other laboratories undertaking their own analyses.

The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data

Atom probe tomography (APT) is a powerful technique to characterize buried three-dimensional nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure-property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the density-based spatial clustering of applications with noise algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the nonuniformity of the atomic density in the APT reconstruction itself (e.g., crystallographic poles and other field evaporation artifacts). This clustering method relies heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures, and an automatic cluster extraction algorithm to analyze clusters of varying atomic density in APT data. This approach requires only one free parameter, and other inputs can be estimated or bounded based on physical parameters, such as the lattice parameter and solute concentration. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen.

Self-consistent atom probe tomography reconstructions utilizing electron microscopy

Atom probe tomography reconstructions provide valuable information on nanometer-scale compositional variations within materials. As such, the spatial accuracy of the reconstructions is of primary importance for the resulting conclusions to be valid. Here, the use of transmission electron microscopy images before and after atom probe analysis to provide additional information and constraints is examined for a number of different materials. In particular, the consistency between the input reconstruction parameters and the output reconstruction is explored. It is demonstrated that it is possible to generate reconstructions in which the input and known values are completely consistent with the output reconstructions. Yet, it is also found that for all of the datasets examined, a particular power law relationship exists such that, if the image compression factor or detection efficiency is not constrained, a series of similarly spatially accurate reconstructions results. However, if one of these values can be independently assessed, then the other is known as well. Means of incorporating these findings and this general methodology into reconstruction protocols are also discussed.

Criteria and considerations for preparing atom-probe tomography specimens of nanomaterials utilizing an encapsulation methodology

Atom-probe tomography (APT) is a powerful method for characterization of nanomaterials due to its atomic-ppm level detection limit and Angstrom spatial resolution. Sample preparation for nanomaterials is, however, challenging because of their small dimensions and complicated geometries. Nanowires, with their high geometrical aspect ratio and nanowire length, 10 to 100 times their typical diameters, are highly suitable specimens for APT analyses, which can be transferred to silicon microposts using a nanomanipulator for direct APT measurements. This method is, however, prone to poor alignment and a limited field-of-view (FOV). Most importantly, direct implementation of APT with high aspect ratio nanowires may yield a low success rate of ∼30%, due to the high electric fields (10-40 V nm^-1) associated with APT. While this is acceptable for samples analyzed solely by APT, a low sample yield makes it challenging to perform correlative experiments on the same nanowire specimen, utilizing other sophisticated characterization instruments. Herein, we introduce a general strategy for preparing high-yield APT specimens by encapsulating the nanowires utilizing a conformal atomic-layer deposition (ALD) coating followed by site-specific lift-out using a dual-beam focused-ion beam microscope. The ALD deposited coating forms strong chemical bonds with the Si nanowires yielding a high-quality and robust interface. The evaporation electric fields of the ALD coating and the nanowires are tuned by changing laser energy to obtain a uniform evaporation rate. The strong adhesion of the ALD-coating/nanowire interface and uniform evaporation rate produce a >90% specimen yield, with small concentration of reconstruction artifacts in 3-D. Simultaneously, the field-of-view is enhanced and the surface of the nanowire becomes visible, which makes the study of surface adsorption, segregation and oxidation possible. We utilized ALD-ZnO coated silicon nanowires as an example for investigating the criteria for choosing coating materials, laser pulse energy, laser direction, sample geometry, and substrate materials. The same criteria and considerations are applicable for preparing specimens of nanoparticles and 2-D material.

Atom probe tomographic assessment of the distribution of germanium atoms implanted in a silicon matrix through nano-apertures

Ion implantation through nanometer-scale apertures (nano-apertures) is a promising method to precisely position ions in silicon matrices, which is a requirement for next generation electronic and quantum computing devices. This paper reports the application of atom probe tomography (APT) to investigate the three-dimensional distribution of germanium atoms in silicon after implantation through nano-aperture of 10 nm in diameter, for evaluation of the amount and spatial distribution of implanted dopants. The experimental results obtained by APT are consistent with a simple simulation with consideration of several effects during lithography and ion implantation, such as channeling and resist flow.

Atom probe tomography analysis of SiGe fins embedded in SiO2: Facts and artefacts

We present atom probe analysis of 40nm wide SiGe fins embedded in SiO₂ and discuss the root cause of artefacts observed in the reconstructed data. Additionally, we propose a simple data treatment routine, relying on complementary transmission electron microscopy analysis, to improve compositional analysis of the embedded SiGe fins. Using field evaporation simulations, we show that for high oxide to fin width ratios the difference in evaporation field thresholds between SiGe and SiO₂ results in a non-hemispherical emitter shape with a negative curvature in the direction across, but not along the fin. This peculiar emitter shape leads to severe local variations in radius and hence in magnification across the emitter apex causing ion trajectory aberrations and crossings. As shown by our experiments and simulations, this translates into unrealistic variations in the detected atom densities and faulty dimensions in the reconstructed volume, with the width of the fin being up to six-fold compressed. Rectification of the faulty dimensions and density variations in the SiGe fin was demonstrated with our dedicated data treatment routine.

Understanding of Capping Effects on the Tip Shape Evolution and on the Atom Probe Data of Bulk LaAlO3 Using Transmission Electron Microscopy

Two challenges exist in laser-assisted atom probe tomography (APT). First, a drastic decline in mass-resolving power is caused, not only by laser-induced thermal effects on the APT tips of bulk oxide materials, but also the associated asymmetric evaporation behavior; second, the field evaporation mechanisms of bulk oxide tips under laser illumination are still unclear due to the complex relations between laser pulse and oxide materials. In this study, both phenomena were investigated by depositing Ni- and Co-capping layers onto the bulk LaAlO3 tips, and using stepwise APT analysis with transmission electron microscopy (TEM) observation of the tip shapes. By employing the metallic capping, the heating at the surface of the oxide tips during APT analysis became more symmetrical, thereby enabling a high mass-resolving power in the mass spectrum. In addition, the stepwise microscopy technique visualized tip shape evolution during APT analysis, thereby accounting for evaporation sequences at the tip surface. The combination of "capping" and "stepwise APT with TEM," is applicable to any nonconductors; it provides a direct observation of tip shape evolution, allows determination of the field evaporation strength of oxides, and facilitates understanding of the effects of ultrafast laser illumination on an oxide tip.

Interfaces in Oxides Formed on NiAlCr Doped with Y, Hf, Ti, and B

This study applies atom probe tomography (APT) to analyze the oxide scales formed on model NiAlCr alloys doped with Hf, Y, Ti, and B. Due to its ability to measure small amounts of alloying elements in the oxide matrix and its ability to quantify segregation, the technique offers a possibility for detailed studies of the dopant's fate during high-temperature oxidation. Three model NiAlCr alloys with different additions of Hf, Y, Ti, and B were prepared and oxidized in O2 at 1,100°C for 100 h. All specimens showed an outer region consisting of different spinel oxides with relatively small grains and the protective Al2O3-oxide layer below. APT analyses focused mainly on this protective oxide layer. In all the investigated samples segregation of both Hf and Y to the oxide grain boundaries was observed and quantified. Neither B nor Ti were observed in the alumina grains or at the analyzed interfaces. The processes of formation of oxide scales and segregation of the alloying elements are discussed. The experimental challenges of the oxide analyses by APT are also addressed.

Atom probe study of B2 order and A2 disorder of the FeCo matrix in an Fe-Co-Mo-alloy

The physical and mechanical properties of intermetallic alloys can be tailored by controlling the degree of order of the solid solution by means of heat treatments. FeCo alloys with an appropriate composition exhibit an A2-disorder↔B2-order transition during continuous cooling from the disordered bcc region. The study of atomic order in intermetallic alloys by diffraction and its influence on the material properties is well established, however, investigating magnetic FeCo-based alloys by conventional methods such as X-ray diffraction is quite challenging. Thus, the imaging of ordered FeCo-nanostructures needs to be done with high resolution techniques. Transmission electron microscopy investigations of ordered FeCo domains are difficult, due to the chemical and physical similarity of Fe and Co atoms and the ferromagnetism of the samples. In this work it will be demonstrated, that the local atomic arrangement of ordered and disordered regions in an industrial Fe-Co-Mo alloy can be successfully imaged by atom probe measurements supported by field ion microscopy and transmission Kikuchi diffraction. Furthermore, a thorough atom probe parameter study will be presented and field evaporation artefacts as a function of crystallographic orientation in Fe-Co-samples will be discussed.

Atom-by-Atom Analysis of Semiconductor Nanowires with Parts Per Million Sensitivity

The functionality of semiconductor devices is determined by the incorporation of dopants at concentrations down to the parts per million (ppm) level and below. Optimization of intentional and unintentional impurity doping relies on methods to detect and map the level of impurities. Detecting such low concentrations of impurities in nanostructures is however challenging to date as on the one hand methods used for macroscopic samples cannot be applied due to the inherent small volumes or faceted surfaces and on the other hand conventional microscopic analysis techniques are not sufficiently sensitive. Here, we show that we can detect and map impurities at the ppm level in semiconductor nanowires using atom probe tomography. We develop a method applicable to a wide variety of nanowires relevant for electronic and optical devices. We expect that it will contribute significantly to the further optimization of the synthesis of nanowires, nanostructures and devices based on these structures.

Atomic-Scale Analytical Tomography

The concept of atomic-scale tomography has been proposed in the past decade as a technique that could deliver the position of all atoms with high precision and their elemental (isotopic) identity. The technique was never intended to be limited to merely structural information and there is clearly a rich array of additional analytical information that can be brought to bear on such tomographs. In this paper, some of these types of information are considered and the implications are explored. The fuller realm of this analytical and structural information may be called atomic-scale analytical tomography.

High-purity 3D nano-objects grown by focused-electron-beam induced deposition

To increase the efficiency of current electronics, a specific challenge for the next generation of memory, sensing and logic devices is to find suitable strategies to move from two- to three-dimensional (3D) architectures. However, the creation of real 3D nano-objects is not trivial. Emerging non-conventional nanofabrication tools are required for this purpose. One attractive method is focused-electron-beam induced deposition (FEBID), a direct-write process of 3D nano-objects. Here, we grow 3D iron and cobalt nanopillars by FEBID using diiron nonacarbonyl Fe2(CO)9, and dicobalt octacarbonyl Co2(CO)8, respectively, as starting materials. In addition, we systematically study the composition of these nanopillars at the sub-nanometer scale by atom probe tomography, explicitly mapping the homogeneity of the radial and longitudinal composition distributions. We show a way of fabricating high-purity 3D vertical nanostructures of ∼50 nm in diameter and a few micrometers in length. Our results suggest that the purity of such 3D nanoelements (above 90 at% Fe and above 95 at% Co) is directly linked to their growth regime, in which the selected deposition conditions are crucial for the final quality of the nanostructure. Moreover, we demonstrate that FEBID and the proposed characterization technique not only allow for growth and chemical analysis of single-element structures, but also offers a new way to directly study 3D core-shell architectures. This straightforward concept could establish a promising route to the design of 3D elements for future nano-electronic devices.

Dopant Diffusion and Activation in Silicon Nanowires Fabricated by ex Situ Doping: A Correlative Study via Atom-Probe Tomography and Scanning Tunneling Spectroscopy

Dopants play a critical role in modulating the electric properties of semiconducting materials, ranging from bulk to nanoscale semiconductors, nanowires, and quantum dots. The application of traditional doping methods developed for bulk materials involves additional considerations for nanoscale semiconductors because of the influence of surfaces and stochastic fluctuations, which may become significant at the nanometer-scale level. Monolayer doping is an ex situ doping method that permits the post growth doping of nanowires. Herein, using atom-probe tomography (APT) with subnanometer spatial resolution and atomic-ppm detection limit, we study the distributions of boron and phosphorus in ex situ doped silicon nanowires with accurate control. A highly phosphorus doped outer region and a uniformly boron doped interior are observed, which are not predicted by criteria based on bulk silicon. These phenomena are explained by fast interfacial diffusion of phosphorus and enhanced bulk diffusion of boron, respectively. The APT results are compared with scanning tunneling spectroscopy data, which yields information concerning the electrically active dopants. Overall, comparing the information obtained by the two methods permits us to evaluate the diffusivities of each different dopant type at the nanowire oxide, interface, and core regions. The combined data sets permit us to evaluate the electrical activation and compensation of the dopants in different regions of the nanowires and understand the details that lead to the sharp p-i-n junctions formed across the nanowire for the ex situ doping process.

Preparation and Analysis of Atom Probe Tips by Xenon Focused Ion Beam Milling

The damage and ion distribution induced in Si by an inductively coupled plasma Xe focused ion beam was investigated by atom probe tomography. By using predefined patterns it was possible to prepare the atom probe tips with a sub 50 nm end radius in the ion beam microscope. The atom probe reconstruction shows good agreement with simulated implantation profiles and interplanar distances extracted from spatial distribution maps. The elemental profiles of O and C indicate co-implantation during the milling process. The presence of small disc-shaped Xe clusters are also found in the three-dimensional reconstruction. These are attributed to the presence of Xe nanocrystals or bubbles that open during the evaporation process. The expected accumulated dose points to a loss of >95% of the Xe during analysis, which escapes undetected.

Mining information from atom probe data

Whilst atom probe tomography (APT) is a powerful technique with the capacity to gather information containing hundreds of millions of atoms from a single specimen, the ability to effectively use this information creates significant challenges. The main technological bottleneck lies in handling the extremely large amounts of data on spatial-chemical correlations, as well as developing new quantitative computational foundations for image reconstruction that target critical and transformative problems in materials science. The power to explore materials at the atomic scale with the extraordinary level of sensitivity of detection offered by atom probe tomography has not been not fully harnessed due to the challenges of dealing with missing, sparse and often noisy data. Hence there is a profound need to couple the analytical tools to deal with the data challenges with the experimental issues associated with this instrument. In this paper we provide a summary of some key issues associated with the challenges, and solutions to extract or "mine" fundamental materials science information from that data.

Effects of laser energy and wavelength on the analysis of LiFePO₄ using laser assisted atom probe tomography

The effects of laser wavelength (355 nm and 532 nm) and laser pulse energy on the quantitative analysis of LiFePO₄ by atom probe tomography are considered. A systematic investigation of ultraviolet (UV, 355 nm) and green (532 nm) laser assisted field evaporation has revealed distinctly different behaviors. With the use of a UV laser, the major issue was identified as the preferential loss of oxygen (up to 10 at%) while other elements (Li, Fe and P) were observed to be close to nominal ratios. Lowering the laser energy per pulse to 1 pJ/pulse from 50 pJ/pulse increased the observed oxygen concentration to nearer its correct stoichiometry, which was also well correlated with systematically higher concentrations of (16)O₂(+) ions. Green laser assisted field evaporation led to the selective loss of Li (~33% deficiency) and a relatively minor O deficiency. The loss of Li is likely a result of selective dc evaporation of Li between or after laser pulses. Comparison of the UV and green laser data suggests that the green wavelength energy was absorbed less efficiently than the UV wavelength because of differences in absorption at 355 and 532 nm for LiFePO₄. Plotting of multihit events on Saxey plots also revealed a strong neutral O2 loss from molecular dissociation, but quantification of this loss was insufficient to account for the observed oxygen deficiency.

Microstructural characterization of an Al-li-mg-cu alloy by correlative electron tomography and atom probe tomography

Correlative electron tomography and atom probe tomography have been carried out successfully on the same region of a commercial 8090 aluminum alloy (Al-Li-Mg-Cu). The combination of the two techniques allows accurate geometric reconstruction of the atom probe tomography data verified by crystallographic information retrieved from the reconstruction. Quantitative analysis of the precipitate phase compositions and volume fractions of each phase have been obtained from the atom probe tomography and electron tomography at various scales, showing strong agreement between both techniques.

Atomic-scale tomography: a 2020 vision

Atomic-scale tomography (AST) is defined and its place in microscopy is considered. Arguments are made that AST, as defined, would be the ultimate microscopy. The available pathways for achieving AST are examined and we conclude that atom probe tomography (APT) may be a viable basis for AST on its own and that APT in conjunction with transmission electron microscopy is a likely path as well. Some possible configurations of instrumentation for achieving AST are described. The concept of metaimages is introduced where data from multiple techniques are melded to create synergies in a multidimensional data structure. When coupled with integrated computational materials engineering, structure-properties microscopy is envisioned. The implications of AST for science and technology are explored.

Refining spatial distribution maps for atom probe tomography via data dimensionality reduction methods

A mathematical framework based on singular value decomposition is used to analyze the covariance among interatomic frequency distributions in spatial distribution maps (SDMs). Using this approach, singular vectors that capture the covariance within the SDM data are obtained. The structurally relevant singular vectors (SRSVs) are identified. Using the SRSVs, we extract information from z-SDMs that not only captures the offset between the atomic planes but also captures the covariance in the atomic structure among the neighborhood atomic planes. These refined z-SDMs classify the Δ(Δz) slices in the SDMs into structurally relevant information, noise, and aberrations. The SRSVs are used to construct refined xy-SDMs that provide enhanced structural information for three-dimensional atom probe tomography.

Atom probe tomography simulations and density functional theory calculations of bonding energies in Cu3Au

In this article the Cu-Au binding energy in Cu3Au is determined by comparing experimental atom probe tomography (APT) results to simulations. The resulting bonding energy is supported by density functional theory calculations. The APT simulations are based on the Müller-Schottky equation, which is modified to include different atomic neighborhoods and their characteristic bonds. The local environment is considered up to the fifth next nearest neighbors. To compare the experimental with simulated APT data, the AtomVicinity algorithm, which provides statistical information about the positions of the neighboring atoms, is applied. The quality of this information is influenced by the field evaporation behavior of the different species, which is connected to the bonding energies.