Atom Probe Tomography Investigation of Clustering in Model P2O5-Doped Borosilicate Glasses for Nuclear Waste Vitrification.

Atom probe tomography (APT) has been utilized to investigate the microstructure of two model borosilicate glasses designed to understand the solubility limits of phosphorous pentoxide (P2O5). This component is found in certain high-level radioactive defence wastes destined for vitrification, where phase separation can potentially lead to a number of issues relating to the processing of the glass and its long-term chemical and structural stability. The development of suitable focused ion beam (FIB)-preparation routes and APT analysis conditions were initially determined for the model glasses, before examining their detailed microstructures. In a 3.0 mol% P2O5-doped glass, both visual inspection and sensitive statistical analysis of the APT data show homogeneous microstructures, while raising the content to 4.0 mol% initiates the formation of phosphorus-enriched nanoscale precipitates. This study confirms the expected inhomogeneities and phase separation of these glasses and offers routes to characterizing these at near-atomic scale resolution using APT.

Large-Scale Atom Probe Tomography Data Mining: Methods and Application to Inform Hydrogen Behavior.

A large number of atom probe tomography (APT) datasets from past experiments were collected into a database to conduct statistical analyses. An effective way of handling the data is shown, and a study on hydrogen is conducted to illustrate the usefulness of this approach. We propose to handle a large collection of APT spectra as a point cloud and use a city block distance-based metric to measure dissimilarity between spectra. This enables quick and automated searching for spectra by similarity. Since spectra from APT experiments on similar materials are similar, the point cloud of spectra contains clusters. Analysis of these clusters of spectra in this point cloud allows us to infer the sample materials. The behavior of contaminant hydrogen is analyzed and correlated with voltage, electric field, and sample base material. Across several materials, the H2+ /H+ ratio is found to decrease with increasing field, likely an indication of postionization of H2+ ions. The absolute amounts of H2+ and H+ are found to frequently increase throughout APT experiments.

Atom Probe Tomography of a Cu-Doped TiNiSn Thermoelectric Material: Nanoscale Structure and Optimization of Analysis Conditions.

Cu-doping and crystallographic site occupations within the half-Heusler (HH) TiNiSn, a promising thermoelectric material, have been examined by atom probe tomography. In particular, this investigation aims to better understand the influence of atom probe analysis conditions on the measured chemical composition. Under a voltage-pulsing mode, atomic planes are clearly resolved and suggest an arrangement of elements in-line with the expected HH (F-43m space group) crystal structure. The Cu dopant is also distributed uniformly throughout the bulk material. For operation under laser-pulsed modes, the returned composition is highly dependent on the selected laser energy, with high energies resulting in the measurement of excessively high absolute Ti counts at the expense of Sn and in particular Ni. High laser energies also appear to be correlated with the detection of a high fraction of partial hits, indicating nonideal evaporation behavior. The possible mechanisms for these trends are discussed, along with suggestions for optimal analysis conditions for these and similar thermoelectric materials.

Processing APT Spectral Backgrounds for Improved Quantification.

We describe a method to estimate background noise in atom probe tomography (APT) mass spectra and to use this information to enhance both background correction and quantification. Our approach is mathematically general in form for any detector exhibiting Poisson noise with a fixed data acquisition time window, at voltages varying through the experiment. We show that this accurately estimates the background observed in real experiments. The method requires, as a minimum, the z-coordinate and mass-to-charge-state data as input and can be applied retrospectively. Further improvements are obtained with additional information such as acquisition voltage. Using this method allows for improved estimation of variance in the background, and more robust quantification, with quantified count limits at parts-per-million concentrations. To demonstrate applications, we show a simple peak detection implementation, which quantitatively suppresses false positives arising from random noise sources. We additionally quantify the detectability of 121-Sb in a standardized-doped Si microtip as (1.5 × 10−5, 3.8 × 10−5) atomic fraction, α = 0.95. This technique is applicable to all modes of APT data acquisition and is highly general in nature, ultimately allowing for improvements in analyzing low ionic count species in datasets.

Reflections on the Analysis of Interfaces and Grain Boundaries by Atom Probe Tomography.

Interfaces play critical roles in materials and are usually both structurally and compositionally complex microstructural features. The precise characterization of their nature in three-dimensions at the atomic scale is one of the grand challenges for microscopy and microanalysis, as this information is crucial to establish structure-property relationships. Atom probe tomography is well suited to analyzing the chemistry of interfaces at the nanoscale. However, optimizing such microanalysis of interfaces requires great care in the implementation across all aspects of the technique from specimen preparation to data analysis and ultimately the interpretation of this information. This article provides critical perspectives on key aspects pertaining to spatial resolution limits and the issues with the compositional analysis that can limit the quantification of interface measurements. Here, we use the example of grain boundaries in steels; however, the results are applicable for the characterization of grain boundaries and transformation interfaces in a very wide range of industrially relevant engineering materials.

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.

A Gas-Phase Reaction Cell for Modern Atom Probe Systems.

In this work, we demonstrate a new system for the examination of gas interactions with surfaces via atom probe tomography. This system provides capability of examining the surface and subsurface interactions of gases with a wide range of specimens, as well as a selection of input gas types. This system has been primarily developed to aid the investigation of hydrogen interactions with metallurgical samples, to better understand the phenomenon of hydrogen embrittlement. In its current form, it is able to operate at pressures from 10-6 to 1000 mbar (abs), can use a variety of gasses, and is equipped with heating and cryogenic quenching capabilities. We use this system to examine the interaction of hydrogen with Pd, as well as the interaction of water vapor and oxygen in Mg samples.

Interpreting Atom Probe Data from Oxide-Metal Interfaces.

Understanding oxide-metal interfaces is crucial to the advancement of materials and components for many industries, most notably for semiconductor devices and power generation. Atom probe tomography provides three-dimensional, atomic scale information about chemical composition, making it an excellent technique for interface analysis. However, difficulties arise when analyzing interfacial regions due to trajectory aberrations, such as local magnification, and reconstruction artifacts. Correlative microscopy and field simulation techniques have revealed that nonuniform evolution of the tip geometry, caused by heterogeneous field evaporation, is partly responsible for these artifacts. Here we attempt to understand these trajectory artifacts through a study of the local evaporation field conditions. With a better understanding of the local evaporation field, it may be possible to account for some of the local magnification effects during the reconstruction process, eliminating these artifacts before data analysis.

Atom Probe Analysis of Ex Situ Gas-Charged Stable Hydrides.

In this work, we report on the atom probe tomography analysis of two metallic hydrides formed by pressurized charging using an ex situ hydrogen charging cell, in the pressure range of 200-500 kPa (2-5 bar). Specifically we report on the deuterium charging of Pd/Rh and V systems. Using this ex situ system, we demonstrate the successful loading and subsequent atom probe analysis of deuterium within a Pd/Rh alloy, and demonstrate that deuterium is likely present within the oxide-metal interface of a native oxide formed on vanadium. Through these experiments, we demonstrate the feasibility of ex situ hydrogen analysis for hydrides via atom probe tomography, and thus a practical route to three-dimensional imaging of hydrogen in hydrides at the atomic scale.

Single-Ion Deconvolution of Mass Peak Overlaps for Atom Probe Microscopy.

Due to the intrinsic evaporation properties of the material studied, insufficient mass-resolving power and lack of knowledge of the kinetic energy of incident ions, peaks in the atom probe mass-to-charge spectrum can overlap and result in incorrect composition measurements. Contributions to these peak overlaps can be deconvoluted globally, by simply examining adjacent peaks combined with knowledge of natural isotopic abundances. However, this strategy does not account for the fact that the relative contributions to this convoluted signal can often vary significantly in different regions of the analysis volume; e.g., across interfaces and within clusters. Some progress has been made with spatially localized deconvolution in cases where the discrete microstructural regions can be easily identified within the reconstruction, but this means no further point cloud analyses are possible. Hence, we present an ion-by-ion methodology where the identity of each ion, normally obscured by peak overlap, is resolved by examining the isotopic abundance of their immediate surroundings. The resulting peak-deconvoluted data are a point cloud and can be analyzed with any existing tools. We present two detailed case studies and discussion of the limitations of this new technique.

Detecting Clusters in Atom Probe Data with Gaussian Mixture Models.

Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.

Automated Atom-By-Atom Three-Dimensional (3D) Reconstruction of Field Ion Microscopy Data.

An automated procedure has been developed for the reconstruction of field ion microscopy (FIM) data that maintains its atomistic nature. FIM characterizes individual atoms on the specimen's surface, evolving subject to field evaporation, in a series of two-dimensional (2D) images. Its unique spatial resolution enables direct imaging of crystal defects as small as single vacancies. To fully exploit FIM's potential, automated analysis tools are required. The reconstruction algorithm developed here relies on minimal assumptions and is sensitive to atomic coordinates of all imaged atoms. It tracks the atoms across a sequence of images, allocating each to its respective crystallographic plane. The result is a highly accurate 3D lattice-resolved reconstruction. The procedure is applied to over 2000 tungsten atoms, including ion-implanted planes. The approach is further adapted to analyze carbides in a steel matrix, demonstrating its applicability to a range of materials. A vast amount of information is collected during the experiment that can underpin advanced analyses such as automated detection of "out of sequence" events, subangstrom surface displacements and defects effects on neighboring atoms. These analyses have the potential to reveal new insights into the field evaporation process and contribute to improving accuracy and scope of 3D FIM and atom probe characterization.

Comparing the Consistency of Atom Probe Tomography Measurements of Small-Scale Segregation and Clustering Between the LEAP 3000 and LEAP 5000 Instruments.

The local electrode atom probe (LEAP) has become the primary instrument used for atom probe tomography measurements. Recent advances in detector and laser design, together with updated hit detection algorithms, have been incorporated into the latest LEAP 5000 instrument, but the implications of these changes on measurements, particularly the size and chemistry of small clusters and elemental segregations, have not been explored. In this study, we compare data sets from a variety of materials with small-scale chemical heterogeneity using both a LEAP 3000 instrument with 37% detector efficiency and a 532-nm green laser and a new LEAP 5000 instrument with a manufacturer estimated increase to 52% detector efficiency, and a 355-nm ultraviolet laser. In general, it was found that the number of atoms within small clusters or surface segregation increased in the LEAP 5000, as would be expected by the reported increase in detector efficiency from the LEAP 3000 architecture, but subtle differences in chemistry were observed which are attributed to changes in the way multiple hit detection is calculated using the LEAP 5000.

Nanoscale Stoichiometric Analysis of a High-Temperature Superconductor by Atom Probe Tomography.

The functional properties of the high-temperature superconductor Y1Ba2Cu3O7-δ (Y-123) are closely correlated to the exact stoichiometry and oxygen content. Exceeding the critical value of 1 oxygen vacancy for every five unit cells (δ>0.2, which translates to a 1.5 at% deviation from the nominal oxygen stoichiometry of Y7.7Ba15.3Cu23O54-δ ) is sufficient to alter the superconducting properties. Stoichiometry at the nanometer scale, particularly of oxygen and other lighter elements, is extremely difficult to quantify in complex functional ceramics by most currently available analytical techniques. The present study is an analysis and optimization of the experimental conditions required to quantify the local nanoscale stoichiometry of single crystal yttrium barium copper oxide (YBCO) samples in three dimensions by atom probe tomography (APT). APT analysis required systematic exploration of a wide range of data acquisition and processing conditions to calibrate the measurements. Laser pulse energy, ion identification, and the choice of range widths were all found to influence composition measurements. The final composition obtained from melt-grown crystals with optimized superconducting properties was Y7.9Ba10.4Cu24.4O57.2.

Practical Issues for Atom Probe Tomography Analysis of III-Nitride Semiconductor Materials.

Various practical issues affecting atom probe tomography (APT) analysis of III-nitride semiconductors have been studied as part of an investigation using a c-plane InAlN/GaN heterostructure. Specimen preparation was undertaken using a focused ion beam microscope with a mono-isotopic Ga source. This enabled the unambiguous observation of implantation damage induced by sample preparation. In the reconstructed InAlN layer Ga implantation was demonstrated for the standard "clean-up" voltage (5 kV), but this was significantly reduced by using a lower voltage (e.g., 1 kV). The characteristics of APT data from the desorption maps to the mass spectra and measured chemical compositions were examined within the GaN buffer layer underlying the InAlN layer in both pulsed laser and pulsed voltage modes. The measured Ga content increased monotonically with increasing laser pulse energy and voltage pulse fraction within the examined ranges. The best results were obtained at very low laser energy, with the Ga content close to the expected stoichiometric value for GaN and the associated desorption map showing a clear crystallographic pole structure.

Resolving the morphology of niobium carbonitride nano-precipitates in steel using atom probe tomography.

Atom probe is a powerful technique for studying the composition of nano-precipitates, but their morphology within the reconstructed data is distorted due to the so-called local magnification effect. A new technique has been developed to mitigate this limitation by characterizing the distribution of the surrounding matrix atoms, rather than those contained within the nano-precipitates themselves. A comprehensive chemical analysis enables further information on size and chemistry to be obtained. The method enables new insight into the morphology and chemistry of niobium carbonitride nano-precipitates within ferrite for a series of Nb-microalloyed ultra-thin cast strip steels. The results are supported by complementary high-resolution transmission electron microscopy.

Level set methods for modelling field evaporation in atom probe.

Atom probe is a nanoscale technique for creating three-dimensional spatially and chemically resolved point datasets, primarily of metallic or semiconductor materials. While atom probe can achieve local high-level resolution, the spatial coherence of the technique is highly dependent upon the evaporative physics in the material and can often result in large geometric distortions in experimental results. The distortions originate from uncertainties in the projection function between the field evaporating specimen and the ion detector. Here we explore the possibility of continuum numerical approximations to the evaporative behavior during an atom probe experiment, and the subsequent propagation of ions to the detector, with particular emphasis placed on the solution of axisymmetric systems, such as isolated particles and multilayer systems. Ultimately, this method may prove critical in rapid modeling of tip shape evolution in atom probe tomography, which itself is a key factor in the rapid generation of spatially accurate reconstructions in atom probe datasets.

A Correlative Study of Interfacial Segregation in a Cu-Doped TiNiSn Thermoelectric half-Heusler Alloy.

The performance of thermoelectric materials depends on both their atomic-scale chemistry and the nature of microstructural details such as grain boundaries and inclusions. Here, the elemental distribution throughout a TiNiCu0.1Sn thermoelectric material has been examined in a correlative study deploying atom-probe tomography (APT) and electron microscopies and spectroscopies. Elemental mapping and electron diffraction reveal two distinct types of grain boundary that are either topologically rough and meandering in profile or more regular and geometric. Transmission electron microscopy studies indicate that the Cu dopant segregates at both grain boundary types, attributed to extrusion from the bulk during hot-pressing. The geometric boundaries are found to have a degree of crystallographic coherence between neighboring grains; the rough boundaries are decorated with oxide impurity precipitates. APT was used to study the three-dimensional character of rough grain boundaries and reveals that Cu is present as discrete, elongated nanoprecipitates cosegregating alongside larger substoichiometric titanium oxide precipitates. Away from the grain boundary, the alloy microstructure is relatively homogeneous, and the atom-probe results suggest a statistical and uniform distribution of Cu with no evidence for segregation within grains. The extrusion suggests a solubility limit for Cu in the bulk material, with the potential to influence carrier and phonon transport properties across grain boundaries. These results underline the importance of fully understanding localized variations in chemistry that influence the functionality of materials, particularly at grain boundaries.

Lattice rectification in atom probe tomography: toward true three-dimensional atomic microscopy.

Atom probe tomography (APT) represents a significant step toward atomic resolution microscopy, analytically imaging individual atoms with highly accurate, though imperfect, chemical identity and three-dimensional (3D) positional information. Here, a technique to retrieve crystallographic information from raw APT data and restore the lattice-specific atomic configuration of the original specimen is presented. This lattice rectification technique has been applied to a pure metal, W, and then to the analysis of a multicomponent Al alloy. Significantly, the atoms are located to their true lattice sites not by an averaging, but by triangulation of each particular atom detected in the 3D atom-by-atom reconstruction. Lattice rectification of raw APT reconstruction provides unprecedented detail as to the fundamental solute hierarchy of the solid solution. Atomic clustering has been recognized as important in affecting alloy behavior, such as for the Al-1.1 Cu-1.7 Mg (at. %) investigated here, which exhibits a remarkable rapid hardening reaction during the early stages of aging, linked to clustering of solutes. The technique has enabled lattice-site and species-specific radial distribution functions, nearest-neighbor analyses, and short-range order parameters, and we demonstrate a characterization of solute-clustering with unmatched sensitivity and precision.

Structural and compositional analysis of (InGa)(AsSb)/GaAs/GaP Stranski-Krastanov quantum dots.

We investigated metal-organic vapor phase epitaxy grown (InGa)(AsSb)/GaAs/GaP Stranski-Krastanov quantum dots (QDs) with potential applications in QD-Flash memories by cross-sectional scanning tunneling microscopy (X-STM) and atom probe tomography (APT). The combination of X-STM and APT is a very powerful approach to study semiconductor heterostructures with atomic resolution, which provides detailed structural and compositional information on the system. The rather small QDs are found to be of truncated pyramid shape with a very small top facet and occur in our sample with a very high density of ∼4 × 1011 cm-2. APT experiments revealed that the QDs are GaAs rich with smaller amounts of In and Sb. Finite element (FE) simulations are performed using structural data from X-STM to calculate the lattice constant and the outward relaxation of the cleaved surface. The composition of the QDs is estimated by combining the results from X-STM and the FE simulations, yielding ∼InxGa1 - xAs1 - ySby, where x = 0.25-0.30 and y = 0.10-0.15. Noticeably, the reported composition is in good agreement with the experimental results obtained by APT, previous optical, electrical, and theoretical analysis carried out on this material system. This confirms that the InGaSb and GaAs layers involved in the QD formation have strongly intermixed. A detailed analysis of the QD capping layer shows the segregation of Sb and In from the QD layer, where both APT and X-STM show that the Sb mainly resides outside the QDs proving that Sb has mainly acted as a surfactant during the dot formation. Our structural and compositional analysis provides a valuable insight into this novel QD system and a path for further growth optimization to improve the storage time of the QD-Flash memory devices.