To solve the uncertainty of the platinum (Pt)–palladium (Pd) phase diagram, especially the existence of a suggested miscibility gap, atom probe tomography (APT) was used to determine the time evolution of the composition after heat treatment. Due to the extraordinarily slow diffusion in the temperature range of the controversial phase separation, the investigated volume was limited to nano-sized multiple layers deposited by ion beam sputtering (IBS). The evaporated volume was reconstructed from the obtained datasets and the respective diffusion coefficients were determined using the Fourier series solution of the diffusion equation. Beginning with pure Pt and Pd layers annealed at 673, 773, 873, and 973 K, the mixing appears to be purely diffusion controlled in the chosen annealing times, but the state of complete mixing was still not observed. Therefore, extended isothermal annealing sequences at 673 and 773 K with pre-alloyed layers have been carried out. They clearly suggest complete mixing even at the lowest investigated temperatures.

Atom probe tomography (APT) has been established in the microscopic chemical and spatial analysis of metallic or semiconductors nanostructures. In recent years, and especially with the development of a transfer shuttle system and adapted preparation protocols, the field of frozen liquids has been opened up. Still, very limited knowledge is available about the evaporation and fragmentation behavior of frozen liquids in APT. In this work, efforts were made to extend the method toward organic and biological soft matter, which are mostly built from hydrocarbon chains, the evaporation and fragmentation behavior of simple alkane chains (n-tetradecanes). Tetradecane shows a very complex evaporation behavior whereby peaks of C1–C15 can be observed. Based on multihit events and the representation of these in correlation plots, more detailed information about the evaporation behavior and the decay of molecules into smaller fragments in the region near the tip can be studied. A variety of different dissociation tracks of larger molecules in their excited state and their subsequent decay in low-field regions, on the way to the detector, could be observed and the dissociation zone in the low-field region was calculated.

We report on comparative atom probe tomography investigations of γ/γ′-forming Co–12Ti–4Mo–Cr alloys. Moderate additions of Cr (2 and 4 at%) reduced the γ/γ′ lattice misfit and increased the γ′ volume fraction of a Co–12Ti–4Mo alloy significantly. These microstructural changes were accompanied by changes in the elemental partitioning between γ and γ′ and site-occupancy in γ′. Spatial distribution maps revealed that Mo occupied both Co and Ti sub-lattice sites in γ′. In agreement with the experimental data, thermodynamic calculations predicted a stronger tendency for Mo to occupy the Co-sites than for Cr and an increase in Cr fraction on the Ti-sites with increasing Cr content.

Binary Fe–Cu alloys are effective prototypes for investigating radiation-induced formation and growth of nanometric Cu-rich precipitates (CRPs) in nuclear reactor pressure vessels. In this report, the temporal evolution of CRPs during thermal aging of Fe–Cu binary alloys has been investigated by using complementary techniques such as atom probe tomography (APT) and small-angle neutron scattering (SANS). We report a detailed quantitative evolution of a rarely observed morphological transformation of Cu precipitates from spherical to ellipsoid with a significant change (approximately two times) in aspect ratio, an effect known to be associated with the 9R-3R structural transition of the precipitates. It is demonstrated through APT that the precipitates remain spherical up to 8 h, however, they subsequently convert to oblate ellipsoid upon further aging. SANS analysis also detected signs of this morphological transition in reciprocal space. Furthermore, SANS quantifies evolution of the precipitates and corroborates well with the APT results. Interestingly, the power-law exponent of the temporal evolution for mean size and number density agree reasonably well with the Lifshitz–Slyozov–Wagner model, in spite of the complex morphological evolution of the precipitates.

We have analyzed atom probe tomography reconstructions of disaggregated meteoritic material containing nanodiamonds and disordered carbon to determine whether these phases formed in the solar system or whether they predate the solar system and were formed in supernovae or the interstellar medium. We developed a method to distinguish between these two carbonaceous phases in < 100 nm diameter aggregates using the ratios of various native and contaminant molecular species. We find variations in measured 12C/13C ratios between the two phases that suggest hydrides form more readily during field evaporation of the disordered C than the nanodiamonds.

Alnico alloys have long been used as strong permanent magnets because of their ferromagnetism and high coercivity. Understanding their structural details allows for better prediction of the resulting magnetic properties. However, quantitative three-dimensional characterization of the phase separation in these alloys is still challenged by the spatial quantification of nanoscale phases. Herein, we apply a dual tomography approach, where correlative scanning transmission electron microscopy (STEM) energy-dispersive X-ray spectroscopic (EDS) tomography and atom probe tomography (APT) are used to investigate the initial phase separation process of an alnico 8 alloy upon non-magnetic annealing. STEM-EDS tomography provides information on the morphology and volume fractions of Fe–Co-rich and Νi–Al-rich phases after spinodal decomposition in addition to quantitative information of the composition of a nanoscale volume. Subsequent analysis of a portion of the same specimen by APT offers quantitative chemical information of each phase at the sub-nanometer scale. Furthermore, APT reveals small, 2–4 nm Fe-rich α1 phases that are nucleated in the Ni-rich α2 matrix. From this information, we show that phase separation of the alnico 8 alloy consists of both spinodal decomposition and nucleation and growth processes. The complementary benefits and challenges associated with correlative STEM-EDS and APT are discussed.

This article focuses on four topics that demonstrate the importance of atom probe tomography for obtaining nanostructural information that provides deep insights into the structures of metallic alloys, leading to a better understanding of their properties. First, we discuss the microstructure–coercivity relationship of Nd-Fe-B permanent magnets, essential for developing a higher coercivity magnet. Second, we address equilibrium segregation at grain boundaries with the aim of manipulating their interfacial structure, energies, compositions, and properties, thereby enabling beneficial material behavior. Third, recent progress in the search to extend the performance and practicality of the next generation of advanced high-strength steels is discussed. Finally, a study of the temporal evolution of a Ni-Al-Cr alloy through the stages of nucleation, growth, and coarsening (Ostwald ripening) and its relationship with the predictions of a model for quasi-stationary coarsening is described. This information is critical for understanding high-temperature mechanical properties of the material.

Nanostructure evolution during low temperature aging of three binary Fe-Cr alloys has been investigated by atom probe tomography. A new method based on radial distribution function (RDF) analysis to quantify the composition wavelength and amplitude of spinodal decomposition is proposed. Wavelengths estimated from RDF have a power-law type evolution and are in reasonable agreement with wavelengths estimated using other more conventional methods. The main advantages of the proposed method are the following: (1) Selecting a box size to generate the frequency diagram, which is known to generate bias in the evaluation of amplitude, is avoided. (2) The determination of amplitude is systematic and utilizes the wavelength evaluated first to subsequently evaluate the amplitude. (3) The RDF is capable of representing very subtle decomposition, which is not possible using frequency diagrams, and thus a proposed theoretical treatment of the experimental RDF creates the possibility to determine amplitude at very early stages of spinodal decomposition.

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.

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.

We demonstrate for the first time that multivariate statistical analysis techniques can be applied to atom probe tomography data to estimate the chemical composition of a sample at the full spatial resolution of the atom probe in three dimensions. Whereas the raw atom probe data provide the specific identity of an atom at a precise location, the multivariate results can be interpreted in terms of the probabilities that an atom representing a particular chemical phase is situated there. When aggregated to the size scale of a single atom (∼0.2 nm), atom probe spectral-image datasets are huge and extremely sparse. In fact, the average spectrum will have somewhat less than one total count per spectrum due to imperfect detection efficiency. These conditions, under which the variance in the data is completely dominated by counting noise, test the limits of multivariate analysis, and an extensive discussion of how to extract the chemical information is presented. Efficient numerical approaches to performing principal component analysis (PCA) on these datasets, which may number hundreds of millions of individual spectra, are put forward, and it is shown that PCA can be computed in a few seconds on a typical laptop computer.

The application of wide field-of-view detection systems to atom probe experiments emphasizes the importance of careful parameter selection in the tomographic reconstruction of the analyzed volume, as the sensitivity to errors rises steeply with increases in analysis dimensions. In this article, a self-consistent method is presented for the systematic determination of the main reconstruction parameters. In the proposed approach, the compression factor and the field factor are determined using geometrical projections from the desorption images. A three-dimensional Fourier transform is then applied to a series of reconstructions, and after comparing to the known material crystallography, the efficiency of the detector is estimated. The final results demonstrate a significant improvement in the accuracy of the reconstructed volumes.

A real-space technique for finding structural information in atom probe tomographs, spatial distribution maps (SDM), is described. The mechanics of the technique are explained, and it is then applied to some test cases. Many applications of SDM in atom probe tomography are illustrated with examples including finding crystal lattices, correcting lattice strains in reconstructed images, quantifying trajectory aberrations, quantifying spatial resolution, quantifying chemical ordering, dark-field imaging, determining orientation relationships, extracting radial distribution functions, and measuring ion detection efficiency.