Sculpins (coastrange and slimy) and sticklebacks (ninespine and threespine) are widely distributed fishes cohabiting 2 south-central Alaskan lakes (Aleknagik and Iliamna), and all these species are parasitized by cryptic diphyllobothriidean cestodes in the genus Schistocephalus. The goal of this investigation was to test for host-specific parasitic relationships between sculpins and sticklebacks based upon morphological traits (segment counts) and sequence variation across the NADH1 gene. A total of 446 plerocercoids was examined. Large, significant differences in mean segment counts were found between cestodes in sculpin (mean = 112; standard deviation [s.d.] = 15) and stickleback (mean = 86; s.d. = 9) hosts within and between lakes. Nucleotide sequence divergence between parasites from sculpin and stickleback hosts was 20.5%, and Bayesian phylogenetic analysis recovered 2 well-supported clades of cestodes reflecting intermediate host family (i.e. sculpin, Cottidae vs stickleback, Gasterosteidae). Our findings point to the presence of a distinct lineage of cryptic Schistocephalus in sculpins from Aleknagik and Iliamna lakes that warrants further investigation to determine appropriate evolutionary and taxonomic recognition.

Using a combination of simulated data and pyrite isotopic reference materials, we have refined a methodology to obtain quantitative δ34S measurements from atom probe tomography (APT) datasets. This study builds on previous attempts to characterize relative 34S/32S ratios in gold-containing pyrite using APT. We have also improved our understanding of the artifacts inherent in laser-pulsed APT of insulators. Specifically, we find the probability of multi-hit detection events increases during the APT experiment, which can have a detrimental effect on the accuracy of the analysis. We demonstrate the use of standardized corrected time-of-flight single-hit data for our isotopic analysis. Additionally, we identify issues with the standard methods of extracting background-corrected counts from APT mass spectra. These lead to inaccurate and inconsistent isotopic analyses due to human variability in peak ranging and issues with background correction algorithms. In this study, we use the corrected time-of-flight single-hit data, an adaptive peak fitting algorithm, and an improved deconvolution algorithm to extract 34S/32S ratios from the S2+ peaks. By analyzing against a standard material, acquired under similar conditions, we have extracted δ34S values to within ±5‰ (1‰ = 1 part per thousand) of the published values of our standards.

In this study, atom probe tomography (APT) was used to investigate strontium-containing bioactive glass particles (BG-Sr10) and strontium-releasing bioactive glass-based scaffolds (pSrBG), both of which are attractive biomaterials with applications in critical bone damage repair. We outline the challenges and corresponding countermeasures of this nonconductive biomaterial for APT sample preparation and experiments, such as avoiding direct contact between focussed ion beam micromanipulators and the extracted cantilever to reduce damage during liftout. Using a low imaging voltage (≤3 kV) and current (≤500 pA) in the scanning electron microscope and a low acceleration voltage (≤2 kV) and current (≤200 pA) in the focussed ion beam prevents tip bending in the final stages of annular milling. To optimize the atom probe experiment, we considered five factors: total detected hits, multiple hits, the background level, the charge-state ratio, and the accuracy of the measured compositions, to explore the optimal laser pulse for BG-Sr10 bioactive glass. We show that a stage temperature of 30 K, 200–250 pJ laser pulse energy, 0.3% detection rate, and 200 kHz pulse rate are optimized experimental parameters for bioactive glass. The use of improved experimental preparation methods and optimized parameters resulted in a 90% successful yield of pSrBG samples by APT.

Zirconium alloys are common fuel claddings in nuclear fission reactors and are susceptible to the effects of hydrogen embrittlement. There is a need to be able to detect and image hydrogen at the atomic scale to gain the experimental evidence necessary to fully understand hydrogen embrittlement. Through the use of deuterium tracers, atom probe tomography (APT) is able to detect and spatially locate hydrogen at the atomic scale. Previous works have highlighted issues with quantifying deuterium concentrations using APT due to complex peak overlaps in the mass-to-charge-state ratio spectrum between molecular hydrogen and deuterium (H2 and D). In this work, we use new methods to analyze historic and simulated atom probe data, by applying currently available data analysis tools, to optimize solving peak overlaps to improve the quantification of deuterium. This method has been applied to literature data to quantify the deuterium concentrations in a concentration line profile across an α-Zr/deuteride interface.

One of the main capabilities of atom probe tomography (APT) is the ability to not only identify but also characterize early stages of precipitation at length scales that are not achievable by other techniques. One of the most popular methods to identify nanoscale clustering in APT data, based on the density-based spatial clustering of applications with noise (DBSCAN), is used extensively in many branches of research. However, it is common that not all of the steps leading to the selection of certain parameters used in the analysis are reported. Without knowing the rationale behind parameter selection, it may be difficult to compare cluster parameters obtained by different researchers. In this work, a simple open-source tool, PosgenPy, is used to justify cluster search parameter selection via providing a systematic sweep through parameter values with multiple randomizations to minimize a false-positive cluster ratio. The tool is applied to several different microstructures: a simulated material system and two experimental datasets from a low-alloy steel . The analyses show how values for the various parameters can be selected to ensure that the calculated cluster number density and cluster composition are accurate.

We investigated a new method for estimating specimen hydrogen content in atom probe tomography (APT) in experiments where molecular hydrogen ions (${\rm H}_2^ +$) originating from the measurement environment can overlap with deuterium (D+) in the mass-to-charge-state spectrum, thus preventing the direct application of isotopic marking for unambiguous hydrogen analysis. First, we applied an existing method for hydrogen content estimation, using ${\rm H}^ + {/}{\rm H}_2^ +$ ratios obtained from paired deuterated/nondeuterated experiments. These measurements demonstrated sufficient residual uncertainty to motivate exploring an alternative method to accurately estimate hydrogen content. By varying the time between evaporation events, it is then shown that a highly correlated relationship between field evaporation rate and hydrogen content exists and can also be used to predict hydrogen content. This leads to a new method for measuring hydrogen content within the specimen. We combine this extrapolation technique with continuous cycling of the evaporation rate or pulse frequency during an APT experiment. This could enable spatially resolved imaging of hydrogen concentrations despite the presence of a contaminant background hydrogen signal, without the need for deuteration.

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.

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.

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.

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.

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.

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.