PosgenPy: An Automated and Reproducible Approach to Assessing the Validity of Cluster Search Parameters in Atom Probe Tomography Datasets

2021 ◽  
pp. 1-10
Author(s):  
Przemysław Klupś ◽  
Daniel Haley ◽  
Andrew J. London ◽  
Hazel Gardner ◽  
James Famelton ◽  
...  
Keyword(s):  
Atom Probe Tomography ◽  
Spatial Clustering ◽  
Atom Probe ◽  
Parameter Selection ◽  
Material System ◽  
Number Density ◽  
Cluster Number ◽  
Simulated Material ◽  
Parameter Values ◽  
Selection Of

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.

scholarly journals A Gas-Phase Reaction Cell for Modern Atom Probe Systems

2019 ◽  
Vol 25 (2) ◽  
pp. 410-417 ◽  
Author(s):  
Daniel Haley ◽  
Ingrid McCarroll ◽  
Paul A. J. Bagot ◽  
Julie M. Cairney ◽  
Michael P. Moody
Keyword(s):  
Gas Phase ◽  
Atom Probe Tomography ◽  
Atom Probe ◽  
Phase Reaction ◽  
Reaction Cell ◽  
Current Form ◽  
Gas Phase Reaction ◽  
Wide Range ◽  
Gas Interactions ◽  
Selection Of

AbstractIn 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.

Effect of Cu on Nanoscale Precipitation Evolution and Mechanical Properties of a Fe–NiAl Alloy

2017 ◽  
Vol 23 (2) ◽  
pp. 350-359 ◽  
Author(s):  
Qin Shen ◽  
Hao Chen ◽  
Wenqing Liu
Keyword(s):  
Mechanical Properties ◽  
Atom Probe Tomography ◽  
Diffusion Rate ◽  
Atom Probe ◽  
Peak Hardness ◽  
Dramatic Improvement ◽  
Number Density ◽  
Cu Alloy ◽  
Tension Tests ◽  
Nial Alloy

AbstractThe microstructural evolution of precipitation in two model alloys, Fe–NiAl and Fe–NiAl–Cu, was investigated during aging at 500°C for different times using atom probe tomography (APT). The APT results reveal that the addition of Cu effectively increases the number density of NiAl precipitates. This is attributed to Cu promoting the nucleation of NiAl particles by increasing the chemical driving force and decreasing the interfacial energy. The NiAl precipitates of the Fe–NiAl–Cu alloy grow and coarsen at a slower rate than that of the Fe–NiAl alloy, mainly due to the slower diffusion rate of the Cu atoms. The mechanical properties of the two alloys were characterized by Vickers hardness and tension tests. It was found that the addition of Cu results in the formation of core–shell precipitates with a Cu-rich core and a NiAl shell, leading to a dramatic improvement of peak hardness and strength. The effect of Cu on precipitation strengthening is discussed in terms of chemical strength and coherency strength.

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

2021 ◽  
pp. 1-11
Author(s):  
Baptiste Gault ◽  
Benjamin Klaes ◽  
Felipe F. Morgado ◽  
Christoph Freysoldt ◽  
Yue Li ◽  
...  
Keyword(s):  
Atom Probe Tomography ◽  
Atom Probe ◽  
Atomic Scale ◽  
High Entropy Alloys ◽  
Material System ◽  
Field Evaporation ◽  
Ion Imaging ◽  
High Entropy ◽  
Spatial Performance ◽  
Pure Metals

Atom probe tomography (APT) is often introduced as providing “atomic-scale” mapping of the composition of materials and as such is often exploited to analyze atomic neighborhoods within a material. Yet quantifying the actual spatial performance of the technique in a general case remains challenging, as it depends on the material system being investigated as well as on the specimen's geometry. Here, by using comparisons with field-ion microscopy experiments, field-ion imaging and field evaporation simulations, we provide the basis for a critical reflection on the spatial performance of APT in the analysis of pure metals, low alloyed systems and concentrated solid solutions (i.e., akin to high-entropy alloys). The spatial resolution imposes strong limitations on the possible interpretation of measured atomic neighborhoods, and directional neighborhood analyses restricted to the depth are expected to be more robust. We hope this work gets the community to reflect on its practices, in the same way, it got us to reflect on our work.

APT Investigation of Effect of Minor Zr on Precipitation Strength of Al-Sc Alloy

2016 ◽  
Vol 877 ◽  
pp. 245-250 ◽  
Author(s):  
Na Xue ◽  
Hui Song ◽  
Chang Bing Zhou ◽  
Xiao Jiao Wang ◽  
Wen Qing Liu
Keyword(s):  
Aging Time ◽  
Atom Probe Tomography ◽  
Diffusion Rate ◽  
Atom Probe ◽  
Precipitation Strengthening ◽  
Number Density ◽  
Zr Addition ◽  
Zr Alloy ◽  
Zr Alloys

As-cast Al-Sc alloys and Zr-containing Al-Sc-Zr alloys were aged at 300°C for different times, the Al-Sc-Zr alloy showed more excellent precipitation strengthening. The atom probe tomography (APT) was applied to characterize the precipitates in the two alloys, the results show that the precipitates in Al-Sc-Zr alloy is smaller in size and is higher in number density than that in the Al-Sc alloy at same aging time, it is because that the Zr addition reduces the diffusion rate of Sc, and which retains the growth of precipitates and results in the excellent precipitation strengthening of Al-Sc-Zr alloy.

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

2019 ◽  
Vol 25 (2) ◽  
pp. 338-348 ◽  
Author(s):  
Jing Wang ◽  
Daniel K. Schreiber ◽  
Nathan Bailey ◽  
Peter Hosemann ◽  
Mychailo B. Toloczko
Keyword(s):  
Cluster Analysis ◽  
Atom Probe Tomography ◽  
Spatial Clustering ◽  
Atom Probe ◽  
Atomic Density ◽  
Scale Model ◽  
Small Scale ◽  
Physical Parameters ◽  
Structure Property ◽  
Ferritic Alloy

AbstractAtom 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.

scholarly journals The Formation of Nanoparticles and Their Competitive Interaction with Twins during Eutectic Si Growth

Materials ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1404
Author(s):  
Wei Wang ◽  
Fengxiang Guo ◽  
Zhigang Gai ◽  
Tao Zhang ◽  
Jianguo Tang ◽  
...  
Keyword(s):  
Atom Probe Tomography ◽  
Atom Probe ◽  
Competitive Interaction ◽  
Dynamics Simulation ◽  
Ab Initio Molecular Dynamics ◽  
Number Density ◽  
Large Size ◽  
Eutectic Si ◽  
Solid Liquid Interface ◽  
Solid Liquid

In order to investigate the competitive interaction between nanoparticles and twin, the eutectic Si microstructures in Al–10Si (wt. %) base alloys with exclusive and combined addition of Sr and Sb are characterized by combined TEM and atom probe tomography (APT). The chemical short range order in Sb–Sb and Sb–Sr pairs is revealed by ab initio molecular dynamics simulation, which promotes the formation of clusters and nanoparticles. The coexistence of nanoparticles and twins is observed in Sb containing alloys, with a negative correlation in the corresponding number density, owing to the competitive stacking of precursors and individual atoms at the solid–liquid interface. Large size particles around 70 nm with a uniform distribution of Sr atoms are formed in Al–10Si–0.35Sb–0.015Sr (wt. %) alloys, due to the precursor aggregation and homogeneous nucleation in the droplets that nucleation are depressed. A model for the formation of nanoparticles and their interaction with twins is proposed.

The Maximum Separation Cluster Analysis Algorithm for Atom-Probe Tomography: Parameter Determination and Accuracy

2014 ◽  
Vol 20 (6) ◽  
pp. 1662-1671 ◽  
Author(s):  
Eric Aimé Jägle ◽  
Pyuck-Pa Choi ◽  
Dierk Raabe
Keyword(s):  
Cluster Analysis ◽  
Atom Probe Tomography ◽  
Atom Probe ◽  
Parameter Determination ◽  
Separation Algorithm ◽  
Cluster Number ◽  
Data Set ◽  
Surrounding Matrix ◽  
Precipitation Phenomena ◽  
Maximum Separation

AbstractAtom-probe tomography is a materials characterization method ideally suited for the investigation of clustering and precipitation phenomena. To distinguish the clusters from the surrounding matrix, the maximum separation algorithm is widely employed. However, the results of the cluster analysis strongly depend on the parameters used in the algorithm and hence, a wrong choice of parameters leads to erroneous results, e.g., for the cluster number density, concentration, and size. Here, a new method to determine the optimum value of the parameter dmax is proposed, which relies only on information contained in the measured atom-probe data set. Atom-probe simulations are employed to verify the method and to determine the sensitivity of the maximum separation algorithm to other input parameters. In addition, simulations are used to assess the accuracy of cluster analysis in the presence of trajectory aberrations caused by the local magnification effect. In the case of Cu-rich precipitates (Cu concentration 40–60 at% and radius 0.25–1.0 nm) in a bcc Fe–Si–Cu matrix, it is shown that the error in concentration is below 10 at% and the error in radius is <0.15 nm for all simulated conditions, provided that the correct value for dmax, as determined with the newly proposed method, is employed.

scholarly journals Carbide Precipitation in a Low Alloyed Steel during Aging Studied by Atom Probe Tomography and Thermodynamic Modeling

Metals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2009
Author(s):  
Mattias Thuvander ◽  
Hans Magnusson ◽  
Ulrika Borggren
Keyword(s):  
Atom Probe Tomography ◽  
Precipitation Hardening ◽  
Atom Probe ◽  
Carbide Precipitation ◽  
Martensitic Structure ◽  
Number Density ◽  
High Number Density ◽  
Molybdenum Carbides ◽  
The Matrix ◽  
Low Alloyed Steel

Carbide precipitation in martensitic low alloyed steels contributes to the mechanical properties through precipitation hardening. A high number density of carbides is desired to maximize the hardening effect, which is achieved through the precipitation of carbides on the dislocations in the martensitic structure. In this study, the nucleation, growth, and coarsening of vanadium and molybdenum carbides during aging at 600 °C for periods up to four weeks were investigated. The work covers characterization with atom probe tomography, which showed that the nucleation of V and Mo rich MC/M2C carbides takes place on dislocations. The growth of these carbides proceeds by the diffusion of elements to the dislocations, which has been modeled using Dictra software, confirming the rate of the reaction as well as the depletion of carbide formers in the matrix. For longer aging times, particle coarsening will decrease the number density of particles with a transition from dislocation-based carbides to separate rounded carbides.

Comparison of Compositional and Morphological Atom-Probe Tomography Analyses for a Multicomponent Fe-Cu Steel

2007 ◽  
Vol 13 (4) ◽  
pp. 272-284 ◽  
Author(s):  
R. Prakash Kolli ◽  
David N. Seidman
Keyword(s):  
Atom Probe Tomography ◽  
Atom Probe ◽  
Separation Distance ◽  
Distribution Functions ◽  
Precipitate Size ◽  
Threshold Method ◽  
Precipitate Size Distribution ◽  
Envelope Method ◽  
Concentration Threshold ◽  
Selection Of

A multicomponent Fe-Cu based steel is studied using atom-probe tomography. The precipitates are identified using two different methodologies and subsequent morphological and compositional results are compared. The precipitates are first identified using a maximum separation distance algorithm, the envelope method, and then by a concentration threshold method, an isoconcentration surface. We discuss in detail the proper selection of the parameters needed to delineate precipitates utilizing both methods. The results of the two methods exhibit a difference of 44 identified precipitates, which can be attributed to differences in the basis of both methods and the sensitivity of our results to user-prescribed parameters. The morphology of the precipitates, characterized by four different precipitate radii and precipitate size distribution functions (PSDs), are compared and evaluated. A variation of less than ∼8% is found between the different radii. Two types of concentration profiles are compared, giving qualitatively similar results. Both profiles show Cu-rich precipitates containing Fe with elevated concentrations of Ni, Al, and Mn near the heterophase interfaces. There are, however, quantitative disagreements due to differences in the basic foundations of the two analysis methods.

Atom Probe Tomographic Characterization of Nanoscale Cu-Rich Precipitates in 17-4 Precipitate Hardened Stainless Steel Tempered at Different Temperatures

2017 ◽  
Vol 23 (2) ◽  
pp. 340-349 ◽  
Author(s):  
Zemin Wang ◽  
Xulei Fang ◽  
Hui Li ◽  
Wenqing Liu
Keyword(s):  
Stainless Steel ◽  
Interfacial Energy ◽  
Atom Probe Tomography ◽  
Atom Probe ◽  
Number Density ◽  
The Matrix ◽  
Different Temperatures

AbstractThe formation of copper-rich precipitates of 17-4 precipitate hardened stainless steel has been investigated, after tempering at 350–570°C for 4 h, by atom probe tomography (APT). The results reveal that the clusters, enriched only with Cu, were observed after tempering at 420°C. Segregation of Ni, Mn to the Cu-rich clusters took place at 450°C, contributing to the increased hardening. After tempering at 510°C, Ni and Mn were rejected from Cu-rich precipitates and accumulated at the precipitate/matrix interfaces. Al and Si were present and uniformly distributed in the precipitates that were <1.5 nm in radius, but Ni, Mn, Al, and Si were enriched at the interfaces of larger precipitates/matrix. The proxigram profiles of the Cu-rich precipitates formed at 570°C indicated that Ni, Mn, Al, and Si segregated to the precipitate/matrix interfaces to form a Ni(Fe, Mn, Si, Al) shell, which significantly reduced the interfacial energy as the precipitates grew into an elongated shape. In addition, the number density of Cu-rich precipitates was increased with the temperature elevated from 350 up to 450°C and subsequently decreased at higher temperatures. Also, the composition of the matrix and the precipitates were measured and found to vary with temperature.

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