Application software for data analysis for three-dimensional atom probe microscopy

Hellman, Olof C.; Vandenbroucke, J.; Rivage, John Blatz du; Seidman, David N.

doi:10.1016/s0921-5093(01)01887-1

Cited by 67 publications

(39 citation statements)

References 7 publications

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“…The 3DAP microscope investigations were performed using a 19% pulse fraction, at 60 K, and a pulse frequency of 1.5 kHz. A custom software program, ADAM 1.5 [7,8], developed at Northwestern University, was used for analyzing the 3DAP microscopy data.…”

Section: Methodsmentioning

confidence: 99%

“…1 (see on-line version of this paper for a colored figure). The interface, represented as a green surface, is identified by an isoconcentration surface defined by a 55 at.% Ti concentration threshold [7,8]. Concentrations of all identified elements are then measured at subnanometer distances from either side of the interface and plotted in the form of a proximity histogram (or proxigram for short) [7].…”

Section: Chemical Analysis: Three-dimensionalmentioning

confidence: 99%

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Atomic Scale Chemistry of α₂/ Interfaces in a Multi-Component TiAl Alloy

2004

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Abstract. We report on the distribution of micro-alloying elements in a multi-component TiAl-based alloy. The specimen contains 3 at.% Nb, 1.5 at.% Cr, 0.5 at.% Mn, 0.6 at.% (W + Hf + Zr), and 0.2 at.% each of B, C, and O. The distributions of all micro-alloying elements with respect to the heterophase interface between α 2 and γ lamellae are analyzed with a three-dimensional atom-probe (3DAP) microscope. All the elements partition except boron, which resides primarily in boride precipitates. Oxygen, C, Mn, and Cr partition to the α 2 -phase, whereas Nb and Zr partition to the γ -phase. Both W and Hf exhibit excess concentration values within ca. 7 nm of the lamellar interface in the α 2 -phase, and their near interfacial excesses are 0.26 and 0.35 atoms nm -2 , respectively.

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Section: Methodsmentioning

confidence: 99%

Section: Chemical Analysis: Three-dimensionalmentioning

confidence: 99%

Atomic Scale Chemistry of α₂/ Interfaces in a Multi-Component TiAl Alloy

2004

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“…Visualization and quantitative evaluation of datasets were performed with the Imago Visualization and Analysis Software (IVAS ) and with ADAM 1.5, a custom software application developed at Northwestern University. [37] Compositional analyses of the precipitates, their heterophase interfaces, and matrix were performed with the proximity histogram method (proxigram for short), giving compositional profiles with respect to distance from an isoconcentration surface. [37][38][39] The Cu-rich precipitates were delineated by a 5 at.…”

Section: E Atom-probe Tomographymentioning

confidence: 99%

“…[37] Compositional analyses of the precipitates, their heterophase interfaces, and matrix were performed with the proximity histogram method (proxigram for short), giving compositional profiles with respect to distance from an isoconcentration surface. [37][38][39] The Cu-rich precipitates were delineated by a 5 at. pct Cu isoconcentration surface.…”

Section: E Atom-probe Tomographymentioning

confidence: 99%

High-Strength Low-Carbon Ferritic Steel Containing Cu-Fe-Ni-Al-Mn Precipitates

Vaynman

Isheim

Kolli³

et al. 2008

Metall Mater Trans A

110

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An investigation of a low-carbon, Fe-Cu-based steel, for Naval ship hull applications, with a yield strength of 965 MPa, Charpy V-notch absorbed impact-energy values as high as 74 J at -40°C, and an elongation-to-failure greater than 15 pct, is presented. The increase in strength is derived from a large number density (approximately 10 23 to 10 24 m -3 ) of copper-iron-nickelaluminum-manganese precipitates. The effect on the mechanical properties of varying the thermal treatment was studied. The nanostructure of the precipitates found within the steel was characterized by atom-probe tomography. Additionally, initial welding studies show that a brittle heat-affected zone is not formed adjacent to the welds.

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“…[22] with permission from The Royal Society of Chemistry structure and to more precisely identify features (for example, precipitates and interfaces) from the 3D data [23][24][25][26][27][28][29][30]. Because data is in the format of discrete points in some metric space, i.e., a point cloud, many data mining algorithms, which have been developed, are applicable to extract the geometric information embedded in the data [31][32][33][34]. Nevertheless, those geometric-based methods have certain limitations when being applied to solve the problems in atom probe data.…”

Section: Characteristics Of Geometric-based Data Analysis Methodsmentioning

confidence: 99%

Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomography Images

2018

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Atom probe tomography (APT) represents a revolutionary characterization tool for materials that combine atomic imaging with a time-of-flight (TOF) mass spectrometer to provide direct space three-dimensional, atomic scale resolution images of materials with the chemical identities of hundreds of millions of atoms. It involves the controlled removal of atoms from a specimen's surface by field evaporation and then sequentially analyzing them with a position sensitive detector and TOF mass spectrometer. A paradox in APT is that while on the one hand, it provides an unprecedented level of imaging resolution in three dimensions, it is very difficult to obtain an accurate perspective of morphology or shape outlined by atoms of similar chemistry and microstructure. The origins of this problem are numerous, including incomplete detection of atoms and the complexity of the evaporation fields of atoms at or near interfaces. Hence, unlike scattering techniques such as electron microscopy, interfaces appear diffused, not sharp. This, in turn, makes it challenging to visualize and quantitatively interpret the microstructure at the "meso" scale, where one is interested in the shape and form of the interfaces and their associated chemical gradients. It is here that the application of informatics at the nanoscale and statistical learning methods plays a critical role in both defining the level of uncertainty and helping to make quantitative, statistically objective interpretations where heuristics often dominate. In this chapter, we show how the tools of Topological Data Analysis provide a new and powerful tool in the field of nanoinformatics for materials characterization.

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Application software for data analysis for three-dimensional atom probe microscopy

Cited by 67 publications

References 7 publications

Atomic Scale Chemistry of α₂/ Interfaces in a Multi-Component TiAl Alloy

Atomic Scale Chemistry of α₂/ Interfaces in a Multi-Component TiAl Alloy

High-Strength Low-Carbon Ferritic Steel Containing Cu-Fe-Ni-Al-Mn Precipitates

Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomography Images

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Application software for data analysis for three-dimensional atom probe microscopy

Cited by 67 publications

References 7 publications

Atomic Scale Chemistry of α2/ Interfaces in a Multi-Component TiAl Alloy

Atomic Scale Chemistry of α2/ Interfaces in a Multi-Component TiAl Alloy

High-Strength Low-Carbon Ferritic Steel Containing Cu-Fe-Ni-Al-Mn Precipitates

Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomography Images

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Product

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Atomic Scale Chemistry of α₂/ Interfaces in a Multi-Component TiAl Alloy

Atomic Scale Chemistry of α₂/ Interfaces in a Multi-Component TiAl Alloy