Kaustubh Kaluskar

Extracting features buried within high density atom probe point cloud data through simplicial homology

Feature extraction from Atom Probe Tomography (APT) data is usually performed by repeatedly delineating iso-concentration surfaces of a chemical component of the sample material at different values of concentration threshold, until the user visually determines a satisfactory result in line with prior knowledge. However, this approach allows for important features, buried within the sample, to be visually obscured by the high density and volume (~10(7) atoms) of APT data. This work provides a data driven methodology to objectively determine the appropriate concentration threshold for classifying different phases, such as precipitates, by mapping the topology of the APT data set using a concept from algebraic topology termed persistent simplicial homology. A case study of Sc precipitates in an Al-Mg-Sc alloy is presented demonstrating the power of this technique to capture features, such as precise demarcation of Sc clusters and Al segregation at the cluster boundaries, not easily available by routine visual adjustment.

Interactive visualization of APT data at full fidelity

Understanding the impact of noise and incomplete data is a critical need for using atom probe tomography effectively. Although many tools and techniques have been developed to address this problem, visualization of the raw data remains an important part of this process. In this paper, we present two contributions to the visualization of data acquired through atom probe tomography. First, we describe the application of a rendering technique, ray-cast spherical impostors, that enables the interactive rendering of large numbers (as large as 10 million plus) of pixel perfect, lit spheres representing individual atoms. This technique is made possible by the use of a consumer-level graphics processing unit (GPU), and it yields an order of magnitude improvement both in render quality and speed over techniques previously used to render spherical glyphs in this domain. Second, we present an interactive tool that allows the user to mask, filter, and colorize the data in real time to help them understand and visualize a precise subset and properties of the raw data. We demonstrate the effectiveness of our tool through benchmarks and an example that shows how the ability to interactively render large numbers of spheres, combined with the use of filters and masks, leads to improved understanding of the three-dimensional (3D) and incomplete nature of atom probe data. This improvement arises from the ability of lit spheres to more effectively show the 3D position and the local spatial distribution of individual atoms than what is possible with point or isosurface renderings. The techniques described in this paper serve to introduce new rendering and interaction techniques that have only recently become practical as well as new ways of interactively exploring the raw data.

Zooming in on Field Evaporation Behavior: A Time Depending Density Functional Theory Study

The evaporation process is a critical phenomenon in Atom Probe Tomography [1] (APT), an experimental technique for studying structure and chemistry of a large variety of materials such as alloys, doped semiconductors, layered materials, geological and biological materials, among others. This approach has emerged as one of the most powerful techniques to analyze semiconductors and device structures at the sub-nanometer scale [2]. APT evaporates atoms on a surface tip by applying a high electric field and a laser pulse, which are reconstructed based on the information of the detector (X, Y) position and time of flight (tof), giving detailed 3D atomic scale information of the studied structure. Despite the advantages of the technique to provide detailed atomistic information of a sample in real space, there is still a challenge in the reconstruction process [3] of the original sample. Individual ions with their reconstructed coordinates often deviate from the ideal positions and affect the subsequent analysis.

Development of Quantitative Standards for Atom Probe Reconstruction Parameters for Analysis of Interfacial Chemistry

The present work is aimed at developing a standard for defining reconstruction parameters for optimal voxel and chemical thresholds. We develop quantitative techniques for the detection of sharp chemical interfaces from the APT outputs of 3D point cloud and 3D chemical interfaces of continuous geometry. The difficulty lies in mapping discrete data to a continuous output while minimizing the loss in chemical information. In the present work, we develop a novel approach, based on the principles of computational homology, to map the discrete 3D point cloud atomic data to the topology of a continuous chemical interface. The computational homology framework developed can be applied to APT data to get meaningful results and quantify sensitivity of the output on the data reconstruction parameters. To incorporate evaporation physics with chemistry and structure and to provide physical definition of uncertainty in spatially defining phases,