title: Automated voxelization of 3D atom probe data through kernel density estimation.
abstract: Identifying nanoscale chemical features from atom probe tomography (APT) data routinely involves adjustment of voxel size as an input parameter, through visual supervision, making the final outcome user dependent, reliant on heuristic knowledge and potentially prone to error. This work utilizes Kernel density estimators to select an optimal voxel size in an unsupervised manner to perform feature selection, in particular targeting resolution of interfacial features and chemistries. The capability of this approach is demonstrated through analysis of the γ / γ' interface in a Ni-Al-Cr superalloy.
authors.affiliation: Institute of Combinatorial Discovery, Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011-2300, USA.
authors.forename: Srikant
authors.initials: S
authors.lastname: Srinivasan
authors.affiliation: Institute of Combinatorial Discovery, Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011-2300, USA.
authors.forename: Kaustubh
authors.initials: K
authors.lastname: Kaluskar
authors.affiliation: Institute of Combinatorial Discovery, Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011-2300, USA.
authors.forename: Santoshrupa
authors.initials: S
authors.lastname: Dumpala
authors.affiliation: Institute of Combinatorial Discovery, Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011-2300, USA.
authors.forename: Scott
authors.initials: S
authors.lastname: Broderick
authors.affiliation: Institute of Combinatorial Discovery, Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011-2300, USA. Electronic address: krajan@iastate.edu.
authors.forename: Krishna
authors.initials: K
authors.lastname: Rajan
keywords: APT; Informatics; Interfaces; Kernel density estimation; Ni Alloy