Public defence in Engineering Physics, M.Sc. Aslam Shaikh

Title of the thesis: New stochastic and computational approaches in atom probe tomography

Thesis defender: Aslam Shaikh
Opponent: Professor Mattias Thuvander, Chalmers University of Technology, Sweden
Custos: Professor Mikko Alava, Aalto University School of Science

This doctoral thesis advances our understanding of atom probe tomography (APT), a microanalysis technique used to map materials atom by atom in three dimensions, and explores how its accuracy can be improved. APT is important in materials science because it helps researchers observe the smallest structural and chemical features of a material. These features have a direct impact on its performance, durability, and reliability.

The purpose of the study was to improve understanding of the physical process behind APT, known as field evaporation. Existing reconstruction methods usually assume that atoms leave the surface in a simple, independent, and predictable way. This research shows that the process is instead partly random and strongly influenced by local atomic surroundings, surface changes, and collective effects between neighboring atoms.

The thesis is relevant to both atom probe research and the wider field of materials characterization because it addresses a fundamental limitation in how experimental data is obtained and interpreted. APT is largely concerned with the reconstruction of this data. A better understanding of field evaporation process can improve the accuracy and reliability of this reconstruction with implications for atomic-scale analysis of metals, semiconductors, energy materials, and other advanced material systems.

The main results show, first, that small random perturbations during ion emission are an intrinsic part of field evaporation and help explain detector artifacts seen in experiments. Second, in complex materials, evaporation does not proceed as isolated events but as correlated, avalanche-like bursts with spatial and temporal correlations. Third, the thesis introduces a new probabilistic reconstruction method based on Gaussian process regression that can learn the correlations in the detector data to produce more accurate three-dimensional reconstructions than conventional geometric methods.

The advancements in this thesis open a path toward more physically consistent atom probe simulations and more accurate reconstruction algorithms. In the long term, this may support the design of better materials by giving researchers a more faithful picture of material structure and composition.

Keywords: atom probe tomography, correlated field evaporation, sample reconstruction

Contact information: https://www.linkedin.com/in/aslamshaikh9911/ 

Thesis available for public display 7 days prior to the defence at Aalto University's public display page.