Techniques in Atom Probe Tomography

New Directions in Data Analysis for Atom Probe Tomography (APT)
APT reconstructions are often visually striking, revealing exciting new perspectives on microstructural features such as precipitates and phase interfaces. However, the sheer volume of data that can be accumulated by experiment combined with the subtle and/or fine-scaled nature of certain nanostructure often leave key features of interest unresolved to visual inspection. It is imperative that the development of sophisticated data mining tools, specific to multi-gigabyte 3-D atom probe data sets, keep pace with the recent experimental advances.

To maximise the vast potential of APT, data analysis methods must be specialised for the assortment of nanostructure types investigated, and must scale well with the rapidly increasing size of the reconstructions. Analysis techniques being developed for the characterisation of nanostructure include; grid-based frequency distributions, clustering algorithms, nearest neighbour distributions and spatial distribution maps. Research is also ongoing into improving the computational efficiency of new algorithms employing sophisticated data voxelisation, parallel computing and supercomputing techniques to the analysis of large data sets.

Data mining techniques will play a critical role in the development of quantitative structure activity relationships, offering far-reaching opportunities for the design of new materials and the optimisation of their performance.

Investigators: , , ;
PhD Student: (thesis title: Quantitative Atom Probe Tomography – Understanding bonding in Cold-Spray-Formed Hybrid Nanomaterials).


Computational Techniques in Nanostructural Analysis
The form of APT data closely corresponds to that generated by computer simulation. With knowledge of experimental parameters such as detector efficiency and spatial resolution it is possible produce simulations that closely complement the nature of experimental APT data sets. The capacity to develop theoretical modeling techniques to both validate and lead future APT will continue to become an increasingly significant component of APT research. Further, it is almost certain that computer simulations modeling the physics of the entire experimental process will be critical to the development of the next generation of APT reconstruction algorithms.

A key computer simulation technique is Kinetic Monte Carlo (KMC). This technique provides both a significant efficiency increase and more importantly a realistic time scale for the simulation based on atom-vacancy exchange transition rates in light alloys. KMC techniques have also been applied to the investigation of dopant diffusion pathways under various implantation and annealing conditions. Other simulation techniques include, Molecular Dynamics (MD), ab initio methods, and Phase Field models for the case analysis of the evolution of larger complex microstructure. The combination of 3-D atomistic APT digital data sets and computational atomistic simulations is already providing new insights into the ways that materials work.

Investigators: , , ;
PhD Student: (thesis title: Quantitative Atom Probe Tomography – Understanding bonding in Cold-Spray-Formed Hybrid Nanomaterials).


New Approaches to Reconstruction in Atom Probe Tomography
Many material properties derive ultimately from atomic structure. Measurement of structure likewise underpins much of modern technological advancement. Explicit knowledge of this structure and composition in three dimensions enables a quantitative interpretation of material function, which is vital for the development of novel materials and understanding of natural matter. A technique capable of supplying such information for substantial volumes of material would represent the ultimate in microscopy. It can be argued that atom probe tomography (APT) is currently the closest technology for delivering such a promise.

State-of-the-art APT can address a broad range of unique scientific and industrial problems, however, sources of systematic error exist, which primarily relate to reconstruction artefacts. As evidenced by the most recent APT literature, understanding these detrimental phenomena is necessary to improve the APT method beyond the significant technological advancements that have occurred to date. This project will address some of these APT reconstruction issues by combining simulation with experiment to develop generic algorithms for improving APT reconstruction.

Investigators: ,


Atom Probe Tomography of Less Conductive Materials
A picosecond laser device has been implemented on the latest atom probe in order to open the application field to poorly conducting materials or insulators. The aim of this project is to explore these new opportunities, studying new ways of specimen preparation (i.e. FIB, ions beam) and to analyse the results using the data mining tools developed at the EMU.

Investigator:


New Approaches to Understanding Grain Boundary Chemistry
Thermomechanical processing of metals relies on the knowledge of the migratory behaviour of grain boundaries, which is strongly affected by elemental segregation in the grain boundary region. This project aims to determine the relationship between solute atmospheres at grain boundaries and the rate of grain boundary migration during annealing in a number of key alloy systems, including nanocrystalline aluminium alloys, TiSiN and Ni-based superalloys. A new approach that combines atom probe tomography (APT) with transmission electron microscopy (TEM) is being developed that allows us to obtain both detailed structural information and precise, nanoscale compositional data from grain boundaries in three dimensions.

Investigator:
PhD Student: (thesis title: Understanding Grain Boundary Chemistry through Advanced Microscopy).
Collaborator: , Imago Scientific Instruments, Madison, WI, USA.