Publication References

1.
Zirong Peng, François Vurpillot, Pyuck-Pa Choi, Yujiao Li, Dierk Raabe, and Baptiste Gault, "On the detection of multiple events in atom probe tomography," Ultramicroscopy 189, 54-60 (2018).
2.
Alisson Kwiatkowski da Silva, Dirk Ponge, Zirong Peng, Gerhard Inden, Y. Lu, Andrew J. Breen, Baptiste Gault, and Dierk Raabe, "Phase nucleation through confined spinodal fluctuations at crystal defects evidenced in Fe–Mn alloys," Nature Communications 9 (1), 1137 (2018).
3.
Shyam Katnagallu, Baptiste Gault, Blazej Grabowski, Jörg Neugebauer, Dierk Raabe, and Gholamali Ali Nematollahi, "Advanced data mining in field ion microscopy," Materials Characterization , 1-12 (2018).

Method developments in field ion emission microscopy techniques

The project focuses on development and design of workflows, which enable advanced processing and analyses of various data obtained from different field ion emission microscope techniques such as field ion microscope (FIM), atom probe tomography (APT), electronic FIM (e-FIM) and time of flight enabled FIM (tof-FIM).

APT is used regularly by the scientists at our institute, and often requires an advanced analysis which are not provided by the proprietary analysis software. As an example, the identification of interfaces such as grain boundaries, and determining their five crystallographic degrees of freedom is often a useful analysis. Creating accurate APT reconstructions based on complementary electron microscope images of the specimen or using Fourier analysis is also a critical step towards maximising the amount of information that can be extracted from one APT run. In-plane compositional information and Gibbsian interfacial excess of grain boundary are another invaluable information for material scientists. Analysis routines to retrieve such information are being developed as a part of this project. Apart from that increasing interest in FIM, has also demanded the development of analysis routines for FIM data. Novel experiments involving challenging materials and combining correlative techniques, are also addressed in the project. Often such challenging data involves invoking advanced data mining analyses and machine learning algorithms. The project on a broad level focuses building bridges between experiments, data mining, simulations and laying pathways towards novel combinations of existing field ion emission microscopy techniques and also other characterization techniques.

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