Gault, B.: Can machine learning bring atom probe microscopy closer to analytical atomic-scale tomography. 12th International Symposium on Atomic Level Characterizations for New Materials and Devices (ALC 19), Kyoto, Japan (2019)
Kasian, O.; Schweinar, K.; Cherevko, S.; Gault, B.; Mayrhofer, K. J. J.: Correlating Atomic Scale Structure with Reaction Mechanisms: Electrocatalytic Evolution of Oxygen. 70th Annual Meeting of the International Society of Electrochemistry, Durban, South Africa (2019)
Gault, B.: An introduction to atom probe tomography: from fundamentals to atomic-scale insights into engineering materials. Rolls Royce Lunchtime Seminar, Derby, UK (2019)
Gault, B.: An introduction to atom probe tomography: from fundamentals to atomic-scale insights into engineering materials. Seminar, University of Manchester, Manchester, UK (2019)
Gault, B.: An introduction to atom probe tomography: from fundamentals to atomic-scale insights into engineering materials. Seminar, University of British Columbia, Vancouver, BC, Canada (2019)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Electron channelling contrast imaging (ECCI) is a powerful technique for observation of extended crystal lattice defects (e.g. dislocations, stacking faults) with almost transmission electron microscopy (TEM) like appearance but on bulk samples in the scanning electron microscope (SEM).