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)
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
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…