Job offer for MSCA DN project “DurAMat”
“Sustainable production, processing and modelling of durable additive manufactured materials for enhanced performance and long-term service in complex environments.”
DC4 - Influence of WAAM parameters on localized corrosion of Mg alloys for bioabsorbable implant applications.
Host: Helmholtz Centrum HEREON, Geesthacht, Germany, with PhD awarded by Kiel University, Kiel, Germany
Objectives: This work will focus on machine-learning guided development of evenly degrading magnesium alloys for bioresorbable implants. In particular, we aim at understanding the influence of WAAM (Wire-Arc-Additive-Manufacturing) fabrication process parameters (e.g., wire composition, diameter, arc discharge voltage and time, cooling rate) on the degradation profile of produced metallic materials (rate and especially the extent of localized corrosion). The aim is to establish relevant process-structure-property relationship and identify the optimal fabrication parameters for uniformly degrading Mg alloys without compromising the mechanical properties. Samples produced will be tested using custom-made Robotic Testing Platform. A data-driven machine-learning model will be developed to determine the impact of the individual process parameters on the selected set of target properties and validated for predicting the properties of untested material. Mechanistic understanding of the driving forces of localized corrosion will be achieved by performing model experiments on selected magnesium scaffolds. A unique combination of spatially resolved electrochemical and surface characterization methods will characterize Mg scaffolds exposed to the simulated body fluid environment.
Research stays are planned at NOVA University Lisbon (Portugal), RISE (Sweden) and Cortronik (Germany).
Supervisors: Prof. Dr. Mikhail Zheludkevich, Dr. Sviatlana Lamaka and Dr. Christian Feiler.
DC9 - Development of corrosion resistant surfaces on AM metals by experimental and data-driven selection of corrosion inhibitors.
Host: Helmholtz Centrum HEREON, Geesthacht, Germany, with PhD awarded by Kiel University, Kiel, Germany
Objectives: This work will focus on data-driven discovery of new corrosion inhibitors for additively manufactured aluminum alloys. A database of corrosion inhibition efficiencies for additively-manufactured aluminum alloy will be generated using a custom-made Robotic Testing Platform. The molecular structure of the used corrosion inhibitors will be encoded to generate a database of input features for training of a predictive quantitative structure-relationship model. Following an active learning approach, the training database and the robustness of the developed machine learning model will be improved. The most promising inhibitors will be impregnated into a coating matrix to evaluate their performance in a coating system.
Research stays are planned at Vrije Universiteit Brussel (Belgium), Smallmatek (Portugal) and BASF (Germany).
Supervisors: Prof. Dr. Mikhail Zheludkevich, Dr. Sviatlana Lamaka and Dr. Christian Feiler.