| 查看: 655 | 回复: 0 | |||
huanying11863金虫 (正式写手)
|
[交流]
德国可生物吸收植入物腐蚀及缓蚀剂研究博士生机会（2个PhD全奖学金位置）
|
|
Project 1: Influence of WAAM parameters on localized corrosion of Mg alloys for bioabsorbable implant applications. Objectives This work will focus on understanding the influence of Cold Metal Transfer (CMT) WAAM 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, including removal of corrosion products before accessing the extent of localized corrosion by 3D-profilometry. 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 metallic scaffolds. A unique combination of spatially resolved electrochemical and surface characterization methods will characterize Mg scaffolds exposed to the simulated body fluid environment. Collect a data set for correlating the fabrication process parameters with degradation profile and mechanical properties. Develop a data-driven model using ML approach for establishing the process-structure-property relationships. Identify the underlying driving forces of localized corrosion to gain the control over it. Develop the optimal material (degradation profile and mechanical properties) by fine-tuning the process parameters Project 2: Development of corrosion resistant surfaces on AM metals by experimental and data-driven selection of corrosion inhibitors. Objectives The proposed project will provide the foundation to train quantitative structure-property relationship models to predict the corrosion inhibition performance of untested small organic molecule corrosion inhibitors. The objectives are: A corresponding database of concentration-dependent corrosion inhibition efficiencies for AM-manufactured materials will be generated using a custom-made robotic testing platform. Subsequently, 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 throughout the implementation of the project. Lastly, the most promising inhibitors will be impregnated into a coating matrix to evaluate their performance in a coating system. 项目的详细信息、奖学金内容及申请窗口：https://duramat-project.be/recruitment/ 如需帮助或咨询，请联系：haijie.tong@hereon.de |
回复此楼» 猜你喜欢
上海交通大学纳米器件和材料研究组招聘教师和博士后
已经有0人回复
-
山东大学类脑计算与器件方向招收2026年9月入学的博士研究生
已经有0人回复
-
半导体科学与信息器件论文润色/翻译怎么收费?
已经有186人回复
-
电镀/电铸模拟分析
已经有0人回复
-
上海交通大学集成电路学院纳米器件和材料研究组招收博士生
已经有0人回复
-
上海交通大学集成电路学院纳米器件和材料研究组招聘教师和博士后
已经有0人回复
-
【CSC博士招生】西班牙CSIC–ICMM | 2D材料/量子电子/热输运方向 | 2025
已经有0人回复
-
求SOFC燃料电池的化工系统流程设计的大神指点！
已经有0人回复
-
上海交通大学集成电路学院纳米电子和光电器件研究组招收博士生
已经有1人回复
-
上海交通大学集成电路学院纳米电子和光电器件研究组招收博士生
已经有1人回复
-
上海交通大学纳米器件和材料研究组招聘博士后和教师
已经有0人回复
