清華大學材料科學與工程研究院《材料科學論壇》學術報告

報告時間：2024年4月16日上午10:30

報告人：Prof. Pedro E. J. Rivera-Diaz-del-Castillo（Royal Academy of Engineering Research Chair, Director of Research, Faculty of Engineering and Physical Sciences, University of Southampton）

報告地點：清華大學逸夫技術科學樓A205學術報告廳

邀請人：陳浩老師

Physical and data-driven modelling approaches for the design of immiscible joints: welding, functional grading, and alloy design

報告簡介：

A common feature shared by the processes of welding, additive manufacturing, and functionally graded materials is the provision of a localised source of energy, the use of alloys amenable to concentrated heating, rapid heating/cooling, and the adoption of dissimilar materials. Miscibility is the property of two substances to mix in all proportions forming a homogeneous mixture or solution; miscible alloys have shaped manufacturing technology since metals started to be combined. Joining immiscible alloys represent a great technological and commercial opportunity; this can be achieved by adding a third surrogate alloy or element to promote the bond.

In this talk, we consider three practical cases of alloy design for immiscible systems: (1) The welding of magnesium with steel alloys mediated by a copper. (2) Functional grading of titanium and copper alloys in horizontal laser powder bed fusion. (3) Grading strategies to additively manufacture nickel-based superalloys with titanium alloys mediated by pure copper. General observations of these cases are the need to quantify energy absorption and temperature distributions, the formation and inhibition of specific intermetallic compounds, and solute redistribution. The three successful cases of alloy joining/grading are reviewed in light of deep learning and physical modelling strategies to discover a broad set or principles and approaches for immiscible multi-material alloy design.

The presenter also takes the opportunity to introduce the world-class characterisation and modelling facilities at the University of Southampton, putting them in the context of our research in additive manufacturing.