Effect of various dopant elements on primary graphite growth

Five spheroidal graphite cast irons were investigated, a usual ferritic grade and four pearlitic alloys containing Cu and doped with Sb, Sn and Ti. These alloys were remelted in a graphite crucible, leading to volatilization of the magnesium added for spheroidization and to carbon saturation of the liquid. The alloys were then cooled down and maintained at a temperature above the eutectic temperature. During this step, primary graphite could develop showing various features depending on the doping elements added. The largest effects were that of Ti which greatly reduces graphite nucleation and growth, and that of Sb which leads to rounded agglomerates instead of lamellar graphite. The samples have been investigated with secondary ion mass spectrometry to enlighten distribution of elements in primary graphite. SIMS analysis showed almost even distribution of elements, including Mg and Al (from the inoculant) in the ferritic grade, while uneven distribution was evident in all doped alloys. Investigations are going on to clarify if the uneven distribution is associated with structural defects in the graphite precipitates

From self-descriptions (SD) to self-recommendations (SR): Evolving Gaia-X for the future European economy

The European decentralized-organized data-infrastructure ecosystem Gaia-X faces the challenge of initiating, maintaining, and intensifying data exchange between data providers and data consumers in all its Gaia-X data exchange domains to contribute significantly to the future viability of the European economy. The overall success of Gaia-X would enhance the innovative power and competitiveness of European companies and reduce their dependence on American and Chinese platform companies. This paper analyzes how the Big Data era affects the design of centralized-organized and decentralized-organized platforms and applies the findings to Gaia-X. It proposes to extend the Self-Descriptions (SD) already firmly embedded in Gaia-X with so-called Self-Recommendations (SR) because, in this way, the decentralized-organized data-infrastructure ecosystem Gaia-X can better express its advantages over centralized-organized platform companies