Structure and Growth of Core–shell Nanoprecipitates in Al–Er–Sc–Zr–V–Si High-temperature Alloys

Lightweight Sc-containing aluminum alloys exhibit superior mechanical performance at high temperatures due to core–shell, L12-ordered trialuminide nanoprecipitates. In this study, the structure of these nanoprecipitates was studied, using different transmission electron microscopy (TEM) techniques, for an Al–Er– Sc–Zr–V–Si alloy that was subjected to a two-stage overaging heat treatment. Energy-dispersive X-ray spectroscopy of the spherical Al3(Sc, Zr, Er ,V) nanoprecipitates revealed a core–shell structure with an Sc- and Er-enriched core and a Zr-enriched shell, without a clear V outer shell. This structure is stable up to 72% of the absolute melting temperature of Al for extended periods of time. High-angle annular dark-field scanning TEM was used to image the {100} planes of the nanoprecipitates, demonstrating a homogeneous L12-ordered superlattice structure for the entire nanoprecipitates, despite the variations in the concentrations of solute atoms within the unit cells. A possible growth path and compositional trajectory for these nanoprecipitates was proposed using high-resolution TEM observations, where different rod-like structural defects were detected, which are considered to be precursors to the spherical L12-ordered nanoprecipitates. It is also hypothesized that the structural defects could consist of segregated Si; however, this was not possible to verify with HAADF-STEM because of the small differences in Al and Si atomic numbers. The results herein allow a better understanding of how the Al–Sc alloys’ core–shell nanoprecipitates form and evolve temporally, thereby providing a better physical picture for future atomistic structural mappings and simulations

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

What is the Path to Fast Fault Simulation?

Motivated by the recent advances in fast fault simulation techniques for large combinational circuits, a panel discussion has been organized for the 1988 International Test Conference. This paper is a collective account of the position statements offered by the panelists

On the structure of defects in the Fe7Mo6 μ\mu-Phase

Topologically close packed phases, among them the $\mu$-phase studied here, are commonly considered as being hard and brittle due to their close packed and complex structure. Nanoindentation enables plastic deformation and therefore investigation of the structure of mobile defects in the $\mu$-phase, which, in contrast to grown-in defects, has not been examined yet. High resolution transmission electron microscopy (HR-TEM) performed on samples deformed by nanoindentation revealed stacking faults which are likely induced by plastic deformation. These defects were compared to theoretically possible stacking faults within the $\mu$-phase building blocks, and in particular Laves phase layers. The experimentally observed stacking faults were found resulting from synchroshear assumed to be associated with deformation in the Laves-phase building blocks