Chemical composition modification of casting aluminium alloys for engine applications

The research activities were focused on evaluating the effect of Mo addition to mechanical properties and microstructure of A354 aluminium casting alloy. Samples, with increasing amount of Mo, were produced and heat treated. After heat treatment and exposition to high temperatures samples underwent microstructural and chemical analyses, hardness and tensile tests. The collected data led to the optimization of both casting parameters, for obtaining a homogeneous Mo distribution in the alloy, and heat treatment parameters, allowing the formation of Mo based strengthening precipitates stable at high temperature. Microstructural and chemical analyses highlighted how Mo addition in percentage superior to 0.1% wt. can modify the silicon eutectic morphology and hinder the formation of iron based β intermetallics. High temperature exposure curves, instead, showed that after long exposition hardness is slightly influenced by heat treatment while the effect of Mo addition superior to 0,3% is negligible. Tensile tests confirmed that the addition of 0.3%wt Mo induces an increase of about 10% of ultimate tensile strength after high temperature exposition (250°C for 100h) while heat treatments have slight influence on mechanical behaviour. These results could be exploited for developing innovative heat treatment sequence able to reduce residual stresses in castings produced with A354 modified with Mo.

A biophysical model for valence-based navigational learning: the role of D-Serine

Recent experiments have revealed the fundamental importance of neuromodulatory action on activity-dependent synaptic plasticity underlying behavioral learning and spatial memory formation. Neuromodulators affect synaptic plasticity through the modification of the dynamics of receptors on the synaptic membrane. However, chemical substances other than neuromodulators, such as receptors co-agonists, can influence the receptors' dynamics and thus participate in determining plasticity. Here we focus on D-serine, which has been observed to affect the activity thresholds of synaptic plasticity by co-activating NMDA receptors. We use a computational model for spatial value learning with plasticity between two place cell layers. The D-serine release is CB1R mediated and the model reproduces the impairment of spatial memory due to the astrocytic CB1R knockout for a mouse navigating in the Morris water maze. The addition of path-constraining obstacles shows how performance impairment depends on the environment's topology. The model can explain the experimental evidence and produce useful testable predictions to increase our understanding of the complex mechanisms underlying learning.