Solidification Cracking Susceptibility of Stainless Steels: New Test and Explanation

The susceptibility of austenitic, ferritic, and duplex stain-less steels to solidification cracking was evaluated by the new Transverse Motion Weldability (TMW) test. The focus was on austenitic stainless steels. 304L and 316L were least susceptible, 321 was significantly more susceptible, and 310 was much more susceptible. However, some 321 welds were even less susceptible than 304L welds. These 321 welds were found to have much finer grains to better resist solidification cracking. Quenching 321 during welding revealed spontaneous grain refining could occur by heterogeneous nucleation. For 304L, 316L, and 310, a new explanation for the susceptibility was proposed based on the continuity of the liquid between columnar dendrites; a discontinuous, isolated liquid allows bonding between dendrites to occur early to better resist cracking. In 304L and 316L, the dendrite-boundary liquid was discontinuous and isolated, as revealed by quenching. The liquid was likely depleted by both fast back diffusion into -dendrites (body-centered cubic) and the L +  + reaction, which consumed L while forming . In 310, however, the dendrites were separated by a continuous liquid that prevented early bonding between them. Back diffusion into -dendrites (face-centered cubic) was much slower, and the L +  + reaction formed little . Quenching also revealed skeletal/lacy formed in 304L and 316L well after solidification ended; thus, skeletal/lacy did not resist solidification cracking, as had been widely believed for decades. The TMW test further demonstrated that both more sulfur and slower welding can increase susceptibility.

Detection of Dendritic Spines Using Wavelet-Based Conditional Symmetric Analysis and Regularized Morphological Shared-Weight Neural Networks

Identification and detection of dendritic spines in neuron images are of high interest in diagnosis and treatment of neurological and psychiatric disorders (e.g., Alzheimer’s disease, Parkinson’s diseases, and autism). In this paper, we have proposed a novel automatic approach using wavelet-based conditional symmetric analysis and regularized morphological shared-weight neural networks (RMSNN) for dendritic spine identification involving the following steps: backbone extraction, localization of dendritic spines, and classification. First, a new algorithm based on wavelet transform and conditional symmetric analysis has been developed to extract backbone and locate the dendrite boundary. Then, the RMSNN has been proposed to classify the spines into three predefined categories (mushroom, thin, and stubby). We have compared our proposed approach against the existing methods. The experimental result demonstrates that the proposed approach can accurately locate the dendrite and accurately classify the spines into three categories with the accuracy of 99.1% for “mushroom” spines, 97.6% for “stubby” spines, and 98.6% for “thin” spines.

Effect of Homogenization Annealing on Microstructure and Property of Cu-7.5Ni-5Sn Alloy

The microstructure and properties of Cu-7.5Ni-5Sn alloy after homogenization treatment was investigated. The research results show that homogenization treatment can obviously eliminate dendritic segregation in Cu-7.5Ni-5Sn alloy. The temperature of homogenization annealing has a great influence than the effect of holding time. The ingots of Cu-7.5Ni-5Sn alloy which were homogenization treated at 780°C for 24 hours can be rolled up to 30% deformation by cold-rolling. Some tiny white matter is still remaining in dendrite boundary, but atom fraction of Ni and Sn of the dendritic segregation is decreased by 12.04% and 4.73% respectively compare with casting state. The electrical conductivity and Brinell hardness of Cu-7.5Ni-5Sn alloy homogenization treated at 800°C for 24 hours is 12.8%IACS and 132Hv, and increases 18.5% and 29.9% respectively.