Diffusion MRI Anisotropy in the Cerebral Cortex is Determined by Unmyelinated Tissue Features

The diffusion of water molecules through the brain is constrained by tissue and cellular substructure, which imposes an anisotropy that can be measured through diffusion magnetic resonance imaging (dMRI). In the white matter, myelinated axons strongly shape diffusion anisotropy; however, in gray matter the determinants of dMRI signals remain poorly understood. Here we investigated the histological tissue properties underlying dMRI anisotropy and diffusivity in the cerebral cortex of the marmoset monkey. We acquired whole brain ex vivo dMRI data designed for high signal-to-noise at ultra-high (150μm) resolution. We compared the MRI to myelin- and Nissl-stained histological sections obtained from the scanned brain. We found that dMRI anisotropy corresponds most strongly not with cortical myelin content, but rather with the microscale anisotropy of tissue features, most notably those unmyelinated features highlighted by Nissl staining. The results suggest that dMRI anisotropy in gray matter derives from the organization of unmyelinated neurites, which are known to be affected by neurodegenerative diseases.

Construction of Cellular Substructure in Laser Powder Bed Fusion

Cellular substructure has been widely observed in the sample fabricated by laser powder bed fusion, while its growth direction and the crystallographic orientation have seldom been studied. This research tries to build a general model to construct the substructure from its two-dimensional morphology. All the three Bunge Euler angles to specify a unique growth direction are determined, and the crystallographic orientation corresponding to the growth direction is also obtained. Based on the crystallographic orientation, the substructure in the single track of austenitic stainless steel 316L is distinguished between the cell-like dendrite and the cell. It is found that, with the increase of scanning velocity, the substructure transits from cell-like dendrite to cell. When the power is 200 W, the critical growth rate of the transition in the single track can be around 0.31 ms−1.

Construction of Cellular Substructure in Selective Laser Melting

Cellular substructure has been widely observed in the sample fabricated by selective laser melting, while its growth direction and the crystallographic orientation have seldom been studied. This research tries to build a general model to construct the substructure from its two dimensional morphology. All the three Bunge Euler angles to specify a unique growth direction are determined, and the crystallographic orientation corresponding to the growth direction is also obtained. Based on the crystallographic orientation, the substructure in the single track is distinguished between cell-like dendrite and cell. It is found that, with the increase of scanning velocity, the substructure transits from cell-like dendrite to cell. The critical growth rate of the transition can be around 0.31 ms-1.

Evolution of the Entropy of Dislocation Structures with Strain in Solid Solutions of Cu-0.5at.% Al

The study on the evolution of the dislocation structure (DS) parameters with strain of solid solutions of Cu-0.5 at.% Al at different test temperatures has been carried out. It has been shown that in substructures with a disordered type of DS (disorder), the disordered mixtures with non-disoriented cells, as well as mixtures of non-disoriented and disoriented cellular structures, the entropy density increases with strain. It has been shown that formation of the cellular substructure corresponds to a diffuse kinetic phase transition of the 1-st kind in the DS. A jump-like decrease in entropy accompanying this phase transition is associated with the annihilation of dislocations in cellular walls and formation of excess dislocation density.

The Effect of Strain on the Impedance and Surface Potential of Austenite in 304 Stainless Steels

Local electrochemical technique was used to measure the impedance of austenite in AISI 304 stainless steel under tensile strain of 0%, 10%, 20%, 30%, 40%. Scanning Kelvin probe (SKP) technique was used to measure the potential distribution of the surface. The results showed that the impedance of the austenite declined with the increase of the strain and declined sharply under the strain of 30%. Potential of austenite decreased non-monotonously with increase of the strain. The potential reached the minimum under strain of 30% and then increased. Through the transmission electron microscope (TEM) results, plane dislocation pile-ups were observed in the grain boundary under the strain of 30% and transformed to cellular substructure structure and cell wall under 40%. Combined with the results of local electrochemistry impedance spectroscopy (LEIS) and surface potential, it may be concluded that it was the dislocation density and dislocation structure influence the impedance spectroscopy significantly, while surface potential was sensitive to the dislocation structure.

Effect of Growth Parameters on Substructure Spacing in NaCl Ice Crystals

The effect of growth velocity υ and solute concentration C on the cellular substructure that develops in NaCl ice is studied in the range 3×10−3 to 10−5 cm s−1 and 1 to 100‰ respectively. The substructure is the result of the formation of a constitutionally super-cooled zone in the liquid ahead of the advancing interface. Unidirectional freezing runs were made by placing a cold plate in contact with the “top” of the solution and using cold-plate temperatures of −20 and −70°C. The growth velocities were determined from a least-squares fit of the growth data to a power series. The average spacings between neighboring substructures a 0 were measured from photomicrographs of precisely located thin sections. Log-log plots of a 0 against υ show that the slope n gradually changes as a function of υ. In the run where no convection occurred, n changes from to 1 as υ decreases in agreement with the prediction of Bolling and Tiller. The results of Rohatgi and Adams are also shown to be in good agreement with this prediction. On the other hand when convection occurs, n changes from to approximately o as υ decreases. This is caused by convection reducing the effective value at C at the growing interface. The variation of a 0 with C is quite complex and shows a minimum in the composition range 9 to 25‰ NaCl.