62 resultados para Functional-properties
Resumo:
In this paper, the mechanical properties of bulk single-phase γ-Y2Si2O7 ceramic are reported. γ-Y2Si2O7 exhibits low shear modulus, excellent damage tolerance, and thus has a good machinability ready for metal working tools. To understand the underlying mechanism of machinability, drilling test, Hertzian contact test, and density functional theory (DFT) calculation are employed. Hertzian contact test demonstrates that γ-Y2Si2O7 is a "quasi-plastic" ceramic and the intrinsically weak interfaces contribute to its machinability. Crystal structure characteristics and DFT calculations of γ-Y2Si2O7 suggest that some weakly bonded planes, which involve Y-O bonds that can be easily broken, are the sources of the low shear deformation resistance and good machinability.
Resumo:
The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.