1,061 research outputs found

    Lifetime of dynamical heterogeneity in a highly supercooled liquid

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    We numerically examine dynamical heterogeneity in a highly supercooled three-dimensional liquid via molecular-dynamics simulations. To define the local dynamics, we consider two time intervals, τα\tau_\alpha and τngp\tau_{\text{ngp}}. τα\tau_\alpha is the α\alpha relaxation time, and τngp\tau_{\text{ngp}} is the time at which non-Gaussian parameter of the van Hove self-correlation function is maximized. We determine the lifetimes of the heterogeneous dynamics in these two different time intervals, τhetero(τα)\tau_{\text{hetero}}(\tau_\alpha) and τhetero(τngp)\tau_{\text{hetero}}(\tau_{\text{ngp}}), by calculating the time correlation function of the particle dynamics, i.e., the four-point correlation function. We find that the difference between τhetero(τα)\tau_{\text{hetero}}(\tau_\alpha) and τhetero(τngp)\tau_{\text{hetero}}(\tau_{\text{ngp}}) increases with decreasing temperature. At low temperatures, τhetero(τα)\tau_{\text{hetero}}(\tau_\alpha) is considerably larger than τα\tau_{\alpha}, while τhetero(τngp)\tau_{\text{hetero}}(\tau_{\text{ngp}}) remains comparable to τα\tau_{\alpha}. Thus, the lifetime of the heterogeneous dynamics depends strongly on the time interval.Comment: 4pages, 6figure

    Dynamical heterogeneity in a highly supercooled liquid: Consistent calculations of correlation length, intensity, and lifetime

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    We have investigated dynamical heterogeneity in a highly supercooled liquid using molecular-dynamics simulations in three dimensions. Dynamical heterogeneity can be characterized by three quantities: correlation length ξ4\xi_4, intensity χ4\chi_4, and lifetime τhetero\tau_{\text{hetero}}. We evaluated all three quantities consistently from a single order parameter. In a previous study (H. Mizuno and R. Yamamoto, Phys. Rev. E {\bf 82}, 030501(R) (2010)), we examined the lifetime τhetero(t)\tau_{\text{hetero}}(t) in two time intervals t=ταt=\tau_\alpha and τngp\tau_{\text{ngp}}, where τα\tau_\alpha is the α\alpha-relaxation time and τngp\tau_{\text{ngp}} is the time at which the non-Gaussian parameter of the Van Hove self-correlation function is maximized. In the present study, in addition to the lifetime τhetero(t)\tau_{\text{hetero}}(t), we evaluated the correlation length ξ4(t)\xi_4(t) and the intensity χ4(t)\chi_4(t) from the same order parameter used for the lifetime τhetero(t)\tau_{\text{hetero}}(t). We found that as the temperature decreases, the lifetime τhetero(t)\tau_{\text{hetero}}(t) grows dramatically, whereas the correlation length ξ4(t)\xi_4(t) and the intensity χ4(t)\chi_4(t) increase slowly compared to τhetero(t)\tau_{\text{hetero}}(t) or plateaus. Furthermore, we investigated the lifetime τhetero(t)\tau_{\text{hetero}}(t) in more detail. We examined the time-interval dependence of the lifetime τhetero(t)\tau_{\text{hetero}}(t) and found that as the time interval tt increases, τhetero(t)\tau_{\text{hetero}}(t) monotonically becomes longer and plateaus at the relaxation time of the two-point density correlation function. At the large time intervals for which τhetero(t)\tau_{\text{hetero}}(t) plateaus, the heterogeneous dynamics migrate in space with a diffusion mechanism, such as the particle density.Comment: 12pages, 13figures, to appear in Physical Review

    Comparing technical efficiency of organic and conventional coffee farms in Nepal using data envelopment analysis (DEA) approach

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    Data Envelopment Analysis (DEA) approach used to estimate technical efficiency and followed by regressing the technical efficiency scores to farm specific characters under tobit regression model. Primary data was collected from random samples of 240 (120 from each) coffee famers. Mean technical efficiency score was 0.89 and 0.83 in organic and conventional coffee farming respectively. Farms operating under CRS, DRS and IRS were 31.67, 3.83 and 37.5% respectively in organic coffee and 29.17, 25 and 45.83% respectively in conventional farming areas. Tobit regression showed the variation in technical efficiency was related education, farm experience and training/extension services and excess to credit.Production frontier, Resource use, Technical efficiency, Organic, Altitude, Productivity Analysis,
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