Narrow Results

We analyze the adhesion probability distribution of diffusion-limited aggregation (DLA) assuming that a random walker directly diffuses to the adhesion position of DLA. The distribution is divided into two regions. In the region that is closer to a seed particle, the adhesion probability is described as the product between the Poisson distribution and the adhesion process. In the region that is farther from a seed particle, the distribution is understood to be the product of the Gaussian and the adhesion process. Both results are physically reasonable.

In nature, especially in non-equilibrium physics, we can see many branching growth patterns. We devised a new method for easily analyzing such pattern structures. A pattern growing in real space is transformed into a one-variable array without destroying the essence of its structure. To validate the method, we analyzed a fractal pattern as an example. By comparing the fractal dimension of the pattern with several exponents of the transformed one-variable array, we discuss the effectiveness of transformation into one-variable arrays.

Wide bandgap II–VI semiconductor quantum dots embedded in glass matrix have shown great potential for opto-electronic device applications. The current problem is to achieve low size dispersion, high volume fraction, and better control over the size of the quantum dots in glass matrix. In this work, a modified growth method has been proposed to achieve a greater control over the size of quantum dots, to reduce their size dispersion and to increase their volume fraction. A theoretical model has been developed to quantitatively estimate the various parameters of the quantum dots. The effects of aging on various parameters of quantum dots in Semiconductor-Doped Glass (SDG) samples have also been discussed in the present work.

Gold nanoparticle assemblies show a strong plasmonic response due to the combined effects of the individual nanoparticles’ plasmon modes. Increasing the number of nanoparticles in structured assemblies leads to significant shifts in the optical and physical properties. We use finite-difference time-domain (FDTD) simulations to analyze the electromagnetic response of structurally ordered gold nanorods in monomer and dimer configurations. The plasmonic coupling between nanorods in monomers or dimers configurations provides a unique technique for tuning the spectrum intensity, spatial distribution and polarization of local electric fields within and surrounding nanostructures. This study shows an exponential coupling behavior when two gold nanorods are assembled in end-to-end and side-by-side dimer configurations with a small separation distance. The maximum electric field in the gaps between adjacent nanorods in end-to-end dimer configuration describes a more significant enhancement factor than the individual gold nanorod. Our FDTD simulation on dimer in end-to-end assembly for small separation distance up to $\sim 40$nm can well explain the observed experimental growth dynamics of gold nanorods.

This paper consists of two parts. In the first part we carry out a traditional growth accounting exercise for the private business sectors of the Swedish economy. A search for structural breaks during the sample period, using Chow tests with a dynamic specification of Total Factor Productivity (TFP) growth rates, and Granger causality tests are carried out for the nine sectors of the Swedish economy. We combine the growth rates of value added and hours worked and calculate labor productivity for the period 1960–1999. In order to facilitate comparisons we present Swedish and international results. To a large extent we are able to replicate the Swedish results. The slow down in TFP growth rates in the 1970s can be identified with the first and the second oil shocks in 1973 and 1979. The other structural breaks occurred in the early 1990s and could possibly be identified with the tax reform of the century in 1991 and the severest of recessions that took place in the Swedish economy. The Granger causality tests indicate that growth rates in investment Granger causes growth rates in TFP for the agriculture and the financial institutions, real estate and other business, while TFP growth rates in mining and quarrying, and manufacturing granger causes growth rates in investment.

In the second part of the paper, we Hodrick–Prescott filter the data, and calculate cross correlations of detrended output, hours, investment and TFP at different leads and lags. The results indicate that investment leads TFP for agriculture, hunting, forestry and fishing, electricity gas and water, and for education, health and social work and community social and personal services. Investment lags TFP for the mining and quarrying, manufacturing industry, and for financial institutions and insurance companies, real estate renting and business service companies. Hours worked lead the TFP cycle for mining and quarring, manufacturing and wholesale/retail trade. The decomposition of TFP into trend and cyclical component dates the business cycle. Standard deviations on the cyclical components of value added, hours worked, TFP, and gross investment reveals that the most volatile variables are gross investment, followed by TFP, GDP and hours worked.

The contribution of this part of the paper lies in the disaggregated data set containing annual information for the period 1963–1999, and in the application of several analytical tools to the growth accounting exercise results. In addition such an extensive growth accounting exercise has not been carried out for the private business sectors of the Swedish economy.

Molecular dynamics simulation is used to study the spontaneous nucleation and solidification of Al liquid. According to the mean first-passage time (MFPT), the critical crystal nucleus size at 31.6% undercooling is 152 atoms, the nucleation rate is $9.60\times 10^{33}$m${}^{-3}$s${}^{-1}$. The nucleation rate obtained by the survival probability (SP) is $9.88\times 10^{33}$m${}^{-3}$s${}^{-1}$, which is very consistent with the result obtained by MFPT. Using Johnson–Mehl–Avrami (JMA) law to analyze the growth of the two extreme conditions in the experiment, the system with the smallest average atomic volume (Run38) grows faster than the system with the largest volume (Run73). In terms of microstructure, Run38 is a lamellar (LAM) structure, and Run73 is a complex polycrystalline structure accompanied by five-fold twinning (FFT). The shapes of clusters in a given range (5–10,000 atoms) during solidification in 100 experiments were counted. The results show that no clusters are perfectly spherical, but ellipsoids are of different shapes, and the larger the ellipsoid size, the closer to a spherical shape.