Heat conductivity of DNA double helix

Thermal conductivity of isolated single molecule DNA fragments is of importance for nanotechnology, but has not yet been measured experimentally. Theoretical estimates based on simplified (1D) models predict anomalously high thermal conductivity. To investigate thermal properties of single molecule DNA we have developed a 3D coarse-grained (CG) model that retains the realism of the full all-atom description, but is significantly more efficient. Within the proposed model each nucleotide is represented by 6 particles or grains; the grains interact via effective potentials inferred from classical molecular dynamics (MD) trajectories based on a well-established all-atom potential function. Comparisons of 10 ns long MD trajectories between the CG and the corresponding all-atom model show similar root-mean-square deviations from the canonical B-form DNA, and similar structural fluctuations. At the same time, the CG model is 10 to 100 times faster depending on the length of the DNA fragment in the simulation. Analysis of dispersion curves derived from the CG model yields longitudinal sound velocity and torsional stiffness in close agreement with existing experiments. The computational efficiency of the CG model makes it possible to calculate thermal conductivity of a single DNA molecule not yet available experimentally. For a uniform (polyG-polyC) DNA, the estimated conductivity coefficient is 0.3 W/mK which is half the value of thermal conductivity for water. This result is in stark contrast with estimates of thermal conductivity for simplified, effectively 1D chains ("beads on a spring") that predict anomalous (infinite) thermal conductivity. Thus, full 3D character of DNA double-helix retained in the proposed model appears to be essential for describing its thermal properties at a single molecule level.Comment: 16 pages, 12 figure

Direct and indirect effect of bt cotton and no bt cotton on the development and reproduction of the predator Podisus nigrispinus (Dallas, 1851) (Hemiptera: Pentatomidae).

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Predicting polydisperse granular segregation

Most granular materials in industrial applications and natural settings are size-polydisperse, but most models and simulations of segregation consider only bidisperse particle distributions. Here, we extend our recently developed theoretical advection–diffusion–segregation model to polydisperse particle distributions. To test the theoretical approach, we model and simulate grains log-normally distributed by size in a chute flow. In steady state, material near the free surface is dominated by large particles, whereas the lower regions are composed of mostly small particles. The segregation pattern depends on a single dimensionless control parameter, which is a function of the particle sizes, the diffusion coefficient, the shear rate, and the flowing layer depth. Interestingly, for all values of the control parameter, the overall log normal particle size distribution is approximately maintained at each spatial location, but with different mean and variance than the overall particle distribution. To confirm the theoretical results, we use discrete element method (DEM) simulations using a general purpose graphics processing unit. Quantitative agreement is found between theory and DEM simulations. Funded by the Dow Chemical Company

Local Simulation Algorithms for Coulombic Interactions

We consider dynamically constrained Monte-Carlo dynamics and show that this leads to the generation of long ranged effective interactions. This allows us to construct a local algorithm for the simulation of charged systems without ever having to evaluate pair potentials or solve the Poisson equation. We discuss a simple implementation of a charged lattice gas as well as more elaborate off-lattice versions of the algorithm. There are analogies between our formulation of electrostatics and the bosonic Hubbard model in the phase approximation. Cluster methods developed for this model further improve the efficiency of the electrostatics algorithm.Comment: Proceedings Statphys22 10 page