712 research outputs found
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
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