Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSelf-Assembly of Nanocomponents into Composite Structures: Derivation and Simulation of Langevin Equations
131
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The kinetics of the self-assembly of nanocomponents into a virus, nanocapsule, or other composite structure is analyzed via a multiscale approach. The objective is to achieve predictability and to preserve key atomic-scale features that underlie the formation and stability of the composite structures. We start with an all-atom description, the Liouville equation, and the order parameters characterizing nanoscale features of the system. An equation of Smoluchowski type for the stochastic dynamics of the order parameters is derived from the Liouville equation via a multiscale perturbation technique. The self-assembly of composite structures from nanocomponents with internal atomic structure is analyzed and growth rates are derived. Applications include the assembly of a viral capsid from capsomers, a ribosome from its major subunits, and composite materials from fibers and nanoparticles. Our approach overcomes errors in other coarse-graining methods which neglect the influence of the nanoscale configuration on the atomistic fluctuations. We account for the effect of order parameters on the statistics of the atomistic fluctuations which contribute to the entropic and average forces driving order parameter evolution. This approach enables an efficient algorithm for computer simulation of self-assembly, whereas other methods severely limit the timestep due to the separation of diffusional and complexing characteristic times. Given that our approach does not require recalibration with each new application, it provides a way to estimate assembly rates and thereby facilitate the discovery of self-assembly pathways and kinetic dead-end structures.
rate research
Read More
Single-walled carbon nanotubes are promising nanoelectronic materials but face long-standing challenges including production of pure semiconducting SWNTs and integration into ordered structures. Here, highly pure semiconducting single-walled carbon nanotubes are separated from bulk materials and self-assembled into densely aligned rafts driven by depletion attraction forces. Microscopy and spectroscopy revealed a high degree of alignment and a high packing density of ~100 tubes/micron within SWNT rafts. Field-effect transistors made from aligned SWNT rafts afforded short channel (~150 nm long) devices comprised of tens of purely semiconducting SWNTs derived from chemical separation within a < 1 micron channel width, achieving unprecedented high on-currents (up to ~120 microamperes per device) with high on/off ratios. The average on-current was ~ 3-4 microamperes per tube. The results demonstrated densely aligned high quality semiconducting SWNTs for integration into high performance nanoelectronics.
This article explores the governing role of the internal hydrodynamics and advective transport within sessile colloidal droplets on the self assembly of nanostructures to form floral patterns. Water acetone binary fluid and Bi2O3 nanoflakes based complex fluids are experimented with. Microliter sessile droplets are allowed to vaporize and the dry out patterns are examined using scanning electron microscopy. The presence of distributed self assembled rose like structures is observed. The population density, structure and shape of the floral structures are noted to be dependent on the binary fluid composition and nanomaterial concentration. Detailed microscopic particle image velocimetry analysis is undertaken to qualitatively and quantitatively describe the solutal Marangoni advection within the evaporating droplets. It has been shown that the kinetics, regime and location of the internal advection are responsible factors towards the hydrodynamics influenced clustering, aggregation and self-assembly of the nanoflakes. In addition, the size of the nanostructures and the complex fluids.
We report self-assembly and phase transition behavior of lower diamondoid molecules and their primary derivatives using molecular dynamic (MD) simulation and density functional theory (DFT) calculations. Two lower diamondoids (adamantane and diamantane), three adamantane derivatives (amantadine, memantine and rimantadine) and two artificial molecules (Adamantane+Na and Diamantane+Na) are studied separately in 125-molecule simulation systems. We performed DFT calculations to optimize their molecular geometries and obtain atomic electronic charges for the corresponding MD simulation, by which we obtained self-assembly structures and simulation trajectories for the seven molecules. Radial distribution functions and structure factors studies showed clear phase transitions for the seven molecules.
For reaction-diffusion processes with at most bimolecular reactants, we derive well-behaved, numerically tractable, exact Langevin equations that govern a stochastic variable related to the response field in field theory. Using duality relations, we show how the particle number and other quantities of interest can be computed. Our work clarifies long-standing conceptual issues encountered in field-theoretical approaches and paves the way for systematic numerical and theoretical analyses of reaction-diffusion problems.
We investigate the nature of the effective dynamics and statistical forces obtained after integrating out nonequilibrium degrees of freedom. To be explicit, we consider the Rouse model for the conformational dynamics of an ideal polymer chain subject to steady driving. We compute the effective dynamics for one of the many monomers by integrating out the rest of the chain. The result is a generalized Langevin dynamics for which we give the memory and noise kernels and the effective force, and we discuss the inherited nonequilibrium aspects.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
