Due to the relatively long time scales inherent to ionic surfactant self-assembly (>ms), an aggressive computational approach is needed to obtain converged data on micellar solutions. This work presents a study of micellization using a coarse-grained (CG) model of aqueous ionic surfactants in replicated molecular dynamics (MD) simulations run on graphics processing unit hardware. The performance of our implementation of the CG model with electrostatics into the HOOMD-Blue GPU-accelerated MD software package is comparable to that of a modest sized cluster running a highly optimized parallel CPU code. From 0.36 ms of cumulative trajectory data, we are able to predict equilibrium thermodynamic and morphological properties of ionic surfactant micellar solutions. Estimating the critical micelle concentrations (CMC) from the free monomer (r 1 ) and premicellar concentrations obtained from simulations of sodium hexyl sulfate (S6S, CMC of 460 AE 6 mM) at high (1 M) concentration, a value in good agreement with experimental results is obtained; however, the same method applied to simulations of sodium nonyl sulfate (S9S, r 1 of 2.4 AE 0.01 mM) and sodium dodecyl sulfate (SDS, r 1 of 0.02 AE 0.01 mM) at the same total concentration systematically underestimates the CMCs. An alternative method for calculating the CMC is presented, where the free monomer concentration computed from high concentration CG-MD data is used as the input to a simple theoretical model which can be used to extrapolate to a more accurate prediction of the CMC. Better agreement between the empirical and predicted CMC is obtained from this theory for S9S (28.7 AE 0.3 mM) and SDS (3.32 AE 0.04 mM), though the CMC for S6S is slightly underestimated (304 AE 3 mM). We also present statistically converged morphological data, including aggregation number distributions and the principal components of the gyration tensor. This data suggest a transition from spherical micelles to rod-like at a specific aggregation number, which increases with increasing hydrocarbon length.

The reported dielectric barrier discharge (DBD) source comprises of a ceramic‐covered copper electrode, and plasma can be ignited in ambient air with grounded ‘opposite’ electrodes or with objects of high capacitance (e.g., human body), when breakdown conditions are satisfied. Filamentary plasma mode is observed when the same source is operated using grounded opposite electrodes like aluminium plate and phosphate buffered saline solution, and a homogeneous plasma mode when operated on glass. When the source is applied on human body, both homogeneous and filamentary discharges occur simultaneously which cannot be resolved into two separate discharges. Here, we report the characterization of filamentary and homogeneous modes of DBD plasma source using the above mentioned grounded electrodes, by applying optical emission spectroscopy, microphotography and numerical simulation. Averaged plasma parameters like electron velocity distribution function and electron density are determined. Fluxes of nitric oxide, ozone and photons reaching the treated surface are simulated. These fluxes obtained in different discharge modes namely, single‐filamentary discharge (discharge ignited in same position), stochastical filamentary discharge and homogeneous discharge are compared to identify their applications in human skin treatment. It is concluded that the fluxes of photons and chemically‐active particles in the single filamentary mode are the highest but the treated surface area is very small. For treating larger area, the homogeneous DBD is more effective than stochastical filamentary discharge.

Our dielectric barrier discharge (DBD) plasma source for bio-medical application comprises a copper electrode covered with ceramic. Objects of high capacitance such as the human body can be used as the opposite electrode. In this study, the DBD source is operated in single-filamentary mode using an aluminium spike as the opposite electrode, to imitate the conditions when the discharge is ignited on a raised point, such as hair, during therapeutic use on the human body. The single-filamentary discharge thus obtained is characterized using optical emission spectroscopy, numerical simulation, voltage–current measurements and microphotography. For characterization of the discharge, averaged plasma parameters such as electron distribution function and electron density are determined. Fluxes of nitric oxide (NO), ozone (O3) and photons reaching the treated surface are simulated. The calculated fluxes are finally compared with corresponding fluxes used in different bio-medical applications.

Particle-in-cell (PIC) simulations with Monte-Carlo collisions are used in plasma science to explore a variety of kinetic effects. One major problem is the long runtime of such simulations. Even on modern computer systems, PIC codes take a considerable amount of time for convergence. Most of the computations can be massively parallelized, since particles behave independently of each other within one time step. Current graphics processing units (GPUs) offer an attractive means for execution of the parallelized code. In this contribution we show a one-dimensional PIC code running on Nvidia R GPUs using the CUDA TM environment. A distinctive feature of the code is that size of the cells that the code uses to sort the particles with respect to their coordinates is comparable to size of the grid cells used for discretization of the electric field. Hence, we call the corresponding algorithm "fine-sorting". Implementation details and optimization of the code are discussed and the speed-up compared to classical CPU approaches is computed.

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