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Nonequilibrium molecular dynamics simulation is applied to investigate the effect of periodic wall roughness on the flow of liquid argon through krypton nanochannels. The effect of the length of a rectangular protrusion on the flow is investigated and compared to the case of nanochannels with flat walls. The results show a clear trapping of fluid atoms inside the rectangular cavities that are formed between successive protrusions. The size of the cavities affects the potential energy map and, consequently, fluid atom localization. This localization results in a reduction of velocity values inside the cavities, as well as a reduction of the slip length near the rough wall.

The effect of rough-wall/fluid interaction on flow in nanochannels is investigated by NEMD. Hydrophobic and hydrophilic surfaces are studied for walls with nearly atomic-size rectangular protrusions and cavities. Our NEMD simulations reveal that the number of liquid atoms temporarily trapped in the cavities is affected by the strength of the potential energy inside the cavities. Regions of low potential energy are possible trapping locations. Fluid atom localization is also affected by the hydrophilicity/hydrophobicity of the surface. Potential energy is greater between two successive hydrophilic protrusions, compared to hydrophobic ones. Moreover, groove size and wall wettability are factors that control effective slip length. Surface roughness and wall wettability have to be taken into account in the design of nanofluidic devices. Keywords NEMD simulation Á Rough-wall nanochannels Á Surface wettability Á Fluid atom trapping Á Potential energy Á Effective slip length List of symbols F ext Magnitude of external driving force h Gap between channel walls K Spring constant k B Boltzman constant L x Length of the computational domain in the x-direction L y Length of the computational domain in the y-direction L z Length of the computational domain in the z-direction L s Slip length L s,eff Effective slip length m Atom mass N Number of atoms p Periodic roughness factor r eqPosition of a wall atom on fcc lattice site r i Position vector of atom i r ij Distance vector between ith and jth atom T Temperature u(r ij ) LJ potential of atom i with atom j V Volume of the computational domain (L x 9 L y 9 L z )Greek symbols e Energy parameter in the LJ potential rLength parameter in the LJ potential t w Fluid velocity at the channel wall t w h i Average fluid velocity at the channel wall 1 Introduction

In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topological properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics.

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