594 research outputs found
Size effects on dynamics of nanodroplets in binary head-on collisions
Head-on collision dynamics of 10, 50 and 100 nm droplets are investigated in vacuum by molecular dynamics, involving 35,858, 4,506,410 and 36,051,466 molecules, respectively. A variety of droplet collision dynamics are observed, such as coalescence, hole formation and shattering, as a function of the Weber number. It is found for the first time that the collision and reflexive separation can occur in the nanodroplet regime when the droplet diameter reaches 100 nm but not for 10 or 50 nm droplets. The size effect in droplet collisions is studied based on the analysis of stretching factors, energy dissipation and collision outcomes for droplets of different diameters. The kinetic energy dissipation due to the atomic interactions at nanoscales is identified to significantly influence the occurrence or otherwise of reflexive separation. Through quantitative analysis of the evolution of the internal structure of the 100 nm nanodroplets collision at the Weber number of 277, it is revealed for the first time that molecules from both parent nanodroplets have penetrated the full length of the merged nanodroplet in the direction of collision, due to a combination of molecular mixing and internal currents. Consequently, all three child nanodroplets have molecules from both parent nanodroplets, contrary to the perception gained from common imaging techniques. The results show that the dynamics, outcomes and mechanisms of nanodroplet collisions have both similarities and differences compared with their micro- and macro-counterparts
Regimes of Head-On Collisions of Equal-Sized Binary Droplets
Through molecular dynamics simulations, head-on collision processes of two identical droplets with a diameter of 10.9 nm are elaborately scrutinized over a wide range of impact Weber numbers (from 6.7 to 1307) both in vacuum and in an ambient of nitrogen gas. As the impact Weber number exceeds a certain critical value, a hole or multiple holes in apparently random locations are observed in the disklike structure formed by two colliding droplets. We name this a new "hole regime" of droplet collisions, which has not yet been reported in previous studies. As the impact Weber number increases, the number of holes increases. The hole or holes may disappear unless a second critical impact Weber number is exceeded, when the merged droplet is likely to experience dramatic shattering. It is also found that the existence of ambient gas provides a "cushion effect" which resists droplet deformation, thus delaying or even preventing the appearance of hole formation and shattering regimes. Moreover, increasing ambient pressure suppresses hole formation. A model based on energy balance is proposed to predict droplet behaviors, which provides a more accurate estimate of the maximum spreading factor compared to previous models. Finally, we further extend the current nanoscale droplet collision regime map and analyze the similarities and dissimilarities between nano- and macroscale droplet collision. Our study extends the current understanding on nanodroplet collisions
Bounce regime of droplet collisions: A molecular dynamics study
Droplet collisions have complex dynamics, which can lead to many different regimes of outcomes. The head-on collision and bounce back regime has been observed in previous experiments but numerical simulations using macro- or mesoscale approaches have difficulties reproducing the phenomena, because the interfacial regions are not well resolved. Previous molecular dynamics (MD) simulations have not reproduced the bounce regime either but have reported the coalescence and/or shattering regimes. To scrutinize the dynamics and mechanisms of binary collisions especially the interfacial regions, head-on collision processes of two identical nano-droplets with various impact velocities both in vacuum and in an ambient of nitrogen gas are investigated by MD simulations. With the right combination of the impact velocity and ambient pressure, the head-on collision and bounce back phenomenon is successfully reproduced. The bounce phenomena are mainly attributed to the “cushion effect” of the in-between nitrogen molecules and evaporated water molecules from the two nano-droplets. The analysis has verified and also extended the current gas film theory for the bounce regime through including the effects of evaporated water molecules (vapour). Some similarities and some dissimilarities between nanoscale and macro-/meso-/microscale droplet collisions have been observed. The study provides unprecedented insight into the interfacial regions between two colliding droplets
Contamination and potential biodegradation of polycyclic aromatic hydrocarbons in mangrove sediments of Xiamen, China
Five stations were established in the Fenglin mangrove area of Xiamen, China to determine the concentrations of polycyclic aromatic hydrocarbons (PAHs) and the numbers of PAH-degrading bacteria in surface sediments. Assessing the biodegradation potential of indigenous microorganisms and isolating the high molecule weight (HMW)-PAH degrading bacteria was also one of the aims of this work. The results showed that the total PAH concentration of sediments was 222.59 ng g(-1) dry weight, whereas the HMW-PAH benzo(a)pyrene (BaP) had the highest concentration among 16 individual PAH compounds. The variation in the numbers of PAH-degrading bacteria was 2.62 x 10(2)-5.67 x 10(4) CFU g(-1) dry weight. The addition of PAHs showed a great influence in increasing the microbial activity in mangrove sediments. A bacterial consortium, which could utilize BaP as the sole source of carbon and energy, and which was isolated from mangrove sediments and enriched in liquid medium for nearly one year degraded 32.8% of BaP after 63 days incubation. (c) 2008 Elsevier Ltd. All rights reserved
Investigation of ethanol oxidation over aluminum nanoparticle using ReaxFF molecular dynamics simulation
Aluminum nanoparticles are an effective and economical additive for producing energetic fuels. In the present study, the state of the art ReaxFF molecular dynamics (MD) simulation has been used to uncover the detailed mechanisms of ethanol oxidation over aluminum nanoparticles with different oxidation states. The MD results reveal the dynamics process of ethanol oxidation reactions at nanoscales. The presence of aluminum nanoparticles is found to reduce the initial temperature of ethanol oxidation to 324 K. It is also found that compared to ethanol, oxygen molecules are more easily adsorbed on aluminum surfaces. Moreover, different oxidation states of aluminum nanoparticles influence the initial ethanol reactions on the nanoparticles’ surfaces. OH-abstraction is more commonly observed on pure aluminum nanoparticles while H-abstraction prevails on aluminum nanoparticles with oxide. The separated H atom from hydroxyl forms bonds with Al and O atom on aluminum nanoparticles surrounded by thin and thick oxide layers, respectively. Adsorptive dissociation of ethanol is hindered by the oxide layer surrounding the aluminum nanoparticle. Gas products like H2O and CO resulting from ethanol oxidation on aluminum nanoparticles with the thick oxide layer are observed while almost all the C, H and O atoms in ethanol diffuse into the nanoparticles without or with the thin oxide layer. For ethanol dissociation, a higher temperature is required than adsorption. In addition, the rate of ethanol dissociation increases with rising reaction temperatures. The activation energy for ethanol adsorptive dissociation is found to be 4.58 kcal/mol on the aluminum nanoparticle with the thin oxide layer, which is consistent with results from much more expensive DFT calculations
A space-time continuous finite element method for 2D viscoelastic wave equation
International audienceA widespread approach to software service analysis uses session types. Very different type theories for binary and multiparty protocols have been developed; establishing precise connections between them remains an open problem. We present the first formal relation between two existing theories of binary and multiparty session types: a binary system rooted in linear logic, and a multiparty system based on automata theory. Our results enable the analysis of multiparty protocols using a (much simpler) type theory for binary protocols, ensuring protocol fidelity and deadlock-freedom. As an application, we offer the first theory of multiparty session types with behavioral genericity. This theory is natural and powerful; its analysis techniques reuse results for binary session types
Quantum-Dot Light-Emitting Diodes with Nitrogen-Doped Carbon Nanodot Hole Transport and Electronic Energy Transfer Layer
Electroluminescence efficiency is crucial for the application of quantum-dot light-emitting diodes (QD-LEDs) in practical devices. We demonstrate that nitrogen-doped carbon nanodot (N-CD) interlayer improves electrical and luminescent properties of QD-LEDs. The N-CDs were prepared by solution-based bottom up synthesis and were inserted as a hole transport layer (HTL) between other multilayer HTL heterojunction and the red-QD layer. The QD-LEDs with N-CD interlayer represented superior electrical rectification and electroluminescent efficiency than those without the N-CD interlayer. The insertion of N-CD layer was found to provoke the Forster resonance energy transfer (FRET) from N-CD to QD layer, as confirmed by time-integrated and - resolved photoluminescence spectroscopy. Moreover, hole-only devices (HODs) with N-CD interlayer presented high hole transport capability, and ultraviolet photoelectron spectroscopy also revealed that the N-CD interlayer reduced the highest hole barrier height. Thus, more balanced carrier injection with sufficient hole carrier transport feasibly lead to the superior electrical and electroluminescent properties of the QD-LEDs with N-CD interlayer. We further studied effect of N-CD interlayer thickness on electrical and luminescent performances for high-brightness QD-LEDs. The ability of the N-CD interlayer to improve both the electrical and luminescent characteristics of the QD-LEDs would be readily exploited as an emerging photoactive material for high-efficiency optoelectronic devices.ope
Efficient and accurate greedy search methods for mining functional modules in protein interaction networks
<p>Abstract</p> <p>Background</p> <p>Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures.</p> <p>Methods</p> <p>In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules.</p> <p>Results</p> <p>The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms.</p> <p>Conclusions</p> <p>Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.</p
Delay-probability-distribution-dependent stability criteria for discrete-time stochastic neural networks with random delays
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