In molecular dynamics (MD) simulations, interactions between water molecules and graphitic surfaces are often modeled as a simple Lennard-Jones potential between oxygen and carbon atoms. A possible ...method for tuning this parameter consists of simulating a water nanodroplet on a flat graphitic surface, measuring the equilibrium contact angle, extrapolating it to the limit of a macroscopic droplet, and finally matching this quantity to experimental results. Considering recent evidence demonstrating that the contact angle of water on a graphitic plane is much higher than what was previously reported, we estimate the oxygen-carbon interaction for the recent SPC/Fw water model. Results indicate a value of about 0.2 kJ/mol, much lower than previous estimations. We then perform simulations of cylindrical water filaments on graphitic surfaces, in order to compare and correlate contact angles resulting from these two different systems. Results suggest that a modified Young's equation does not describe the relation between contact angle and drop size in the case of extremely small systems and that contributions different from the one deriving from contact line tension should be taken into account.
► Molecular dynamics simulations for the equilibrium contact angle of graphitic surfaces. ► Assessment of predictions of Young equation. ► Transition to the macroscopic limit.
Wetting is a widespread ...phenomenon, most prominent in a number of cases, both in nature and technology. Droplets of pure water with initial radius ranging from 20 to 80Å spreading on graphitic surfaces are studied by molecular dynamics simulations. The equilibrium contact angle is determined and the transition to the macroscopic limit is discussed using Young equation in its modified form. While the largest droplets are almost perfectly spherical, the profiles of the smallest ones are no more properly described by a circle. For the sake of accuracy, we employ a more general fitting procedure based on local averages. Furthermore, our results reveal that there is a possible transition to the macroscopic limit. The modified Young equation is particularly precise for characteristic lengths (radii and contact-line curvatures) around 40Å.
A hierarchical procedure bridging the gap between atomistic and mesoscopic simulation for polymer−clay nanocomposite (PCN) design is presented. The dissipative particle dynamics (DPD) is adopted as ...the mesoscopic simulation technique, and the interaction parameters of the mesoscopic model are estimated by mapping the corresponding energy values obtained from atomistic molecular dynamics (MD) simulations. The predicted structure of the nylon 6 PCN system considered is in excellent agreement with previous experimental and atomistic simulation results.
This work reports on the heat and mass transfer evolution of ceramic lattices during their oxidation at 1400°C and 1600°C in air. Si–SiC and Si–SiC–ZrB2 systems were employed as skeleton material ...because they, previously produced as monolithic bars, showed promising oxidation behavior at high temperatures. Regular arrays of tetrakaidecahedra were first designed by CAD, then 3D printed and finally converted into ceramic by replica technique followed by reactive silicon infiltration. The surface area of each sample was calculated and specific weight variations were evaluated as a function of time. During oxidation, effective thermal conductivity and pressure drop of each sample were measured. Finally, results were correlated with the phenomena occurring during high‐temperature oxidation.
Finite element (FE) techniques can be used for the calculation of the effective properties of random heterogeneous materials, the required input simply consisting of phase properties and ...representative three-dimensional models of material microstructure. This approach has been widely exploited in recent years, although limited by the considerable amount of computational power required to obtain statistically accurate results. By using simple microstructural models of compression moulded polymer–graphite composites and a FE code modified for execution on graphical processing units, we show that reliable predictions of electrical properties for these materials can now be obtained in a reasonable computational time and with acceptable accuracy and precision. By using an approach based on design of experiments, we also perform a set of simulations aimed at determining the microstructural details which are most significant for the effective properties of these materials.
This work presents a new hybrid manufacturing process to produce ZrB2–SiC ceramics with the SiC phase synthesized in situ by reaction bonding. Since ZrB2–SiC composites properties strongly depend on ...their grain size, finer and thus more expensive powders are usually employed. In the first part of the process, silicon carbide with a fine microstructure was produced by the reaction bonding between silicon powders and carbon derived from powders and pyrolysed phenolic resin The latter, being fluid before polymerization, filled the interstices between the powders thanks to the high pressure applied. Because of this behavior, after spark plasma sintering, the resulting microstructure presents the SiC phase dispersed between the ZrB2 grains in a different ways when compared with the standard ceramic powders consolidation methods.
An innovative many-scale molecular modeling procedure has been developed and applied to study possible ways to improve and recycle automotive reinforced acrylonitrile–butadiene–styrene (ABS) scraps ...by their conversion into organoclay nanocomposites.
In this work, we simulated modified organoclay exfoliation and intercalation at an atomistic level, thus providing information about the rational choice of compatibilizers and polymer insertions behavior. Phase morphology and segregation domains have then been obtained resorting to mesoscale simulation techniques. Finally, finite element calculations at micrometric level have been performed, considering the whole structure of the nanocomposite (i.e., mineral filler and polymer blend), to calculate the corresponding improvement in the mechanical properties. Output data, such as phase morphologies and mechanical properties, have been validated against experimental data available in literature, finding good agreements.
The proposed procedure relies solely on input data obtained by molecular simulations, exception made for the experimental value of the Young modulus of the filler. Accordingly, our computational recipe constitutes a sort of innovative,
atomistic-based, step-by-step procedure, in which each level calculations yield information necessary to perform simulation at the next, higher level length/time scale.
We present an innovative, multiscale computational approach to probe the behaviour of polymer–clay nanocomposites (PCNs). Our modeling recipe is based on 1) quantum/force‐field‐based atomistic ...simulation to derive interaction energies among all system components; 2) mapping of these values onto mesoscopic bead–field (MBF) hybrid‐method parameters; 3) mesoscopic simulations to determine system density distributions and morphologies (i.e., intercalated versus exfoliated); and 4) simulations at finite‐element levels to calculate the relative macroscopic properties. The entire computational procedure has been applied to two well‐known PCN systems, namely Nylon 6/Cloisite 20A and Nylon 6/Cloisite 30B, as test materials, and their mechanical properties were predicted in excellent agreement with the available experimental data. Importantly, our methodology is a truly bottom‐up approach, and no “learning from experiment” was needed in any step of the entire procedure.
Structural snapshots of polymer–clay nanocomposites are obtained by a mesoscopic bead–field hybrid simulation method in which the clay platelets and compatibiliser molecules are represented as soft‐core beads and the polymer is represented by a field model (see picture; bead colors: brown, clay; blue/light green, compatibiliser; field colors: red, high density values; green, intermediate density values; blue, low density values).
In recent decades, finite element (FE) techniques have been extensively used for predicting effective properties of random heterogeneous materials. In the case of very complex microstructures, the ...choice of numerical methods for the solution of this problem can offer some advantages over classical analytical approaches, and it allows the use of digital images obtained from real material samples (e.g., using computed tomography). On the other hand, having a large number of elements is often necessary for properly describing complex microstructures, ultimately leading to extremely time-consuming computations and high memory requirements. With the final objective of reducing these limitations, we improved an existing freely available FE code for the computation of effective conductivity (electrical and thermal) of microstructure digital models. To allow execution on hardware combining multi-core CPUs and a GPU, we first translated the original algorithm from Fortran to C, and we subdivided it into software components. Then, we enhanced the C version of the algorithm for parallel processing with heterogeneous processors. With the goal of maximizing the obtained performances and limiting resource consumption, we utilized a software architecture based on stream processing, event-driven scheduling, and dynamic load balancing. The parallel processing version of the algorithm has been validated using a simple microstructure consisting of a single sphere located at the centre of a cubic box, yielding consistent results. Finally, the code was used for the calculation of the effective thermal conductivity of a digital model of a real sample (a ceramic foam obtained using X-ray computed tomography). On a computer equipped with dual hexa-core Intel Xeon X5670 processors and an NVIDIA Tesla C2050, the parallel application version features near to linear speed-up progression when using only the CPU cores. It executes more than 20 times faster when additionally using the GPU.
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