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Amphiphilic building blocks play an important role in fabricating nanomaterials. To achieve the precise control of self-assembled nanostructures, it is important to understand the self-assembly process at both microscopic and mesoscopic scale. Multiscale simulations could simulate the self-assembly process in both microscopic and mesoscopic scale, and get the metastable and equilibrium assembled structures and the corresponding trajectories. Based on these trajectories, we can further build the kinetic network model and obtain the kinetic transition pathway of the self-assembly process. This approach provides the theoretical principles for designing novel self-assembly building blocks and achieving novel self-assembled structures. In this article, we review our recent progress on the study of mechanisms of self-assembly of amphiphilic building blocks, such as small organic molecules, block copolymers and patchy particles by combining multiscale simulation and kinetic network model analysis.

In this study, we investigate the motion of polymer segments in polymer/nanoparticle composites by varying nanoparticle (NP) volume fractions. By studying the probability distribution of segment displacement, segment trajectory, and the square displacement of segment, we find the intermittent motion of segments, accompanied with the coexistence of slow and fast segments in polymer nanocomposites (PNCs). The displacement distribution of segments exhibits an exponential tail, rather than a Gaussian form. The intermittent dynamics of chain segments is comprised of a long-range jump motion and a short-range localized motion, which is mediated by the weakly attractive interaction between NP and chain segment and the strong confinement induced by NPs. Meanwhile, the intermittent motion of chain segments can be described by the adsorption-desorption transition at low particle loading and confinement effect at high particle loading. These findings may provide important information for understanding the anomalous motion of polymer chains in the presence of NPs.

In lithium-ion batteries, separator serves to isolate the positive and negative electrodes, as well as provide a free shuttle for Li-ion transport inside the battery. Commercial polyolefin separator has relatively higher thermal shrinkage and lower electrolyte wettability, which limits the application of batteries in extreme conditions. In this work, we prepared phenolic resin (AF) modified polyethylene (PE) composite separators by the process of immersion in situ reaction. The obtained PE@AF composite separator has lower thermal shrinkage and higher electrolyte wettability than pure PE separator. The shrinkage of our prepared PE@AF separator is only 6% when stored at 145 °C for 30 min, greatly smaller than the pure PE separator (more than 77%). Moreover, the ion conductivity of PE@AF composite separator increases from 0.206 mS cm−1 for the pure one to 0.604 mS cm−1. Apart from this, the Li/electrolyte-soaked PE@AF separator/LiFePO4 battery exhibits a higher coulombic efficiency (96.7%) and discharge capacity retention rate (86.0%) after 450 cycles than the pure one (67.4% and 72.7%, respectively). Our results indicate that the AF coating plays a vital part in improving the thermal stability and electrochemical property of polyolefin separators.

The wheelchair climbing-stairs is a complex mehatronics system, which includes the front leg mechanism, rear leg mechanism, seat mechanism, and so on. Each has an independent CPU to control itself motion. Their coordination can implement the climbing-stair act for the wheelchair climbing robot. Firstly, the paper presents the control system platform for the wheelchair robot, and introduces its functions and requirements. Secondly, describes the process of each component work, such as, the front leg mechanism, rear leg mechanism, and seat mechanism. And designs a control system platform to implement their act based on VC++6.0 software. Finally, the serial communication protocol is given to describe the data exchange process of the upper and lower CPUs towards wheelchair climbing-stairs.

Molecular dynamics simulations are useful tools to unveil molecular mechanisms of polymer phase separation, self-assembly, adsorption, and so on. Due to large molecular size and slow relaxation of the polymer chains, a great amount of issues related to large-distance chain displacement cannot be tackled easily with conventional molecular dynamic simulations. Systematic coarse-graining and enhanced sampling methods are two types of improvements that can boost spatiotemporal scales in polymer simulations. We present two typical ways to obtain the coarse-graining potential either by fitting to correct liquid structures or by fitting to available thermodynamic properties of polymer systems. The newly proposed anisotropic coarse-grained particle model can be used to describe aggregation and assembly of polymeric building blocks from disk-like micelles to Janus particles. We also present a stochastic polymerization model combined with coarse-grained simulations to investigate the problems strongly influenced by the coupling of polymerization and excluded volume effects. Finally, a facile implementation of integrated tempering sampling method is illustrated to be very efficient on bypassing local energy minima and having access to true equilibrium polymer structures.

We present a mesoscale simulation model that is suitable for describing the deformable and non-centrosymmetric characteristics of soft triblock Janus particles. The model parameters are readily mapped onto experimental systems under different ambient conditions. We examine the influence of Janus balance and the flexibility of Janus particle aggregates on the packing structures. Some ordered structures, such as the hexagonal columnar structure and the body-centered tetragonal structure, are observed in our simulations. Our study demonstrates that the Janus balance and the flexibility of Janus particle aggregates can be tuned to obtain various ordered packing structures. The soft Janus particles with soft and deformable characteristics may bring new excitement to materials science.

A novel mesoscopic simulation method is adopted to study the ordered packing of the anisotropic disklike particles with a soft repulsive interaction, which possesses a modified anisotropic conservative force type used in dissipative particle dynamics. We examine the influence of the shape of the particles, the angular width of the repulsion, and the strength of the repulsion on the packing structures. Specifically, an ordered hexagonal columnar structure is obtained in our simulations. Our study demonstrates that an anisotropic repulsive potential between soft discoidal particles is sufficient to produce a relatively ordered hexagonal columnar structure.

Molecular dynamics simulations are adopted to calculate the equation of state characteristic parameters P*, rho*, and T* of isotactic polypropylene (iPP) and poly(ethylene-co-octene) (PEOC), which can be further used in the Sanchez-Lacombe lattice fluid theory (SLLFT) to describe the respective physical properties. The calculated T* is a function of the temperature, which was also found in the literature. To solve this problem, we propose a Boltzmann fitting of the data and obtain T* at the high-temperature limit. With these characteristic parameters, the pressure-volume-temperature (PVT) data of iPP and PEOC are predicted by the SLLFT equation of state. To justify the correctness of our results, we also obtain the PVT data for iPP and PEOC by experiments. Good agreement is found between the two sets of data. By integrating the Euler-Lagrange equation and the Cahn-Hilliard relation, we predict the density profiles and the surface tensions for iPP and PEOC, respectively. Furthermore, a recursive method is proposed to obtain the characteristic interaction energy parameter between iPP and PEOC. This method, which does not require fitting to the experimental phase equilibrium data, suggests an alternative way to predict the phase diagrams that are not easily obtained in experiments. As an example, in the framework of SLLFT, the spinodal curve for the iPP/PEOC blend is predicted at the low molecular weights that are used in the simulations.

GALAMOST [graphics processing unit (GPU)-accelerated large-scale molecular simulation toolkit] is a molecular simulation package designed to utilize the computational power of GPUs. Besides the common features of molecular dynamics (MD) packages, it is developed specially for the studies of self-assembly, phase transition, and other properties of polymeric systems at mesoscopic scale by using some lately developed simulation techniques. To accelerate the simulations, GALAMOST contains a hybrid particle-field MD technique where particle-particle interactions are replaced by interactions of particles with density fields. Moreover, the numerical potential obtained by bottom-up coarse-graining methods can be implemented in simulations with GALAMOST. By combining these force fields and particle-density coupling method in GALAMOST, the simulations for polymers can be performed with very large system sizes over long simulation time. In addition, GALAMOST encompasses two specific models, that is, a soft anisotropic particle model and a chain-growth polymerization model, by which the hierarchical self-assembly of soft anisotropic particles and the problems related to polymerization can be studied, respectively. The optimized algorithms implemented on the GPU, package characteristics, and benchmarks of GALAMOST are reported in detail. © 2013 Wiley Periodicals, Inc.

We develop a mesoscale nonequilibrium simulation model to study the effect of steady shear on the hierarchical self-assembly of soft disklike particles in dilute solutions. By properly tuning shear rates and solvent conditions, soft disklike particles can self-assemble into flexible threads and bundle-like structures along the flow direction. Shear flow facilitates the self-assembly of soft disklike particles into one-dimensional long threads along the flow direction; however, it suppresses the formation of flexible bundles from the threads while decreasing the solvent quality. The relatively well-defined bundle structures along the flow direction can only be obtained when the solvent condition becomes even worse. Our study elucidates how the solvent condition and shear rate can be utilized to control the shear-induced self-assembled structures, which would enable designed nanofabrication.