To explore the mechanism of how the nanorod surface properties regulate the compatibilization behavior and the morphology transition in demixing polymer blends, we perform dissipative particle dynamics simulations and study the impact of three typical nanorods on the phase separation kinetics and structure as well as their location and arrangement under both shear-free and shear conditions with the variation of nanorod–polymer affinity parameters. Depending on the dispersion and location of nanorods, blends in the quiescent case either undergo full phase separation and generate bulky two-phase morphology, or experience microphase separation and form BμE-like structure, or proceed viscoelastic phase separation and take the kinetically trapped cocontinuous network morphology, whereas shear flow can either accelerate domain coarsening or strongly impact the phase behavior through shear-induced bulk phase separation or shear-induced ordering transition. Particularly, the shear-induced lamellar phase in Janus nanorod-filled blends chooses parallel orientation and displays the lateral ordering within layers.

In the present work, we develop a coarse-grained (CG) model for polyimide (PI) at 800 K and 1 atm by applying iterative Boltzmann inversion (IBI) and the density correction method to derive the bonded and nonbonded interaction potentials. Although the CG force field is built at a single thermodynamic state point without any temperature correction, the CG model possesses a rather favorable temperature transferability in a wide temperature range of 300–800 K at P = 1 atm and a good pressure transferability to some extent in a certain pressure range from 0.1 to 30 MPa. In addition to the local conformation and local packing distribution functions, the thermodynamic properties such as the glass transition temperature and the coefficient of linear thermal expansion are predicted correctly by the CG model, and the isothermal compressibility coefficients calculated from both atomic and CG models are on the same order of magnitude. Additionally, the stress–strain behavior under compression or tension of the CG model shows a qualitative agreement with the atomistic results, and the corresponding values of the elastic modulus of the CG model at different temperatures roughly match with those of the atomistic model.

Membrane fusion not only involves many biologic phenomena such as neurotransmission, exo‐ and endocytosis, fertilization, membrane traffic, and viral infection, but also is relevant for many technological applications, that is, drug delivery. Therefore, unraveling the molecular mechanism of these important processes are both helpful to deepen the understanding of vital phenomena and instructive for the development of medical technology, for example, gene therapy. With the advances in computation power and algorithms, molecular simulation has become an invaluable tool to systematically investigate the entire membrane fusion process at the molecular level, in which not only the conformations and motions of lipid molecule but also the protein/DNA intermediates can easily be monitored. Nowadays, by these powerful methods, both the different pathways and the intermediate structures are discriminated, and the precise mechanisms and possible factors are explored. The present progress report reviews recent studies based on computational approaches with an aim to clarify the membrane fusion dynamics at a molecular level, which not only provides a useful starting point for a more thorough understanding about the membrane fusion process but also inspires developing promising applications such as drug or imaging‐agent delivery and gene therapy.

Ordered microstructures assembled from the mixture of the ABC 3-miktoarm star terpolymers and the linear homopolymers have been investigated by using dynamic density functional theory. The simulations reveal that completely different ordered microphase pattern is found with addition of a few percent homopolymers that is identical in component to one of the arms on the ABC 3-miktoarm star terpolymer. For example, the original density pattern of ABC 3-miktoarm star terpolymers with parameters of N(A)=N(B)=N(C)=10 and chi(AB)=0.90, chi(BC)=chi(CA)=0.45 is in a perfectly ordered knitting feature. However, with gradual addition of the linear polymer same as block C on ABC 3-miktoarm star terpolymer into the system, the density patterns evolve with the volume fraction of the linear polymer from the ordered knitting patterns into the hexagonal patterns. Furthermore, with addition of linear polymers same as block A, lamellar microstructure has finally resulted. The simulation points out a way for designing and manufacturing nanomaterials with totally different microstructures.

The lipid membrane plays crucial roles in countless biologic processes, ranging from cell motility, endo-and exocytosis, and cell division to protein aggregation and trafficking. To gain a molecular insight in these biologic processes, the recently developed mesoscale simulation technique, dissipative particle dynamics (DPD) simulation, has become an invaluable tool. By providing a brief survey of existing atomistic and popular coarse-grained models used today in studying the dynamics (including vesicle formation and (protein-mediated) vesicle fusion) and phase behavior of lipid bilayers, this review illustrates how mesoscopic DPD models can be used to obtain a better understanding of these biologic processes currently inaccessible to atomistic and most coarse-grained models.

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Using replica-exchange multicanonical Monte Carlo simulation, the aggregates of two homopolymers were numerically investigated through the microcanonical analysis method. The microcanonical entropy showed one convex function in the transition region, leading to a negative microcanonical specific heat. The origin of temperature backbending was the rearrangement of the segments during the process of aggregation; this aggregation process proceeded via a nucleation and growth mechanism. It was observed that the segments with a sequence number from 10 to 13 in the polymer chain have leading effects on the aggregation.

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