Molecular Dynamics of Janus Nanodimers Dispersed in Lamellar Phases of a Block Copolymer

Dispersion and Diffusion Mechanism of Nanofillers with Different Geometries in Bottlebrush Polymers: Insights from Molecular Dynamics Simulation

The dispersion and diffusion mechanism of nanofillers in polymer nanocomposites (PNCs) are crucial for understanding the properties of PNCs, which is of great significance for the design of novel materials. Herein, we investigate the dispersion and diffusion behavior of two geometries of nanofillers, namely, spherical nanoparticles (SNPs) and nanorods (NRs), in bottlebrush polymers by utilizing coarse-grained molecular dynamics simulations. With the increase of the interaction strength between the nanofiller and polymer (ε_np), both the SNPs and NRs experience a typical "aggregated phase-dispersed phase-bridged phase" state transition in the bottlebrush polymer matrix. We evaluate the validity of the Stokes-Einstein (SE) equation for predicting the diffusion coefficient of nanofillers in bottlebrush polymers. The results demonstrate that the SE predictions are slightly larger than the simulated values for small SNP sizes because the local viscosity that is felt by small SNPs in the densely grafted bottlebrush polymer does not differ much from the macroscopic viscosity. The relative size of the length of the NRs (L) and the radius of gyration (R_g) of the bottlebrush polymer play a key role in the diffusion of NRs. In addition, we characterize the anisotropic diffusion of NRs to analyze their translational and rotational diffusion. The motion of NRs in the direction perpendicular to the end-to-end vector is more hindered, indicating that there is a strong coupling between the rotation of NRs and the motion of the polymer. The NR motion shows stronger anisotropic diffusion at short time scales because of the steric effects generated by side chains of the bottlebrush polymer. In general, our results provide a fundamental understanding of the dispersion of nanofillers and the microscopic mechanism of nanofiller diffusion in bottlebrush polymers.

Performance Test of Micro-Slit Antenna Loaded with High Refractive Index Medium Based on Image Recognition

Image recognition is the pattern recognition of images. Simply put, it is the prescribed use of the pattern recognition technology in the image. It creates an image recognition template for the input of image information, analyzes and extracts the shape characteristics of the image, and then creates a classifier, relying on the shape of the image classified. However, since particles with high refractive index media can detect galvanic couples and magnetic dipoles together under the excitation of an external field, the interference of the radiation fields of galvanic couples and magnetic dipoles can be used to adjust the incident field. For the study of nanocubes with high refractive index media, the polarization phase of the nanocube particle environment is obtained by the method of long-distance propagation. The loaded micro-slit antenna is also a kind of aperture antenna, which is formed by opening a hole in the metal surface, and the hole will emit electromagnetic waves from the outside of the unit. Loaded micro-slit antennas have a variety of shapes, and they have many advantages such as sturdy structure, fast handling, convenient feeding, and being simple, compact, concealed, and decorative. Therefore, it is necessary to verify various performance parameters of the system by simulating performance tests and to verify the performance of the system by simulating various normal, high load, and abnormal load conditions. The performance test includes load and stress tests, and they can be used together. The purpose of load testing is to clarify the performance of the system under different tasks and to verify the changes in various system performance parameters as the load gradually increases.

Entropic control of nanoparticle self-assembly through confinement

Entropy can be the sole driving force for the construction and regulation of ordered structures of soft matter systems. Specifically, under confinement, the entropic penalty could induce enhanced entropic effects which potentially generate visually ordered structures. Therefore, spatial confinement or a crowding environment offers an important approach to control entropy effects in these systems. Here, we review how spatial confinement-mediated entropic effects accurately and even dynamically control the self-assembly of nanoscale objects into ordered structures, focusing on our efforts towards computer simulations and theoretical analysis. First, we introduce the basic principle of entropic ordering through confinement. We then introduce the applications of this concept to various systems containing nanoparticles, including polymer nanocomposites, biological macromolecular systems and macromolecular colloids. Finally, the future directions and challenges for tailoring nanoparticle organization through spatial confinement-mediated entropic effects are detailed. We expect that this review could stimulate further efforts in the fundamental research on the relationship between confinement and entropy and in the applications of this concept for designer nanomaterials.

Hybrid Time-Dependent Ginzburg–Landau Simulations of Block Copolymer Nanocomposites: Nanoparticle Anisotropy

Block copolymer melts are perfect candidates to template the position of colloidal nanoparticles in the nanoscale, on top of their well-known suitability for lithography applications. This is due to their ability to self-assemble into periodic ordered structures, in which nanoparticles can segregate depending on the polymer–particle interactions, size and shape. The resulting coassembled structure can be highly ordered as a combination of both the polymeric and colloidal properties. The time-dependent Ginzburg–Landau model for the block copolymer was combined with Brownian dynamics for nanoparticles, resulting in an efficient mesoscopic model to study the complex behaviour of block copolymer nanocomposites. This review covers recent developments of the time-dependent Ginzburg–Landau/Brownian dynamics scheme. This includes efforts to parallelise the numerical scheme and applications of the model. The validity of the model is studied by comparing simulation and experimental results for isotropic nanoparticles. Extensions to simulate nonspherical and inhomogeneous nanoparticles are discussed and simulation results are discussed. The time-dependent Ginzburg–Landau/Brownian dynamics scheme is shown to be a flexible method which can account for the relatively large system sizes required to study block copolymer nanocomposite systems, while being easily extensible to simulate nonspherical nanoparticles.