Prediction of water transport properties on an anisotropic wetting surface via deep learning.

Understanding the water flow behavior on an anisotropic wetting surface is of practical significance in nanofluidic devices for their performance improvement. However, current methods of experiments and simulations face challenges in measuring water transportation in real time and visually displaying it. Here, molecular dynamics simulation was integrated with our developed multi-attribute point cloud dataset and a customized network of deep learning to achieve mapping from an anisotropic wetting surface to the static and dynamic behaviors of water molecules and realize the high-performance prediction of water transport behavior. More importantly, for the chaotic phenomenon of water molecule flow caused by thermal fluctuation and limited sampling, we proposed a nanoparticle tracking optimization strategy to improve the prediction performance of the velocity field. The prediction results proved that the deep learning framework proposed in this work had superior performance in terms of accuracy, computational cost and visualization, and had the potential for generality to model the transport behavior of different molecules. Our framework can be expected to motivate the development of real-time water flow prediction at an interface and contribute to the optimization and design of surface structures in nanofluidic devices.

Uncovering the Mechanism of Size Effect on the Thermomechanical Properties of Highly Cross-Linked Epoxy Resins.

Epoxy resins are widely used as matrix resins, especially for carbon-fiber-reinforced plastic, due to their outstanding physical and mechanical properties. To date, most research into cross-linking processes using simulation has considered only a distance-based criterion to judge the probability of reaction. In this work, a new algorithm was developed for use with the large-scale atomic/molecular massively parallel simulator (LAMMPS) simulation package to study the cross-linking process; this new approach combines both a distance-based criterion and several kinetic criteria to identify whether the reaction has occurred. Using this simulation framework, we investigated the effect of model size on predicted thermomechanical properties of three different structural systems: diglycidyl ether of bisphenol A (DGEBA)/4,4'-diaminodiphenyl sulfone (4,4'-DDS), DGEBA/diethylenetriamine (DETA), and tetraglycidyl diaminodiphenylmethane (TGDDM)/4,4'-DDS. Derived values of gel point, volume shrinkage, and cross-linked resin density were found to be insensitive to model size in these three systems. Other thermomechanical properties, i.e., glass-transition temperature, Young's modulus, and yield stress, were found to reach stable values for systems larger than ∼40 000 atoms for both DGEBA/4,4'-DDS and DGEBA/DETA. However, these same properties modeled for TGDDM/4,4'-DDS did not stabilize until the system size reached 50 000 atoms. Our results provide general guidelines for simulation system size and procedures to more accurately predict the thermomechanical properties of epoxy resins.

Super Ductility of Nanoglass Aluminium Nitride.

Ceramics have been widely used in many fields because of their distinctive properties, however, brittle fracture usually limits their application. To solve this problem, nanoglass ceramics were developed. In this article, we numerically investigated the mechanical properties of nanoglass aluminium nitride (ng-AlN) with different glassy grain sizes under tension using molecular dynamics simulations. It was found that ng-AlN exhibits super ductility and tends to deform uniformly without the formation of voids as the glassy grain size decreases to about 1 nm, which was attributed to a large number of uniformly distributed shear transformation zones (STZs). We further investigated the effects of temperature and strain rate on ng-AlNd = 1 nm, which showed that temperature insignificantly influences the elastic modulus, while the dependence of the ultimate strength on temperature follows the T2/3 scaling law. Meanwhile, the ultimate strength of ng-AlNd = 1 nm is positively correlated with the strain rate, following a power function relationship.

Molecular dynamics study of strengthening mechanism of nanolaminated graphene/Cu composites under compression.

Molecular dynamics simulations of nanolaminated graphene/Cu (NGCu) and pure Cu under compression are conducted to investigate the underlying strengthening mechanism of graphene and the effect of lamella thickness. It is found that the stress-strain curves of NGCu undergo 3 regimes i.e. the elastic regime I, plastic strengthening regime II and plastic flow regime III. Incorporating graphene monolayer is proved to simultaneously contribute to the strength and ductility of the composites and the lamella thickness has a great effect on the mechanical properties of NGCu composites. Different strengthening mechanisms play main role in different regimes, the transition of mechanisms is found to be related to the deformation behavior. Graphene affected zone is developed and integrated with rule of mixtures and confined layer slip model to describe the elastic properties of NGCu and the strengthening effect of the incorporated graphene.

Investigation of Interaction between Dislocation Loop and Coherent Twin Boundary in BCC Ta Film during Nanoindentation.

In this work, the interaction between dislocation loop (DL) and coherent twin boundary (CTB) in a body-centered cubic (BCC) tantalum (Ta) film during nanoindentation was investigated with molecular dynamics (MD) simulation. The formation and propagation of <111> full DLs in the nanotwinned (nt) Ta film during the indentation was observed, and it was found that CTB can strongly affect the stress distribution in the Ta film, and thus change the motion and type of dislocations. There are three kinds of mechanisms for the interaction between DL and CTB in a twinned BCC Ta film: (i) dislocation absorption, (ii) dislocation desorption, and (iii) direct slip transmission. The nucleation of twin boundary dislocations and the formation of the steps in CTB were also observed during the indentation. The mechanisms presented in this work can provide atomic images for understanding the plastic deformation of BCC metals with mirror-symmetry grain boundary structures, and provide available information for the evaluation and design of high-performance nt BCC metallic thin film coatings.

Codelivery of a miR-124 Mimic and Obatoclax by Cholesterol-Penetratin Micelles Simultaneously Induces Apoptosis and Inhibits Autophagic Flux in Breast Cancer in Vitro and in Vivo.

Penetratin is a classical cell-penetrating peptide with the potential to assist in the transmembrane delivery of proteins or drugs. However, the synthesis and application of cholesterol-penetratin (Chol-P) conjugates as nonviral delivery systems for microRNAs or drugs have not previously been reported. In this study, the amphiphilic Chol-P was shown to self-assemble into micelles and efficiently deliver miR-124 and obatoclax. The codelivered miR-124-M-Oba had a homogeneous particle size and a positive zeta potential. Treatment with miR-124 mincreased cytotoxicity, and cell proliferation, was promoted by miR-124 inhibitor-loaded micelles in MCF-7 human breast cancer cells. Moreover, the inhibitory effects on cell proliferation, colony formation, and cell migration were increased in the miR-124-M-Oba group compared to the miR-124-M group. miR-124-M-Oba induced higher levels of mitochondrial apoptosis via Bax and caspase-9 activation. In addition, we found that the cationic Chol-P and miR-124-M could potently induce autophagy, and miR-124 was degraded in the corresponding autophagolysosomes. The obatoclax encapsulated in miR-124-M-Oba could inhibit the degradation of miR-124 and p62 in autophagolysosomes, which consequently maintained the concentration of miR-124 in breast cancer cells. Furthermore, miR-124-M-Oba potently inhibited tumor growth in subcutaneous xenograft breast cancer models. In summary, the miR-124-M-Oba prepared in this work showed improved apoptosis induction and autophagic flux inhibitory effects in MCF-7 cells, and miR-124-M-Oba may have potential applications in breast cancer therapy.

Discovery and in vivo evaluation of novel RGD-modified lipid-polymer hybrid nanoparticles for targeted drug delivery.

In the current study, the lipid-shell and polymer-core hybrid nanoparticles (lpNPs) modified by Arg-Gly-Asp(RGD) peptide, loaded with curcumin (Cur), were developed by emulsification-solvent volatilization method. The RGD-modified hybrid nanoparticles (RGD-lpNPs) could overcome the poor water solubility of Cur to meet the requirement of intravenous administration and tumor active targeting. The obtained optimal RGD-lpNPs, composed of PLGA (poly(lactic-co-glycolic acid))-mPEG (methoxyl poly(ethylene- glycol)), RGD-polyethylene glycol (PEG)-cholesterol (Chol) copolymers and lipids, had good entrapment efficiency, submicron size and negatively neutral surface charge. The core-shell structure of RGD-lpNPs was verified by TEM. Cytotoxicity analysis demonstrated that the RGD-lpNPs encapsulated Cur retained potent anti-tumor effects. Flow cytometry analysis revealed the cellular uptake of Cur encapsulated in the RGD-lpNPs was increased for human umbilical vein endothelial cells (HUVEC). Furthermore, Cur loaded RGD-lpNPs were more effective in inhibiting tumor growth in a subcutaneous B16 melanoma tumor model. The results of immunofluorescent and immunohistochemical studies by Cur loaded RGD-lpNPs therapies indicated that more apoptotic cells, fewer microvessels, and fewer proliferation-positive cells were observed. In conclusion, RGD-lpNPs encapsulating Cur were developed with enhanced anti-tumor activity in melanoma, and Cur loaded RGD-lpNPs represent an excellent tumor targeted formulation of Cur which might be an attractive candidate for cancer therapy.