Engulfing Behavior of Nanoparticles into Thermoresponsive Microgels: A Mesoscopic Simulation Study.

The engulfing of nanoparticles into microgels provides a versatile platform to design nano- and microstructured materials with various shape anisotropies and multifunctional properties. Manipulating the spontaneous engulfment process remains elusive. Herein, we report a mesoscopic simulation study on the engulfing behavior of nanoparticles into thermoresponsive microgels. The effects of the multiple parameters, including binding strength, temperature, and nanoparticle size, are examined systematically. Our simulation results disclose three engulfing states at different temperatures, namely full-engulfing, half-engulfing, and surface contact. The engulfing depth is determined by the complementary balance of interfacial elastocapillarity. Specifically, the van der Waals interaction of hybrid microgel-nanoparticle offers the capillary force while the internally networked structure of microgel reinforces the elasticity repulsion. Our study, validated by relevant experimental results, provides a mechanistic understanding of the interfacial elastocapillarity for nanoparticle-microgels.

Enhancing Gas Solubility in Nanopores: A Combined Study Using Classical Density Functional Theory and Machine Learning.

Geometrical confinement has a large impact on gas solubilities in nanoscale pores. This phenomenon is closely associated with heterogeneous catalysis, shale gas extraction, phase separation, etc. Whereas several experimental and theoretical studies have been conducted that provide meaningful insights into the over-solubility and under-solubility of different gases in confined solvents, the microscopic mechanism for regulating the gas solubility remains unclear. Here, we report a hybrid theoretical study for unraveling the regulation mechanism by combining classical density functional theory (CDFT) with machine learning (ML). Specifically, CDFT is employed to predict the solubility of argon in various solvents confined in nanopores of different types and pore widths, and these case studies then supply a valid training set to ML for further investigation. Finally, the dominant parameters that affect the gas solubility are identified, and a criterion is obtained to determine whether a confined gas-solvent system is enhance-beneficial or reduce-beneficial. Our findings provide theoretical guidance for predicting and regulating gas solubilities in nanopores. In addition, the hybrid method proposed in this work sets up a feasible platform for investigating complex interfacial systems with multiple controlling parameters.

A reaction density functional theory study of the solvent effect in prototype SN2 reactions in aqueous solution.

The bimolecular nucleophilic substitution (SN2) reaction is a fundamental and representative reaction in organic chemistry, and the reaction rate is sensitive to the choice of underlying solvents. Herein, we investigate the solvent effect on the free energy profiles of two paradigm reactions in aqueous solution, i.e., symmetric and asymmetric SN2 reactions, by using the proposed multiscale reaction density functional theory (RxDFT) method, which employs quantum density functional theory for calculating the intrinsic reaction free energy coupled with classical density functional theory for addressing solvation contribution. The solvent effect is quantitatively addressed with RxDFT by examining the changes in the free energy profile of the chemical reaction from the gas phase to the aqueous solution. The complete descriptions of the free energy profiles in aqueous solution for the SN2 reactions based on RxDFT agree well with the results from the Specific Reaction Parameterization (SRP) quantum model, QM/MM and the RISM/SCF method. Overall, the RxDFT method is an efficient tool to predict the free energy profile and address the solvent effect of chemical reactions with satisfactory accuracy and low computational cost.

Membrane Wrapping Pathway of Injectable Hydrogels: From Vertical Capillary Adhesion to Lateral Compressed Wrapping.

Membrane wrapping pathway of injectable hydrogels (IHs) plays a vital role in the nanocarrier effectiveness and biomedical safety. Although considerable progress in understanding this complicated process has been made, the mechanism behind this process has remained elusive. Herein, with the help of large-scale dissipative particle dynamics simulations, we explore the molecular mechanism of membrane wrapping by systematically examining the IH architectures and hydrogel-lipid binding strengths. To the best of our knowledge, this is the first report on the membrane wrapping pathway on which IHs transform from vertical capillary adhesion to lateral compressed wrapping. This transformation results from the elastocapillary deformation of networked gels and nanoscale confinement of the bilayer membrane, and it takes long time for the IHs to be fully wrapped owing to the high energy barriers and wrapping-induced shape deformation. Collapsed morphologies and small compressed angles are identified in the IH capsules with a thick shell or strong binding strength to lipids. In addition, the IHs binding intensively to the membrane exhibit special nanoscale mixing and favorable deformability during the wrapping process. Our study provides a detailed mechanistic understanding of the influence of architecture and binding strength on the IH membrane wrapping efficiency. This work may serve as rational guidance for the design and fabrication of IH-based drug carriers and tissue engineering.