A Molecular Dynamics Analysis of the Thickness and Adhesion Characteristics of the Quasi-Liquid Layer at the Asphalt-Ice Interface.

The quasi-liquid layer (QLL), a microstructure located between ice and an adhering substrate, is critical in generating capillary pressure, which in turn influences ice adhesion behavior. This study employed molecular dynamics (MD) methods to obtain QLL thickness and utilized these measurements to estimate the adhesive strength between ice and asphalt. The research involved constructing an ice-QLL-asphalt MD model, encompassing four asphalt types and five temperature ranges from 250 K to 270 K. The QLL thickness was determined for various asphalts and temperatures using the tetrahedral order parameter gradient. Additionally, capillary pressure was calculated based on the QLL thickness and other geometric parameters obtained from the MD analysis. These findings were then compared with ice adhesion strength data acquired from pull-off tests. The results indicate that QLL thickness varies with different asphalt types and increases with temperature. At a constant temperature, the QLL thickness decreases in the order of the basal plane, primary prism plane, and secondary prism plane. Furthermore, the adhesion strength of the QLL diminishes as the temperature rises, attributed to the disruption of hydrogen bonds at lower temperatures. The greater the polarity of the asphalt's interface molecules, the stronger the adhesion strength and binding free energy. The MD simulations of the asphalt-ice interface offer insights into the atomic-scale adhesive properties of this interface, contributing to the enhancement in QLL property prediction and calibration at larger scales.

Constructing Electrically and Mechanically Self-Healing Elastomers by Hydrogen Bonded Intermolecular Network.

One key limitation of artificial skin-like materials is the shortened service life caused by mechanical damages during practical applications. The ability to self-heal can effectively extend the material service life, reduce the maintenance cost, and ensure safety. Therefore, it is important and necessary to fabricate materials with simultaneously mechanical and electrical self-healing behavior in a facile and convenient way. Herein, we report a stretchable and conductive self-healing elastomer based on intermolecular networks between poly(acrylic acid) (PAA) and reduced graphene oxide (rGO) through a facile and convenient postreduction and one-pot method. The introduction of rGO provides the PAA-GO elastomers with good mechanical stability and electrical properties. Moreover, this material exhibited both electrical and mechanical self-healing properties. After cutting, the elastomers self-healed quickly (∼30 s) and efficiently (∼95%) at room temperature. The elastomers were accurate and reliable in detecting external strain even after healing. The elastomers were further applied for strain sensors, which were attached directly to human skin to monitor external movements, including finger bending and wrist twisting.