We perform molecular dynamics (MD) simulations of a water capillary bridge (WCB) expanding between two identical chemically heterogeneous surfaces. The model surfaces, based on the structure of silica, are hydrophobic and are decorated by a hydrophilic (hydroxylated silica) patch that is in contact with the WCB. Our MD simulations results, including the WCB profile and forces induced on the walls, are in agreement with capillarity theory even at the smallest wall separations studied, h = 2.5−3 nm. Remarkably, the energy stored in the WCB can be relatively large, with an energy density that is comparable to that harvested by water-responsive materials used in actuators and nanogenerators.

Relevant to broad applied fields and natural processes, interfacial ionic hydrates have been widely studied by ultrahigh-resolution atomic force microscopy (AFM). However, the complex relationship between AFM signal and the investigated system makes it difficult to determine the atomic structure of such a complex system from AFM images alone. Using machine learning, we achieved precise identification of the atomic structures of interfacial water/ionic hydrates based on AFM images, including the position of each atom and the orientations of water molecules. Furthermore, it was found that structure prediction of ionic hydrates can be achieved cost-effectively by transfer learning using neural network (NN) trained with easily available interfacial water data. Thus, this work provides an efficient and economical methodology which not only opens up avenues to determine atomic structures of more complex systems from AFM images, but may also help to interpret other scientific studies involving sophisticated experimental results.

Quasi-elastic neutron scattering (QENS) has many applications that are directly related to the development of high-performance functional materials and biological macromolecules, especially those containing some water. The analysis method of QENS spectra data is important to obtain parameters that can explain the structure of materials and the dynamics of water. In this paper, we present a revised jump-diffusion and rotation-diffusion model (rJRM) used for QENS spectra data analysis. By the rJRM, the QENS spectra from a pure magnesium-silicate-hydrate (MSH) sample are fitted well for the Q range from 0.3 Å−1 to 1.9 Å−1 and temperatures from 210 K up to 280 K. The fitted parameters can be divided into two kinds. The first kind describes the structure of the MSH sample, including the ratio of immobile water (or bound water) C and the confining radius of mobile water a 0. The second kind describes the dynamics of confined water in pores contained in the MSH sample, including the translational diffusion coefficient D t, the average translational residence time τ 0, the rotational diffusion coefficient D r, and the mean squared displacement (MSD) 〈 u 2 〉 . The rJRM is a new practical method suitable to fit QENS spectra from porous materials, where hydrogen atoms appear in both solid and liquid phases.

The formation of nanoscale water capillary bridges (WCBs) between chemically heterogeneous (patchy) surfaces plays an important role in different scientific and engineering applications, including nanolithography, colloidal aggregation, and bioinspired adhesion. However, the properties of WCB of nanoscale dimensions remain unclear. Using molecular dynamics simulations, we investigate the geometrical and thermodynamic properties of WCB confined between chemically heterogeneous surfaces composed of circular hydrophilic patches on a hydrophobic background. We find that macroscopic capillary theory provides a good description of the WCB geometry and forces induced by the WCB on the confining surfaces even in the case of surface patches with diameters of only 4 nm. Upon stretching, the WCB contact angle changes from hydrophobic-like values (θ > 90°) to hydrophilic-like values (θ < 90°) until it finally breaks down into two droplets at wall separations of ∼ 9–10 nm. We also show that the studied nanoscale WCB can be used to store relevant amounts of energy E P and explore how the walls patch geometry can be improved in order to maximize E P. Our findings show that nanoscale WCB can, in principle, be exploited for the design of clean energy storage devices as well as actuators that respond to changes in relative humidity. The present results can also be of crucial importance for the understanding of water transport in nanoporous media and nanoscale engineering systems.