Decoding the Hydrogen Bond Network of Water in Carbon Nanotubes with Atomistic Simulations

Improved understanding of confined aqueous solutions is critical for a wide range of applications, from water desalination to energy storage. However, probing the structure of confined water with experimental techniques remains a significant challenge. In this work, we use large-scale molecular dynamics simulations with a machine learning potential to compute the infrared (IR) spectrum of water in carbon nanotubes (CNTs). The theoretical spectra are then combined with existing experiments to elucidate how and when the hydrogen bond network of water is altered by confinement. We confirm that water undergoes an order-disorder transition within a CNT diameter of approximately 1.2 nm. For wider CNTs, confinement imposes a monotonic disruptive effect on the hydrogen bond network of water, which decays slowly with CNT diameter. In sharp contrast, confinement in narrower CNT pores affects water structure in a complex and non-linear fashion. Our study reveals peculiar hydrogen-bond network of confined water and it provides new interpretation for infrared spectroscopic measurements. This work also offers a general platform to simulate water in CNTs with quantum accuracy at time and length scales beyond-reach of conventional quantum-mechanical approaches.