2025/02/14 by Song, Yizhi, Xifan Wu, Wu, Xifan · 1 citation
Physics and Astronomy · #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Spectroscopy and Quantum Chemical Studies
paper · pdf · doi:10.48550/arxiv.2502.09915
openalex publication_date 2025/02/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Understanding the pressure-dependent dielectric properties of water is crucial for a wide range of scientific and practical applications. In this study, we employ a deep neural network trained on density functional theory data to investigate the dielectric properties of liquid water at room temperature across a pressure range of 0.1 MPa to 1000 MPa. We observe a nonlinear increase in the static dielectric constant ε0 with increasing pressure, a trend that is qualitatively consistent with experimental observations. This increase in ε0 is primarily attributed to the increase in water density under compression, which enhances collective dipole fluctuations within the hydrogen-bonding network as well as the dielectric response. Despite the increase in ε0, our results reveal a decrease in the Kirkwood correlation factor GK with increasing pressure. This decrease in GK is attributed to pressure-induced structural distortions in the hydrogen-bonding network, which weaken dipolar correlations by disrupting the ideal tetrahedral arrangement of water molecules.