Structure and dynamics of water at water–graphene and water–hexagonal boron-nitride sheet interfaces revealed by ab initio sum-frequency generation spectroscopy
Literature Information
Tatsuhiko Ohto, Hirokazu Tada, Yuki Nagata
We simulate sum-frequency generation (SFG) spectra of isotopically diluted water at the water–graphene and water–hexagonal boron-nitride (hBN) sheet interfaces, using ab initio molecular dynamics simulations. A sharp ‘dangling’ O–D peak around ∼2640 cm−1 appearing in both simulated SFG spectra evidences that both graphene and hBN are hydrophobic. The dangling O–D peak is 10 cm−1 red-shifted at the water–hBN interface relative to the peak at the water–graphene interface. This frequency difference gives a stronger O–D⋯N intermolecular interaction between water and hBN than the O–D⋯C interaction between water and graphene. Accordingly, the anisotropy decay of such a dangling O–D group slows down near hBN compared with near graphene, illustrating that the dynamics of the dangling O–D group are also affected by the stronger O–D⋯N interaction than the O–D⋯C interaction. We discuss molecular-level insights into the structure and dynamics of interfacial water in the context of the friction of hBN and graphene.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.












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