Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition

• Published in: Nature communications Vol. 15; no. 1; p. 3911
• Main Authors: Linker, T. M., Krishnamoorthy, A., Daemen, L. L., Ramirez-Cuesta, A. J., Nomura, K., Nakano, A., Cheng, Y. Q., Hicks, W. R., Kolesnikov, A. I., Vashishta, P. D.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.05.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 119/118; 639/638/440/94; 639/638/563/981; 639/766/119/1002; Ammonia; Chemical interactions; chemical physics; Crystals; Humanities and Social Sciences; Hydrogen fuels; Inelastic scattering; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Liquid phases; Machine learning; Molecular dynamics; multidisciplinary; Neural networks; Neutron scattering; Neutrons; Phase transitions; Science; Science (multidisciplinary); Spectroscopy; structure of solids and liquids; Theoretical analysis; Vibrations
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-48246-9

Vibrational spectroscopy allows us to understand complex physical and chemical interactions of molecular crystals and liquids such as ammonia, which has recently emerged as a strong hydrogen fuel candidate to support a sustainable society. We report inelastic neutron scattering measurement of vibrational properties of ammonia along the solid-to-liquid phase transition with high enough resolution for direct comparisons to ab-initio simulations. Theoretical analysis reveals the essential role of nuclear quantum effects (NQEs) for correctly describing the intermolecular spectrum as well as high energy intramolecular N-H stretching modes. This is achieved by training neural network models using ab-initio path-integral molecular dynamics (PIMD) simulations, thereby encompassing large spatiotemporal trajectories required to resolve low energy dynamics while retaining NQEs. Our results not only establish the role of NQEs in ammonia but also provide general computational frameworks to study complex molecular systems with NQEs. Through neutron scattering experiments coupled with machine learning, the authors uncover the strong role of nuclear quantum effects in the dynamics of ammonia in both its solid and technologically relevant liquid phase.