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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/227982
A transferable molecular model for accurate thermodynamic studies of water in large-scale systems
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Water is essential for life, and its unique properties present significant scientific challenges because of our limited understanding of its thermodynamic behavior. This knowledge gap hinders the accurate theoretical replication of water's properties across various temperatures and pressures, mainly due to the complex quantum nature of its many-body interactions. To address this challenge, we developed a novel molecular model for bulk liquid water that focuses on the hydrogen bond network and its cooperativity. We show that these factors are crucial to controlling water's thermodynamics. Our study introduces an innovative strategy to derive many-body parameters from quantum calculations, validated by advanced polarizable models and calibrated with experimental data under ambient conditions. Our results demonstrate that this model accurately predicts water's equation of state and response functions over a temperature range of approximately 60 degrees at atmospheric pressure and around 40 degrees up to 50 MPa. This quantitative validation underscores the model's reliability and transferability, providing new insights into water's cooperative fluctuations across a broader range of thermodynamic conditions than previously achieved. Moreover, our model's computational efficiency allows for scalability in simulating water droplets nearing micrometer sizes without extensive computational resources or long simulation times. This breakthrough holds significant theoretical and technological implications, opening avenues for advanced research across various scientific fields and applications.
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CORONAS, Luis Enrique, VILANOVA, Oriol and FRANZESE, Giancarlo. A transferable molecular model for accurate thermodynamic studies of water in large-scale systems. Journal of Molecular Liquids. 2025. Vol. 434. ISSN 0167-7322. [consulted: 10 of June of 2026]. Available at: https://hdl.handle.net/2445/227982