Molecular modeling of water and aqueous electrolytes under electric field: thermal, dielectric, and transport properties

Water plays a critical role in thermal transport, electrochemical energy storage, and electrically driven interfacial phenomena. Accurately capturing its coupled thermo-electrical behavior remains a challenge in MD simulations. This study combines machine learning, and MD simulations to provide a computational study of water and electrolyte systems. To increase the predictive accuracy of the TIP4P water model, a machine learning-guided reparameterization has been developed which shows better concordance with experimental dielectric and thermal properties of water. Using this model, the electro-thermal behavior of water under external electric fields has been investigated. A concentration-driven shift from field-responsive transport to structurally arrested dynamics dominated by ion pairing has been explored further using this model as a solvent in nonequilibrium MD simulations of NaCl and NaClO4 electrolytes. Altogether, this work offers molecular-level under-standing of electro-thermal transport phenomena and creates a foundation for modeling water and electrolyte system for energy device.

Grantor dc:publisher

University of Tennessee at Chattanooga

Year dc:date.available

2027

Author dc:creator

• Dey, Khowshik

Contributors dc:contributor

• Barisik, Murat
• Sreenivas, Kidambi; Ranjan, Reetesh
• College of Engineering and Computer Science

• Energy storage
• Supercapacitors
• Molecules--Models
• Molecular dynamics
• Water as fuel

Licence

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/1083

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-2273