Computer simulation of water and electrolytes : force field development
Scientic Supervisor / Contact Person
Name and Surname
Carlos Vega
ORCID (link)
Researcher ID (link)
Localization & Research Area
Faculty / Institute
Faculty of Chemical Science
Department
Physical Chemistry
Research Area
Chemistry (CHE), Physics (PHY)
MSCA & ERC experience
Research group / research team hosted any MSCA fellow?
Yes
Research group / research team have any ERC beneficiaries?
No
Research Team & Research Topic
Research Team / Research Group Name (if any)
Computer simulation of water and electrolytes : force field development
Website of the Research team / Research Group / Department
Brief description of the Research Team / Research Group / Department
Our group performs computer simulations of liquid and solids, with special interest in water.
In the past our group has developed successful models for water: TIP4P/2005 and TIP4P/ICE. We are experts in obtainin the phase diagram of water from computer simulations, and in determining nucleation rates for the crystallization of ice from supercooled water. Currently we are developing a force field for electrolytes denoted : Madrid-2019 force field.
259 publications, 24000 citations (Google scholar) h index : 70 (google scholar)
Associate Editor of the Journal of Chemical Physis
In the past our group has developed successful models for water: TIP4P/2005 and TIP4P/ICE. We are experts in obtainin the phase diagram of water from computer simulations, and in determining nucleation rates for the crystallization of ice from supercooled water. Currently we are developing a force field for electrolytes denoted : Madrid-2019 force field.
259 publications, 24000 citations (Google scholar) h index : 70 (google scholar)
Associate Editor of the Journal of Chemical Physis
Research lines / projects proposed
Force field development of electrolytes
Studies on nucleation using the seeding technique
Polarizable force fields for water
Machine learning applied to water and electrolytes
Studies on nucleation using the seeding technique
Polarizable force fields for water
Machine learning applied to water and electrolytes
Key words
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