Kovalenko A.
National Institute for Nanotechnology, CA
Keywords: ionic liquids, molecular theory of solvation, nanochemistry, nanoporous carbon, organic rosette nanotubes, solution, supercapacitor
Predictive molecular modeling of nanosystems in solution, important in many applications, requires long-time description of millions molecules, which is by far not feasible with ab initio methods, challenging for molecular simulations, and problematic for continuum theories which are phenomenological and non-transferable. Statistical-mechanical, molecular theory of solvation (3D-RISM) operates with 3D distributions of species in the statistical ensemble rather than with molecular trajectories and predicts from the first principles the solvation structure and thermodynamics of nanosystems. It properly accounts for chemical functionalities by representing both electrostatic and non-polar features of the solvation structure, such as hydrogen bonding, solvophobicity, salt bridges, structural solvent, associative and electrochemical effects. We have coupled the 3D-RISM theory with ab initio quantum chemistry methods in a self-consistent description of electronic structure, optimized geometry, and chemical reactions in solution, and have extensively validated the KS-DFT/3D-RISM-KH multiscale method against experimental data for solvation thermochemistry, conformational equilibria, tautomerization energies and activation barriers for various nanosystems in different solvents. This presentation exhibits our recent works explaining experimental results for the electronic and solvation structure of ionic liquids, mechanisms of self-assembly, conformational stability and solvent-driven supramolecular chirality of synthetic organic rosette nanotubes, and mechanisms of sorption and supercapacitance for nanoporous carbon electrodes.
Journal: TechConnect Briefs
Volume: 2, Nanotechnology 2010: Electronics, Devices, Fabrication, MEMS, Fluidics and Computational
Published: June 21, 2010
Pages: 665 - 668
Industry sectors: Advanced Materials & Manufacturing | Sensors, MEMS, Electronics
Topic: Informatics, Modeling & Simulation
ISBN: 978-1-4398-3402-2