Researchers have developed a simulation method to determine the properties of molecular enclosures based on slow growth thermodynamic integration (SGTI).
Molecular enclosures appear often in both solid-state materials and biological systems, including nanoporous materials for energy storage and nanolipid particles for drug delivery. The constituent ions and molecules within these enclosures can largely determine the properties and performance of the entire system. Therefore, it is critical to determine their density, relative concentration, arrangement, physical and electronic structure, viscosity, diffusivity, and other properties. However, these properties can vary dramatically, yet often remain poorly understood. So improving understanding of how these systems are assembled can improve their design and efficacy in a variety of applications.
Working together, researchers at the University of California, Davis and collaborators at Lawrence Livermore National Laboratory have developed a simulation method based on SGTI that improves understanding of the properties of molecular enclosures. SGTI is an improvement compared to standard thermodynamic integration (TI), because SGTI only requires knowledge of the initial state, while TI requires knowledge of states along the entire integration. The SGTI method developed employs a spliced soft-core interaction potential (SSCP) that is designed to more accurately represent the target hard-core interaction potential (HCP). The proposed method allows proper wall thickness to be maintained when filling an enclosure, an important consideration when attempting to maintain the target thickness of the enclosure's wall. The proposed SSCP can be used in any system employing a standard soft[core potential (SCP), and should be tunable to outperform previously-used SCPs in a wide variety of applications.
Country | Type | Number | Dated | Case |
United States Of America | Issued Patent | 11,734,478 | 08/22/2023 | 2019-572 |
Additional Patent Pending
Carbon nanotube, Molecular dynamics, Simulation, Soft-core, Thermodynamic integration