Dry and wet nanoparticulate systems are encountered in a variety of applications including pharmaceutics, biomedical and chemical processing. In understanding and optimization of these systems, an accurate predictive capacity is critical. Since the physics of the interacting force fields in such systems are complex, a multi-scale approach is necessary, requiring large-scale simulations. The proposed research aims to develop cost-effective and accurate predictive approaches for multi-scale computations of nanoparticulate systems.
Multiscale dynamics simulation of self-assembly and transport of nanoparticles in both dry and wet nanoparticulate systems will be performed by integrating sub-models at different scales using data-enabled approaches. The unique behavior of the dry particulate systems is that they present both solid-like and liquid-like features leading to a number of fascinating characters. Understanding the transport of nanoparticles in wet particulate systems through multi-scale computation will significantly improve the process by revealing dominant parameters to obtain desirable final nanostructure. An "objective-driven" method will be utilized to regenerate appropriate parameter sets by combining Ab initio calculation for interatomic force construction and Monte Carlo optimization of parameters. A multiscale computation, which covers atom-atom, atom-cluster, and cluster-cluster scales, will be carried out through a data-stream support methodology. Through atom-atom level simulation, crucial sets of force field (FF) parameters will be generated; the atom-cluster level computation will mainly investigate interactions between a single or a group of clusters (nanoparticles) and immersing flowing liquid molecules. Once all the infrastructures are well established via reconstructing innovative cage particle and porting to extensible LAMMPS, many phenomena associated with self-assembly and transport in nanoparticulate systems can be rigorously computed under this framework.
The general "objective-driven" method will be implemented into software to meet needs of many optimizations works, including obtaining desired FF parameters. The newly developed atomic style-cage granule and other sub-models will further empower the open-source molecular dynamics code LAMMPS, which has a very large number of users around the world. Since the code is also compatible to LIGGGHTS (based on LAMMPS) and CFDEM (a combination of LAMMPS and OpenFOAM), their users will also definitely benefit from the functionalities and data obtained from this project. The outcome of the research will be disseminated through publications in archival journals, presentations at national and international conferences, and students' thesis/dissertations. The proposed outreach activities will also help promoting the public awareness and recognition of science and engineering and promote the public image of scientists and engineers, which will play a very important role in education in all levels and may also have broader impacts on technology, economy, and society.
