(161b) How to Design a Fast Nanocar
AIChE Annual Meeting
2019
2019 AIChE Annual Meeting
Computational Molecular Science and Engineering Forum
Software Engineering in and for the Molecular Sciences
Monday, November 11, 2019 - 12:45pm to 1:00pm
In this work we developed a nanocar builder tool that can be used with a user interface and/or as a Python library for automated building of nanocars. Nanocars are single molecule vehicles that resemble macroscopic automobiles and they are important for understanding how to control molecular diffusion on surfaces. This process is commonly utilized in cells to transport molecular cargo: enzyme molecules are moved along protein filament tracks converting chemical energy into mechanical work. The nanocar builder tool was developed as a plug-in for Avogadro 2 molecular visualizer and a complementary Python package was developed to perform the geometric operations for building the nanocar. The current release allows users to build a nanocar molecule from components of chassis and wheel molecules. Additionally, users can build a metal surface to place the molecular car and assign force field parameters for the system which provides an initial configuration to study diffusion behavior of these molecules. Using the nanocar builder Python library we generated hypothetical nanocars and studied their diffusion using Molecular Dynamics simulations. We investigated how the molecular interactions effect the diffusion of nanocars and outlined guidelines on how to design faster nanocars.
Currently, the plug-in is available on GitHub (https://github.com/kbsezginel/nanocar-avogadro) including a webpage where users can find detailed written instructions on installation and usage, as well as video tutorials (https://kbsezginel.github.io/nanocar-avogadro). With the upcoming 2nd International Nanocar Race our nanocar builder can be used to improve nanocar designs by understanding how the molecular components of the nanocar affect the diffusion behavior. Additionally, we believe this plug-in serves as a proof-of-concept for a unique platform to build complex molecular machine systems.