Molecular Dynamics Simulations of Colloidal Semiconductor Nanocrystals

Colloidal semiconductor nanocrystals (NCs), or quantum dots (QDs), have emerged as a promising research topic due to their distinctive optical and optoelectronic properties. Their impact and relevance, which have been endorsed through this year’s Nobel Prize in Chemistry, have posed the need for a comprehensive understanding of how the nanoscale impacts semiconductors, enabling the manipulation of synthetic protocols, the tuning of their size and properties and making them suitable for a wide range of technological applications. A true to life theoretical description of the structural and optoelectronic characteristics of these materials should investigate the atomistic processes occurring on their surfaces and the interactions taking place between the different components of the system. The dynamic evolution of these interactions can be investigated by molecular dynamic (MD) simulations, which track the variations of the positions and velocities of the components over time, yielding a position-update relation (trajectory). Classical or molecular-mechanical (MM) methodologies, based on classical force fields (FF), can provide an effective computational aid, as their low computational cost allows for the simulation of models whose sizes and shapes align with experimental observations, and long timescale simulations. This thesis will first tackle the optimization and validation of a classical FF model for the description of NC models of two of the main groups of colloidal semiconductor NCs: perovskites, particularly CsPbBr3, and III-V NC NCs models, both capped by organic ligands. FF models have then been employed for the investigation of two case studies: (i) the role played by different ligand precursors and their ratios in the synthesis of colloidal InAs tetrapods, and (ii) the key dynamic features displayed by oleate ligand binding on the surface of CdSe NCs for performance optimization and stability.