Understanding the chemico-physical properties of colloidal semiconductor nanocrystals (NCs) requires exploration of the dynamic processes occurring at the NC surfaces, in particular at the ligand–NC interface. Classical molecular dynamics (MD) simulations under realistic conditions are a powerful tool to acquire this knowledge because they have good accuracy and are computationally cheap, provided that a set of force-field (FF) parameters is available. In this work, we employed a stochastic algorithm, the adaptive rate Monte Carlo method, to optimize FF parameters of cesium lead halide perovskite (CsPbBr 3 ) NCs passivated with typical organic molecules used in the synthesis of these materials: oleates, phosphonates, sulfonates, and primary and quaternary ammonium ligands. The optimized FF parameters have been obtained against MD reference trajectories computed at the density functional theory level on small NC model systems. We validated our parameters through a comparison of a wide range of nonfitted properties to experimentally available values. With the exception of the NC–phosphonate case, the transferability of the FF model has been successfully tested on realistically sized systems (>5 nm) comprising thousands of passivating organic ligands and solvent molecules, just as those used in experiments.

Synthesis protocols of colloidal semiconductor nanocrystals (NCs) comprise the coordination of the semiconductive inorganic core by a layer of organic ligands, which play a crucial role in stabilizing the NCs...

In the last two decades, colloidal semiconductor nanocrystals have emerged as a phenomenal research topic due to their size-dependent optoelectronic properties and to their outstanding versatility in many technological applications. In this review, we provide an historical account of the most relevant computational works that have been carried out to understand atomistically the electronic structure of these materials, including the main requirements needed for the preparation of nanocrystal models that align well with the experiments. We further discuss how the advancement of these computational tools has affected the analysis of these nanomaterials over the years. We focus our review on the three main families of colloidal semiconductor nanocrystals: group II-VI and IV-VI metal chalcogenides, group III-V metal pnictogenides and metal halides, in particular lead-based halide perovskites. We discuss the most recent research frontiers and outline the future outlooks expected in this field from a computational perspective.