(330b) Microscopic Modeling Ligand Crosslinking in Nanopatterning of Quantum Dots (QDs)

The utilization of quantum dots (QDs) for the development of high-resolution displays (HDRs) has garnered significant attention due to their high photoluminescence quantum yield, wide color gamut, tunable optoelectronic properties [1]. The development of HDRs requires precise nanopatterning of QDs to generate tiny RGB pixels, which is a fundamental unit in HDRs. Unfortunately, during repeated nanopatterning of QDs, the deposited QD films are damaged when exposed to various solvents in the post-processing steps [2,3]. Thus, the literature is rife with different approaches for altering the nanopatterning process and developing robust QD films. Amongst various approaches, crosslinking of QD surface ligands to form crosslinked QD network has shown great promise [4,5]. Specifically, such a crosslinked network interlocks the neighboring QDs and increases the QD thin-film resistance during post-processing. For this method, crosslinker structure, and the number of crosslinkers have significant effects on the crosslinking performance. However, experiments could not fully ascertain the mechanism of the crosslinking process [4]. To this end, a kinetic Monte Carlo (kMC) model is developed to elucidate the mechanism and kinetics of the crosslinking process. Specifically, the ligand crosslinking reaction is broken down into two sub-steps (i.e., radical formation, and a C-H insertion reaction). Then, the surface reaction kinetics for these two sub-steps is modeled and integrated with a 2D kMC lattice. In this model, different spatial crosslinking configurations between the crosslinkers and ligands are reflected considering the geometry, dimensions, and structure of the crosslinkers. For example, the crosslinking efficiency of planar 4-armed crosslinkers is found to be higher with tetrahedral 2-armed crosslinkers because of their structural compatibility with the surface-ligand shell and the two additional crosslinking arms. Overall, a) the developed kMC model virtually probes into the crosslinking mechanism; b) helps quantify the crosslinking performance of different crosslinkers, and c) the simulation results are in excellent agreement with the experimental observations.

References:

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