Multi-scale molecular dynamics of perovskite quantum dots: from atomic fluctuations to predictive stability design.

contextPerovskite quantum dots (PQDs) are promising nanomaterials for optoelectronic and energy-conversion applications due to their high photoluminescence quantum yield, tunable bandgap, and defect tolerance. However, their soft ionic lattices exhibit dynamic disorder, anharmonic vibrations, and ion migration, leading to challenges in structural and optoelectronic stability. This review elucidates how molecular dynamics (MD) simulations decode the interplay of atomic fluctuations, lattice dynamics, and surface reconstruction in PQDs, revealing mechanisms governing their stability and performance. It highlights how multi-scale MD frameworks link femtosecond-scale atomic motions to microsecond-scale degradation processes, enabling predictive design of resilient PQDs. Key findings include the role of anharmonic lattice vibrations in defect tolerance, the impact of surface ligand dynamics on emission linewidth, and the mitigation of ion migration through matrix embedding, offering strategies for enhanced device reliability.

methodsClassical molecular dynamics (CMD) simulations employ Lennard-Jones, Buckingham, ReaxFF, and COMB3 force fields to model mesoscale phenomena, including ligand rearrangement and surface fusion. Ab initio molecular dynamics (AIMD) uses density functional theory (DFT) with PBE and HSE06 functionals, typically with plane-wave basis sets (e.g., PAW), to capture ion-electron coupling and lattice anharmonicity. Nonadiabatic molecular dynamics (NAMD) incorporates surface hopping to simulate ultrafast charge transfer. Machine-learning potentials, trained via neural networks and Gaussian processes, enhance sampling with metadynamics and replica-exchange techniques.