# Machine Vision-Enabled Octahedral Network Reconstruction and Structural Analysis of Perovskite Quantum Dots

## TL;DR

This paper introduces a machine vision method to analyze the atomic structure of perovskite quantum dots, revealing how their octahedral networks affect material properties.

## Contribution

A novel machine vision approach is introduced for high-fidelity structural analysis of perovskite quantum dots using low-dose STEM imaging.

## Key findings

- CsPbI3 quantum dots show reduced PbX6 octahedral tilting in outer unit cells, forming isotropic core–shell features.
- Mixed-halide CsPbI3–xBrx QDs exhibit inhomogeneous and anisotropic octahedral tilting due to dopant segregation and phase instability.
- The method enables precise lattice parameter extraction and establishes atomic-scale structure–property relationships in perovskite nanomaterials.

## Abstract

The structural framework
of metal-halide perovskites
is defined
by corner-sharing PbX6 octahedra, whose tilts, distortions,
and connectivity dictate the phase stability, carrier dynamics, and
optoelectronic performance. Despite their pivotal role, direct experimental
analysis of octahedral configurations in perovskite quantum dots (QDs)
remains elusive due to the lack of robust analytical standards. Here,
we introduce a machine vision-enabled approach integrating self-supervised
denoising (S2SRED) for noise-sensitive datasets, atomic species classification,
and automated reconstruction of the PbX6 octahedral network
with precise lattice parameter extraction, enabling high-fidelity
processing of low-dose scanning transmission electron microscopy (STEM)
images. In CsPbI3 QDs, we observe reduced PbX6 octahedral tilting in the outer unit cells, forming an isotropic
core–shell feature. In contrast, mixed-halide CsPbI3–x
Br
x
(x = 0.5) QDs show inhomogeneous and anisotropic PbX6 octahedral
tilting distributions resulting from dopant segregation and impaired
phase stability as corroborated by photoluminescence measurements.
By standardizing metrics for octahedral and lattice geometries, this
method helps establish atomic-scale structure–property links
in perovskite nanomaterials.