ABSTRACT

A novel method is developed to analyze the structural formation of colloidal particles based on image recognition via a convolutional neural network (CNN). This makes it possible to analyze various complex structures that are difficult to study using a traditional bond-order parameter analysis. Molecular dynamics simulations on soft colloidal systems are performed in quasi two-dimensional and three-dimensional systems, and the efficiency of the proposed method is demonstrated.

中文翻译：

---

一种通过图像识别分析软物质结构形成的机器学习方法

摘要

基于卷积神经网络（CNN）的图像识别，开发了一种新的方法来分析胶体颗粒的结构形成。这使得使用传统的键序参数分析来分析难以研究的各种复杂结构成为可能。在准二维和三维系统中对软胶体系统进行了分子动力学模拟，证明了该方法的有效性。