Investigating Chiral Morphogenesis of Gold Using Generative Cellular Automata

Overview

Journal Nat Mater

Date 2024 May 1

PMID 38693448

Authors

Sang Won Im

Dongsu Zhang

Jeong Hyun Han

Ryeong Myeong Kim

Changwoon Choi

Young Min Kim

Ki Tae Nam

Affiliations

Soon will be listed here.

Abstract

Homochirality is an important feature in biological systems and occurs even in inorganic nanoparticles. However, the mechanism of chirality formation and the key steps during growth are not fully understood. Here we identify two distinguishable pathways from achiral to chiral morphologies in gold nanoparticles by training an artificial neural network of cellular automata according to experimental results. We find that the chirality is initially determined by the nature of the asymmetric growth along the boundaries of enantiomeric high-index planes. The deep learning-based interpretation of chiral morphogenesis provides a theoretical understanding but also allows us to predict an unprecedented crossover pathway and the resulting morphology.

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