Incorporating plasmonic featurization with machine learning to achieve accurate and bidirectional prediction of nanoparticle size and size distribution

• Main Authors: Tan, Emily Xi, Chen, Yichao, Lee, Yih Hong, Leong, Yong Xiang, Leong, Shi Xuan, Stanley, Chelsea Violita, Pun, Chi Seng, Ling, Xing Yi
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Chemistry; Nanoparticle Sizes; Plasmonics
• Online Access: https://hdl.handle.net/10356/162377
• Institution: Nanyang Technological University

Determination of nanoparticle size and size distribution is important because these key parameters dictate nanomaterials' properties and applications. Yet, it is only accomplishable using low-throughput electron microscopy. Herein, we incorporate plasmonic-domain-driven feature engineering with...