Issue 9, 2024

Machine learning in nanozymes: from design to application

Abstract

Nanozymes, a distinctive class of nanomaterials endowed with enzyme-like activity and kinetics akin to enzyme-catalysed reactions, present several advantages over natural enzymes, including cost-effectiveness, heightened stability, and adjustable activity. However, the conventional trial-and-error methodology for developing novel nanozymes encounters growing challenges as research progresses. The advent of artificial intelligence (AI), particularly machine learning (ML), has ushered in innovative design approaches for researchers in this domain. This review delves into the burgeoning role of ML in nanozyme research, elucidating the advancements achieved through ML applications. The review explores successful instances of ML in nanozyme design and implementation, providing a comprehensive overview of the evolving landscape. A roadmap for ML-assisted nanozyme research is outlined, offering a universal guideline for research in this field. In the end, the review concludes with an analysis of challenges encountered and anticipates future directions for ML in nanozyme research. The synthesis of knowledge in this review aims to foster a cross-disciplinary study, propelling the revolutionary field forward.

Graphical abstract: Machine learning in nanozymes: from design to application

Article information

Article type
Review Article
Submitted
31 yan 2024
Accepted
06 mar 2024
First published
06 mar 2024

Biomater. Sci., 2024,12, 2229-2243

Machine learning in nanozymes: from design to application

Y. Gao, Z. Zhu, Z. Chen, M. Guo, Y. Zhang, L. Wang and Z. Zhu, Biomater. Sci., 2024, 12, 2229 DOI: 10.1039/D4BM00169A

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