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Nanomaterials play a crucial role in the biomedical field, and with the rise of the digital era, artificial intelligence (AI) has become a valuable tool in all stages of nanomaterial development, spanning from design to synthesis and characterization. In this review, we explore recent advancements in the field of AI-driven nanomaterials. Firstly, we delve into how AI can be leveraged in material design, utilizing vast databases to develop new materials. Secondly, we discuss intelligent synthesis, where AI algorithms are employed to optimize the synthesis process. Subsequently, we explore how to efficiently extract depth information from nanomaterial characterization results using AI-based methods. Lastly, we offer a glimpse into the future of biomedical nanomaterials, highlighting the potential impact of AI in this rapidly evolving field.

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Application of Artificial Intelligence in the Exploration and Optimization of Biomedical Nanomaterials

Show Author's information Xiaoyang Zhu1Yan Li1( )Ning Gu2( )
State Key Laboratory of Digital Medical Engineering, Jiangsu Key Laboratory for Biomaterials and Devices, Southeast University, Nanjing 210009, China
Medical School, Nanjing University, Nanjing 210093, China


Nanomaterials play a crucial role in the biomedical field, and with the rise of the digital era, artificial intelligence (AI) has become a valuable tool in all stages of nanomaterial development, spanning from design to synthesis and characterization. In this review, we explore recent advancements in the field of AI-driven nanomaterials. Firstly, we delve into how AI can be leveraged in material design, utilizing vast databases to develop new materials. Secondly, we discuss intelligent synthesis, where AI algorithms are employed to optimize the synthesis process. Subsequently, we explore how to efficiently extract depth information from nanomaterial characterization results using AI-based methods. Lastly, we offer a glimpse into the future of biomedical nanomaterials, highlighting the potential impact of AI in this rapidly evolving field.

Keywords: machine learning, artificial intelligence (AI), high-throughput, biomedical nanomaterials, nanomaterials design



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Publication history

Received: 30 July 2023
Revised: 24 August 2023
Accepted: 28 August 2023
Published: 12 October 2023
Issue date: September 2023


© The Author(s) 2023.



This work was financially funded by the National Natural Science Foundation of China (51832001, 61821002), the Natural Science Foundation of Jiangsu Province (BK20222002) and the Nanjing Science and Technology Development Foundation (202205066).

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