DataVXACS Applied Materials & InterfacesPaper
journal article·2022-10-19

Machine Learning-Aided Design of Gold Core–Shell Nanocatalysts toward Enhanced and Selective Photooxygenation

Mohsen Tamtaji, Xuyun Guo, Abhishek Tyagi, Patrick Ryan Galligan, Zhenjing Liu, Alexander Roxas, Hongwei Liu, Yuting Cai, Hoilun Wong, Lun Zeng, Jianbo Xie, Yucong Du, Zhigang Hu, Dong Lu, William A. Goddard, Ye Zhu, Zhengtang Luo

ACS Applied Materials & Interfaces· Volume 14· Issue 41
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Source abstract

Abstract

We demonstrate the use of the machine learning (ML) tools to rapidly and accurately predict the electric field as a guide for designing core–shell Au–silica nanoparticles to enhance 1O2 sensitization and selectivity of organic synthesis. Based on the feature importance analysis, obtained from a deep neural network algorithm, we found a general and linear dependent descriptor (θ ∝ aD0.25t–1, where a, D, and t are the shape constant, size of metal nanoparticles, and distance from the metal surface) for the electric field around the core–shell plasmonic nanoparticle. Directed by the new descriptor, we synthesized gold-silica nanoparticles and validated their plasmonic intensity using scanning transmission electron microscopy-electron energy loss spectroscopy (STEM-EELS) mapping. The nanoparticles with θ = 0.40 demonstrate an ∼3-fold increase in the reaction rate of photooxygenation of anthracene and 4% increase in the selectivity of photooxygenation of dihydroartemisinic acid (DHAA), a long-standing goal in organic synthesis. In addition, the combination of ML and experimental investigations shows the synergetic effect of plasmonic enhancement and fluorescence quenching, leading to enhancement for 1O2 generation. Our results from time-dependent density functional theory (TD-DFT) calculations suggest that the presence of an electric field can favor intersystem crossing (ISC) of methylene blue to enhance 1O2 generation. The strategy reported here provides a data-driven catalyst preparation method that can significantly reduce experimental cost while paving the way for designing photocatalysts for organic drug synthesis.
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Research context

NanomaterialsCatalysis & surfaces

OpenAlex topics: Gold and Silver Nanoparticles Synthesis and Applications · Advanced Nanomaterials in Catalysis · Advanced Photocatalysis Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemical and Biological Engineering, Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, William Mong Institute of Nano Science and Technology, and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong999077, P. R. China

Department of Applied Physics, Research Institute for Smart Energy, The Hong Kong Polytechnic University, Hong Kong, China

Guangzhou Baiyun Medical Adhesive Co. Ltd., Guangzhou, Guangdong510405, P. R. China

Silver Age Engineering Plastics (Dongguan) Co. Ltd., Dongguan, Guangdong523187, P. R. China

Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, Guangdong511458, P. R. China

Materials and Process Simulation Center (MSC), MC 139-74, California Institute of Technology, Pasadena, California91125, United States

Funding

Guangdong Science and Technology Department · Research Grants Council, University Grants Committee · National Natural Science Foundation of China · Hong Kong Polytechnic University · ?International science and technology cooperation projects? of Science and Technological Bureau of Guangzhou Huangpu District · IER foundation · Shenzhen Special Fund for Central Guiding the Local Science and Technology Development · Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology

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