Machine learning guided microwave-assisted quantum dot synthesis and an indication of residual H2O2 in human teeth. Issue 37 (14th September 2022)

• Record Type: Journal Article
• Authors: Xu, Quan; Tang, Yaoyao; Zhu, Peide; Zhang, Weiye; Zhang, Yuqi; Solis, Oliver Sanchez; Hu, Travis Shihao; Wang, Juncheng
• Is Part Of: Nanoscale. Volume 14:Issue 37(2022)
• Page Start: 13771
• Page End: 13778
• Publication Date: 2022-09-14
• Subjects: Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/d2nr03718a
• Languages: English
• ISSNs: 2040-3364

Abstract

Abstract : Machine learning approach was employed to guide the fabrication of blue carbon dots(CDs) with excellent result. The quantum yield of the CDs can increase up to 200% and can be used as fluorescent probes for bleaching teeth H2 O2 detection. Abstract : The current preparation methods of carbon quantum dots (CDs) involve many reaction parameters, which leads to many possibilities in the synthesis processes and high uncertainty of the resultant production performance. Recently, machine learning (ML) methods have shown great potential in correlating the selected features in many applications, which can help understand the relevant structure–function relationships of CDs and discover better synthesis recipes as well. In this work, we employ the ML approach to guide the blue CD synthesis in microwave systems. After optimizing the synthesis parameters and conditions, the quantum yield (QY) increases to about 200% higher than the average value of the prepared samples without ML guidance. The obtained CDs are applied as fluorescent probes to monitor hydrogen peroxide (H2 O2 ) in human teeth. The CD probe exhibits a linear relationship with the concentration of H2 O2 ranging from 0 to 1.1 M with a lower detection limit of 0.12 M, which can effectively detect the residual H2 O2 after bleaching teeth. This work shows that the adopted ML methods have considerable advantages in guiding the synthesis of high-quality CDs, which could accelerate the development of other novel functional materials in energy, biomedical, and environmental remediation applications.