Machine learning guided microwave-assisted quantum dot synthesis and an indication of residual H 2 O 2 in human teeth
Machine learning guided microwave-assisted quantum dot synthesis and an indication of residual H 2 O 2 in human teeth
复制标题
机器学习引导微波辅助量子点合成以及人类牙齿中残留 H 2 O 2 的指示
DOI：
10.1039/d2nr03718a
复制
发表时间：
2022
期刊：
影响因子：
6.7
通讯作者：
Wang, Juncheng
中科院分区：
文献类型：
--
作者：
Xu, Quan;Tang, Yaoyao;Zhu, Peide;Zhang, Weiye;Zhang, Yuqi;Solis, Oliver Sanchez;Hu, Travis Shihao;Wang, Juncheng
目前碳量子点的制备方法涉及的反应参数较多，导致合成过程的可能性较大，产物性能的不确定性较高。最近，机器学习（ML）方法在许多应用中将选定的特征关联起来方面表现出了巨大的潜力，这可以帮助理解CD的相关结构-功能关系，并发现更好的合成配方。在这项工作中，我们采用ML方法来指导微波系统中的蓝色CD合成。优化合成参数和条件后，量子产率（QY）比没有ML指导的制备样品的平均值提高了约200%。将所得的CD作为荧光探针应用于监测人牙齿中的过氧化氢（H2 O2）。该探针在0 ~ 1.1M范围内与H2 O2浓度呈良好的线性关系，检测下限为0.12M，可有效地检测牙齿漂白后残留的H2 O2。这项工作表明，所采用的ML方法在指导高质量CD的合成方面具有相当大的优势，这可以加速能源，生物医学和环境修复应用中其他新型功能材料的开发。
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 (H2O2) in human teeth. The CD probe exhibits a linear relationship with the concentration of H2O2 ranging from 0 to 1.1 M with a lower detection limit of 0.12 M, which can effectively detect the residual H2O2 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.