Glaubitz Christina, Bazzoni Amélie, Ackermann-Hirschi Liliane, Baraldi Laura, Haeffner Moritz, Fortunatus Roman, Rothen-Rutishauser Barbara, Balog Sandor, Petri-Fink Alke
Adolphe Merkle Institute, University of Fribourg, Chemin des Verdiers 4, 1700 Fribourg, Switzerland.
Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 17/A, 43124 Parma, Italy.
J Phys Chem C Nanomater Interfaces. 2023 Dec 28;128(1):421-427. doi: 10.1021/acs.jpcc.3c05938. eCollection 2024 Jan 11.
Characterizing nanoparticles (NPs) is crucial in nanoscience due to the direct influence of their physiochemical properties on their behavior. Various experimental techniques exist to analyze the size and shape of NPs, each with advantages, limitations, proneness to uncertainty, and resource requirements. One of them is electron microscopy (EM), often considered the gold standard, which offers visualization of the primary particles. However, despite its advantages, EM can be expensive, less accessible, and difficult to apply during dynamic processes. Therefore, using EM for specific experimental conditions, such as observing dynamic processes or visualizing low-contrast particles, is challenging. This study showcases the potential of machine learning in deriving EM parameters by utilizing cost-effective and dynamic techniques such as dynamic light scattering (DLS) and UV-vis spectroscopy. Our developed model successfully predicts the size and shape parameters of gold NPs based on DLS and UV-vis results. Furthermore, we demonstrate the practicality of our model in situations in which conducting EM measurements presents a challenge: Tracking in situ the synthesis of 100 nm gold NPs.
在纳米科学中，表征纳米颗粒（NPs）至关重要，因为其物理化学性质会直接影响它们的行为。存在多种用于分析纳米颗粒大小和形状的实验技术，每种技术都有其优点、局限性、不确定性倾向和资源需求。其中之一是电子显微镜（EM），它常被视为金标准，可提供初级颗粒的可视化。然而，尽管电子显微镜有其优点，但它可能成本高昂、难以获取，并且在动态过程中难以应用。因此，在特定实验条件下使用电子显微镜，如观察动态过程或可视化低对比度颗粒，具有挑战性。本研究展示了机器学习在通过利用诸如动态光散射（DLS）和紫外可见光谱等经济高效且动态的技术来推导电子显微镜参数方面的潜力。我们开发的模型基于动态光散射和紫外可见光谱结果成功预测了金纳米颗粒的大小和形状参数。此外，我们证明了我们的模型在进行电子显微镜测量具有挑战性的情况下的实用性：原位跟踪100纳米金纳米颗粒的合成。
