Biglarbeigi Pardis, Bhattacharya Gourav, Finlay Dewar, Payam Amir Farokh
Department of Pharmacology & Therapeutics, University of Liverpool, Whelan Building, Liverpool, England, L69 3GE, UK.
School of Engineering, Ulster University, York Street, Belfast, Northern Ireland, BT15 1AP, UK.
Adv Sci (Weinh). 2025 Mar;12(11):e2411556. doi: 10.1002/advs.202411556. Epub 2025 Jan 28.
Recent advancements in atomic force microscopy (AFM) have enabled detailed exploration of materials at the molecular and atomic levels. These developments, however, pose a challenge: the data generated by microscopic and spectroscopic experiments are increasing rapidly in both size and complexity. Extracting meaningful physical insights from these datasets is challenging, particularly for multilayer heterogeneous nanoscale structures. In this paper, an unsupervised approach is presented to enhance AFM image contrast by analyzing the nonlinear response of a cantilever interacting with a material's surface using a wavelet-based AFM. This method simultaneously measures different frequencies and harmonics in a single scan, without the need for additional hardware and exciting multiple cantilevers' eigenmodes. This developed AFM image contrast enhancement (AFM-ICE) approach employs unsupervised learning, image processing, and image fusion techniques. The method is applied to interpret complex multilayer structures consist of defects, deposited nanoparticles and heterogeneities. Its substantial capability is demonstrated to improve image contrast and differentiate between various components. This methodology can pave the way for rapid and precise determination of material properties with enhanced resolution.
原子力显微镜（AFM）的最新进展使得在分子和原子水平上对材料进行详细探索成为可能。然而，这些进展带来了一个挑战：微观和光谱实验产生的数据在规模和复杂性上都在迅速增加。从这些数据集中提取有意义的物理见解具有挑战性，特别是对于多层异质纳米级结构。在本文中，提出了一种无监督方法，通过使用基于小波的原子力显微镜分析悬臂与材料表面相互作用的非线性响应来增强原子力显微镜图像的对比度。该方法在单次扫描中同时测量不同频率和谐波，无需额外硬件且无需激发多个悬臂的本征模式。这种开发的原子力显微镜图像对比度增强（AFM-ICE）方法采用无监督学习、图像处理和图像融合技术。该方法被应用于解释由缺陷、沉积的纳米颗粒和不均匀性组成的复杂多层结构。其强大的能力被证明可以提高图像对比度并区分各种成分。这种方法可以为以更高分辨率快速精确地确定材料特性铺平道路。
