Forchheimer Daniel, Forchheimer Robert, Haviland David B
Department of Applied Physics, Section for Nanostructure Physics, Royal Institute of Technology (KTH), SE-106 91 Stockholm, Sweden.
Division of Information Coding, Department of Electrical Engineering, Linköping University, SE- 581 83 Linköping, Sweden.
Nat Commun. 2015 Feb 10;6:6270. doi: 10.1038/ncomms7270.
Atomic force microscopy has recently been extented to bimodal operation, where increased image contrast is achieved through excitation and measurement of two cantilever eigenmodes. This enhanced material contrast is advantageous in analysis of complex heterogeneous materials with phase separation on the micro or nanometre scale. Here we show that much greater image contrast results from analysis of nonlinear response to the bimodal drive, at harmonics and mixing frequencies. The amplitude and phase of up to 17 frequencies are simultaneously measured in a single scan. Using a machine-learning algorithm we demonstrate almost threefold improvement in the ability to separate material components of a polymer blend when including this nonlinear response. Beyond the statistical analysis performed here, analysis of nonlinear response could be used to obtain quantitative material properties at high speeds and with enhanced resolution.
原子力显微镜最近已扩展到双峰操作,通过激发和测量两个悬臂本征模式来实现更高的图像对比度。这种增强的材料对比度在分析具有微米或纳米级相分离的复杂异质材料时具有优势。在这里,我们表明,在谐波和混合频率下分析对双峰驱动的非线性响应会产生更大的图像对比度。在单次扫描中同时测量多达17个频率的幅度和相位。使用机器学习算法,我们证明,当包含这种非线性响应时,分离聚合物共混物材料组分的能力提高了近三倍。除了这里进行的统计分析之外,非线性响应分析可用于高速且高分辨率地获得定量材料特性。