Atomic force microscopy-infrared spectroscopy (AFM-IR) is a technique that combines the nanoscale spatial resolution of AFM with the chemical specificity of IR spectroscopy. However, conventional AFM-IR methods suffer from low signal-to-noise ratio (SNR), nonchemical artifacts, and inaccurate spectra. A recent advance, null-deflection AFM-IR (NDIR), overcomes these limitations and enables high-fidelity nanoscale chemical imaging of biological samples.
Small molecule imaging plays a crucial role in comprehending biological structures, functions, and disease mechanisms. In this presentation, we will show the effectiveness of this imaging technique through the exploration of different biological samples, such as the intricate visualizations of cellular ultrastructure in thin sections of breast cancer cells. Challenges posed by the extension of this technique to different types of samples and ongoing efforts to make instrumental enhancements will be discussed as well.
Infrared spectroscopic imaging combines the ability to record molecular content with the ability to visualize chemistry in its spatial diversity. Given the need to record a significantly larger quantity of data than a typical microscopy image (MB vs. GB) and the extensive bandwidth of the spectra (~10 m), trade-offs often have to be made between the closely related considerations of signal to noise ratio, spatial-spectral coverage, resolution and optical arrangements. Here, we present a path from rigorous theory to modeling and design to realizing the advantages offered by new ideas on fundamentally changing these trade-offs. We first describe a new microscope design for increased speed and rapid coverage that is useful for biomedical and clinical tissue imaging. Next, we describe a configuration to measure chirality in samples that promises higher spectral information that present methods. Finally, we present a new approach to nanoscale IR imaging that provides greater fidelity and speed at unprecedented levels of signal to noise ratio. Finally, we show how emerging machine learning approaches can further augment these advances. For each instrumentation advance, examples of use cases will be presented.
Atomic Force Microscopy – Infrared spectroscopy (AFM-IR) is a powerful technique for mapping material composition at sub micrometer length scales. Unlike related technologies such as scanning near-field optical microscopy (SNOM), the detected signal can be equally sensitive to both chemical and mechanical sample properties due to variations in the cantilever’s response (or responsivity) to a sample perturbation local to the tip. Understanding cantilever responsivity has led to new approaches for correcting this effect, which show improved chemical specificity and imaging fidelity for heterogeneous samples. Here, we present implications of correcting the cantilever responsivity effect in AFM-IR images for studying biological samples at nanometer length scales and discuss the future of this emerging technology.
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