Understanding the resolution and sensitivity in photothermal nanoscale chemical imaging - a point spread function approach

17 January 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Atomic force microscopy-infrared spectroscopy (AFM-IR) is a photothermal scanning probe technique that combines nanoscale spatial resolution with the chemical analysis capability of mid-infrared spectroscopy. Using this hybrid technique, chemical identification down to the single molecule level has been demonstrated. However, the mechanism at the heart of AFM-IR, the transduction of local photothermal heating to cantilever deflection, is still not fully understood. Existing physical models only describe this process in few special cases but not in many of the types of sample geometries encountered in the practical use of AFM-IR. Here, we introduce an analytical expression for modeling the temperature and photothermal expansion process, verified with finite element simulations and validated with AFM-IR experiments. This method describes AFM-IR signal amplitudes in vertically and laterally heterogeneous samples and allows us to study the effect of the position and size of the absorber as well as laser repetition rate and pulse width on AFM-IR signal amplitudes and spatial resolution. Theses results will help experimentalists to select optimal AFM-IR settings and to achieve high signal intensity and resolution in AFM-IR experiments. The results also point towards the importance of interfacial thermal resistance and its contribution to AFM-IR imaging contrast. Understanding the significance and role of this so far hardly considered parameter will help to better understand the working principles of advanced AFM-IR modes such as tapping AFM-IR or surface sensitive AFM-IR.

Keywords

Atomic force microscopy-infrared
chemical imaging
photothermal expansion

Supplementary materials

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Supplementary Informarion
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A PDF file including of additional figures S1 to S12, table S1 and the additional derivations for equations in the main text.
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