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Infrared Near-Field Microscopy as a Platform for Nanoscale Biomedical Spectroscopy and Imaging.

Hongcai Deng^1,2, Xin Zhao^3,4, Xinyue Na^1,2

¹National Engineering Research Center of Electromagnetic Radiation Control Materials University of Electronic Science and Technology of China, Chengdu 611731, China.

ACS Applied Materials & Interfaces

|May 15, 2026

Summary

Scanning near-field optical microscopy (SNOM) provides nanoscale chemical imaging for precision medicine. This review covers SNOM advancements and challenges for clinical translation in nanobiology.

Keywords:

biomedical spectroscopy clinical translation infrared SNOM label-free molecular fingerprinting nanoscale vibrational spectroscopy

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Area of Science:

Nanotechnology
Spectroscopy
Biophysics

Background:

Precision medicine demands nanoscale tools for early disease detection.
Conventional optical microscopy is limited by diffraction, hindering nanoscale analysis.
Scanning Near-field Optical Microscopy (SNOM) offers a solution by combining chemical and spatial resolution.

Purpose of the Study:

To systematically review the evolution of SNOM techniques.
To summarize recent advancements in SNOM systems and applications.
To analyze challenges and future potential for clinical translation.

Main Methods:

Review of SNOM development from imaging to spectroscopic platforms (nano-FTIR, AFM-IR).
Summary of advances in ultrafast, liquid-phase, terahertz, and miniaturized SNOM.
Analysis of SNOM applications in biological samples (proteins, nucleic acids, viruses, etc.).

Main Results:

SNOM enables in situ chemical characterization beyond the diffraction limit.
Recent SNOM systems offer enhanced speed, liquid-phase analysis, and miniaturization.
SNOM successfully resolves molecular heterogeneity and interactions in biological systems.

Conclusions:

SNOM is a powerful tool for nanobiological imaging and molecular diagnostics.
Addressing challenges in sample prep, speed, and standardization is crucial for clinical translation.
Future applications in AI-assisted analysis, portability, and neuroscience show significant promise.