Micromolar chemical imaging by high-energy low-photodamage Coherent Anti-stokes Raman Scattering (HELP-CARS)

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Authors: Guangrui Ding, Dingcheng Sun, Yifan Zhu, Rong Tang, Hongli Ni, Yuhao Yuan, Haonan Lin, Ji‐Xin Cheng
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Abstract

Coherent anti-Stokes Raman scattering (CARS) microscopy offers label-free chemical imaging capabilities, but its performance is constrained by small Raman scattering cross-section, strong non-resonant background (NRB), and limited signal-to-noise ratio (SNR). Here, we introduce a high-energy, low-photodamage CARS (HELP-CARS) platform designed to overcome these physical limitations. By employing a 1-MHz non-collinear optical parametric amplifier (NOPA) with extensive pulse chirping, HELP-CARS increases the coherent Raman excitation efficiency by ~300 times and improves the signal-to-nonresonant background ratio by 11 times, while inducing negligible damage during live cell imaging. Furthermore, to remove non-independent noise and physically entangled non-resonant background, we incorporate self-supervised deep-learning denoising and background removal based on the Kramers-Kronig relationship, yielding sensitivity improvement by an additional order of magnitude. Together, these advances provide a micromolar imaging sensitivity (160 uM for Dimethyl sulfoxide-d6) corresponding to 1000 molecules in the focal volume. Such high sensitivity enables high-fidelity chemical imaging in both fingerprint and silent windows. Hyperspectral HELP-CARS imaging of deuterated fatty acids allowed first observation of chemical separation with single lipid droplet. Together, HELP-CARS offers a powerful and generalizable approach for ultrasensitive and quantitative vibrational imaging of biological systems.

Fields of Study & Subjects

Spectroscopy Techniques in Biomedical and Chemical Research Advanced Fluorescence Microscopy Techniques Spectroscopy and Quantum Chemical Studies

Publication details

Journal / source
arXiv (Cornell University)
Publication date
9 February 2026
Language
EN
Document type
Preprint