# Orthogonally Dispersed Spectroscopic Single‐Molecule Localization Microscopy

## TL;DR

A new microscopy technique called ODsSMLM improves imaging by using all photons for both location and color information, avoiding previous trade-offs.

## Contribution

ODsSMLM introduces an orthogonal dispersion method that eliminates localization artifacts and uses all photons for both localization and spectroscopy.

## Key findings

- ODsSMLM achieves 10 nm localization precision and 1.1 nm spectral precision with 3000 photons.
- The method provides isotropic lateral resolution of 27 nm in dual-color imaging experiments.
- It eliminates dispersion-dependent localization artifacts by encoding positions via orthogonal spectral channels.

## Abstract

Spectroscopic single‐molecule localization microscopy (sSMLM) simultaneously acquires both spatial and spectral information from fluorescent molecules, facilitating molecular characterization analysis and multicolor imaging. However, this technique poses a fundamental dilemma: a finite photon budget must be split between localization and spectroscopy, limiting the performance of both. To alleviate this trade‐off, we propose orthogonally dispersed sSMLM (ODsSMLM). By modulating single‐molecule emission spectra through an orthogonal structure, ODsSMLM allows all photons to be used for both localization and spectral characterization. Crucially, this approach provides isotropic lateral localization precision, effectively removing the inherent dispersion‐dependent localization artifacts of other methods. Using simulated data, we demonstrate that under a 3000‐photon budget, ODsSMLM attains a localization precision of 10 nm and a spectral precision of 1.1 nm. Moreover, in dual‐color imaging experiments of microtubules and clathrin, ODsSMLM achieved isotropic lateral resolution of 27 nm.

Orthogonally dispersed spectroscopic single‐molecule localization microscopy (ODsSMLM) encodes molecular positions via two orthogonal spectral channels, enabling full photon utilization for simultaneous spatial localization and spectral analysis. By synthesizing location information from the non‐dispersive directions, it effectively eliminates the impact of spectral heterogeneity on localization.