# Recovering high-resolution information using energy filtering in MicroED

## TL;DR

Energy filtering in electron crystallography improves data quality by reducing noise and preserving high-resolution information.

## Contribution

The study demonstrates that energy filtering can recover high-resolution data from electron diffraction, even after radiation damage.

## Key findings

- Energy filtering reduces noise and sharpens Bragg peaks in electron diffraction data.
- High-resolution information is preserved and intensity statistics improve with energy filtering.
- Energy filtering enhances data quality and reliability in macromolecular electron crystallography.

## Abstract

Inelastic scattering poses a significant challenge in electron crystallography by elevating background noise and broadening Bragg peaks, thereby reducing the overall signal-to-noise ratio. This is particularly detrimental to data quality in structural biology, as the diffraction signal is relatively weak. These effects are aggravated even further by the decay of the diffracted intensities as a result of accumulated radiation damage, and rapidly fading high-resolution information can disappear beneath the noise. Loss of high-resolution reflections can partly be mitigated using energy filtering, which removes inelastically scattered electrons and improves data quality and resolution. Here, we systematically compared unfiltered and energy-filtered microcrystal electron diffraction data from proteinase K crystals, first collecting an unfiltered dataset followed directly by a second sweep using the same settings but with the energy filter inserted. Our results show that energy filtering consistently reduces noise, sharpens Bragg peaks, and extends high-resolution information, even though the absorbed dose was doubled for the second pass. Importantly, our results demonstrate that high-resolution information can be recovered by inserting the energy filter slit. Energy-filtered datasets showed improved intensity statistics and better internal consistency, highlighting the effectiveness of energy filtering for improving data quality. These findings underscore its potential to overcome limitations in macromolecular electron crystallography, enabling higher-resolution structures with greater reliability.