David McDonagh

The paper introduces an automated data processing workflow for 3DED datasets using AutoED, converting data to NeXus format and reducing workload for electron diffraction scientists.

The paper uses Monte Carlo simulations to model neutron protein crystallography experiments for the NMX instrument at ESS, improving event formation and analyzing scattering effects.

This study uses machine learning to predict protein crystal solvent content from Patterson maps, achieving over 50% error reduction compared to existing methods.

Laue-DIALS is an open-source software pipeline for analyzing polychromatic X-ray diffraction data, enabling efficient processing and integration of diffraction intensities with wavelength correction.