Integration of an event-driven Timepix3 hybrid pixel detector into a cryo-EM workflow

Abstract The development of direct electron detectors has played a key role in low-dose electron microscopy imaging applications. Monolithic active-pixel sensor (MAPS) detectors are currently widely applied for cryogenic electron microscopy (cryo-EM); however, they have best performance at 300~kV, have relatively low read-out speed and only work in imaging mode. Hybrid pixel detectors (HPDs) can operate at any energy, have a higher DQE at lower voltage, have unprecedented high time resolution, and can operate in both imaging and diffraction modes. This could make them well-suited for novel low-dose life-science applications, such as cryo-ptychography, iDPC, and liquid cell imaging. Timepix3 is not frame-based, but truly event-based, and can record individual hits with 1.56~ns time resolution. Here, we present the integration of such a detector into a cryo-EM workflow and demonstrate that it can be used for automated data collection on biological specimens. The performance of the detector in terms of MTF and DQE has been investigated at 200~kV and we studied the effect of deterministic blur. We describe a single-particle analysis structure of \SI{3}{\angstrom} resolution and compare it with Falcon3 data collected under the same microscope. These studies could pave the way toward more efficient low-dose single-particle techniques. Data description Data has been split up in several different directories. In general: each directory contains individual READMEs Flat fields Collected on both TImepix3 and Falcon3 at 200 kV using a Tecnai Arctica microscope. These data have been used for calculating NPS, ToT correction and gain correction. Knife edge Collected on both TImepix3 and Falcon3 at 200 kV using a Tecnai Arctica microscope. These data have been used for calculating MTF. ToT correction calibration file This calibration file has been used to correct all raw Timepix3 data. Including micrographs deposited in EMPIAR. Gain correction Gain correction files calculated from flat field data for several different image formation methods of the Timepix3. The Python script for calculating the gain has been included. Software The software tpx3HitParser, tpx3EventViewer and the MTF-NPS-DQE scripts have listed as related identifiers to this entry.