Ghostbuster: A phase retrieval diffraction tomography algorithm for cryo-EM.

Ewald sphere curvature correction, which extends beyond the projection approximation, stretches the shallow depth of field in cryo-EM reconstructions of thick particles. Here we show that even for previously assumed thin particles, reconstruction artifacts which we refer to as ghosts can appear. By retrieving the lost phases of the electron exitwaves and accounting for the first Born approximation scattering within the particle, we show that these ghosts can be effectively eliminated. Our simulations demonstrate how such ghostbusting can improve reconstructions as compared to existing state-of-the-art software. Like ptychographic cryo-EM, our Ghostbuster algorithm uses phase retrieval to improve reconstructions, but unlike the former, we do not need to modify the existing data acquisition pipelines.

Engineering a Hierarchy of Disorder: A New Route to Synthesize High-Performance 3D Nanoporous All-Carbon Materials*.

A new nanoporous amorphous carbon (NAC) structure that achieves both ultrahigh strength and high electrical conductivity, which are usually incompatible in porous materials is reported. By using modified spark plasma sintering, three amorphous carbon phases with different atomic bonding configurations are created. The composite consisted of an amorphous sp2-carbon matrix mixed with amorphous sp3-carbon and amorphous graphitic motif. NAC structure has an isotropic electrical conductivity of up to 12 000 S m-1, Young's modulus of up to ≈5 GPa, and Vickers hardness of over 900 MPa. These properties are superior to those of existing conductive nanoporous materials. Direct investigation of the multiscale structure of this material through transmission electron microscopy, electron energy loss spectroscopy, and machine learning-based electron tomography revealed that the origin of the remarkable material properties is the well-organized sp2/sp3 amorphous carbon phases with a core-shell-like architecture, where the sp3-rich carbon forms a resilient core surrounded by a conductive sp2-rich layer. This research not only introduces novel materials with exceptional properties but also opens new opportunities for exploring amorphous structures and designing high-performance materials.

Preventing the Capillary-Induced Collapse of Vertical Nanostructures.

Robust processes to fabricate densely packed high-aspect-ratio (HAR) vertical semiconductor nanostructures are important for applications in microelectronics, energy storage and conversion. One of the main challenges in manufacturing these nanostructures is pattern collapse, which is the damage induced by capillary forces from numerous solution-based processes used during their fabrication. Here, using an array of vertical silicon (Si) nanopillars as test structures, we demonstrate that pattern collapse can be greatly reduced by a solution-phase deposition method to coat the nanopillars with self-assembled monolayers (SAMs). As the main cause for pattern collapse is strong adhesion between the nanopillars, we systematically evaluated SAMs with different surface energy components and identified H-bonding between the surfaces to have the largest contribution to the adhesion. The advantage of the solution-phase deposition method is that it can be implemented before any drying step, which causes patterns to collapse. Moreover, after drying, these SAMs can be easily removed using a gentle air-plasma treatment right before the next fabrication step, leaving a clean nanopillar surface behind. Therefore, our approach provides a facile and effective method to prevent the drying-induced pattern collapse in micro- and nanofabrication processes.

A data reduction and compression description for high throughput time-resolved electron microscopy.

Fast, direct electron detectors have significantly improved the spatio-temporal resolution of electron microscopy movies. Preserving both spatial and temporal resolution in extended observations, however, requires storing prohibitively large amounts of data. Here, we describe an efficient and flexible data reduction and compression scheme (ReCoDe) that retains both spatial and temporal resolution by preserving individual electron events. Running ReCoDe on a workstation we demonstrate on-the-fly reduction and compression of raw data streaming off a detector at 3 GB/s, for hours of uninterrupted data collection. The output was 100-fold smaller than the raw data and saved directly onto network-attached storage drives over a 10 GbE connection. We discuss calibration techniques that support electron detection and counting (e.g., estimate electron backscattering rates, false positive rates, and data compressibility), and novel data analysis methods enabled by ReCoDe (e.g., recalibration of data post acquisition, and accurate estimation of coincidence loss).