STEM image simulation with hybrid CPU/GPU programming

Atomic-level imaging of beam-sensitive COFs and MOFs by low-dose electron microscopy

Electron microscopy, an important technique that allows for the precise determination of structural information with high spatiotemporal resolution, has become indispensable in unravelling the complex relationships between material structure and properties ranging from mesoscale morphology to atomic arrangement. However, beam-sensitive materials, particularly those comprising organic components such as metal-organic frameworks (MOFs) and covalent organic frameworks (COFs), would suffer catastrophic damage from the high energy electrons, hindering the determination of atomic structures. A low-dose approach has arisen as a possible solution to this problem based on the integration of advancements in several aspects: electron optical system, detector, image processing, and specimen preservation. This article summarizes the transmission electron microscopy characterization of MOFs and COFs, including local structures, host-guest interactions, and interfaces at the atomic level. Revolutions in advanced direct electron detectors, algorithms in image acquisition and processing, and emerging methodology for high quality low-dose imaging are also reviewed. Finally, perspectives on the future development of electron microscopy methodology with the support of computer science are presented.

Computationally Efficient Handling of Partially Coherent Electron Sources in (S)TEM Image Simulations via Matrix Diagonalization

We introduce a novel method to improve the computational efficiency for (S)TEM image simulation by employing matrix diagonalization of the mixed envelope function (MEF). The MEF is derived by taking the finite size and the energy spread of the effective electron source into account, and is a component of the transmission cross-coefficient that accounts for the correlation between partially coherent waves. Since the MEF is a four-dimensional array and its application in image calculations is time-consuming, we reduce the computation time by using its eigenvectors. By incorporating the aperture function into the matrix diagonalization, only a small number of eigenvectors are required to approximate the original matrix with high accuracy. The diagonalization enables for each eigenvector the calculation of the corresponding image by employing the coherent model. The individual images are weighted by the corresponding eigenvalues and then summed up, resulting in the total partially coherent image.

ToTEM: A software for fast TEM image simulation

ToTEM, a multislice based image simulation software is developed for transmission electron microscope (TEM). This software implements the following major features: i) capability of assigning three-dimensional potentials of atom into multiple slices and precise introduction of phase shift caused by the sub-pixel atomic position, ii) employing CUDA coding and graphical processing units (GPU) with multi-threading parallel algorithm based on the powerful batch (inverse) fast Fourier transform (FFT), which is especially beneficial for image simulation of scanning transmission electron microscopy (STEM) or (integrated) differential phase contrast (i)DPC, iii) design for efficiently generating large batch of dataset of high resolution transmission electron microscopy (HRTEM) images. Image simulation acceleration for STEM has been verified by simulating a large-scale SrTiO₃ . Additionally, iDPC image of MFI-type zeolites with xylene molecules encapsulated in straight channels demonstrates the advantage of iDPC in detecting light molecules. This article is protected by copyright. All rights reserved.

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. Here, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditional multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.