Related papers: Probing electron beam induced transformations on a…
Transmission electron microscopy at very low energy is a promising way to avoid damaging delicate biological samples with the incident electrons, a known problem in conventional transmission electron microscopy. For imaging in the 0-30 eV…
We demonstrate the feasibility of coincidence measurements in a conventional transmission electron microscope, revealing the temporal correlation between electron energy loss spectroscopy (EELS) and energy dispersive X-ray (EDX)…
We recast the Howie-Whelan equations for generating simulated transmission electron microscope (TEM) images, replacing the dependence on local atomic displacements with atomic positions only. This allows very rapid computation of simulated…
High-throughput analysis of multidimensional transmission electron microscopy (TEM) datasets remains a significant challenge, limiting the broader impact on strategic materials research. Conventional workflows typically involve sequential,…
Transmission electron microscopy (TEM) is a potent technique for the determination of three-dimensional atomic scale structure of samples in structural biology and materials science. In structural biology, three-dimensional structures of…
Beam damage is a major limitation in electron microscopy that becomes increasingly severe at higher resolution. One possible route to circumvent radiation damage, which forms the basis for single-particle electron microscopy and related…
The development of four-dimensional (4D) scanning transmission electron microscopy (STEM) using fast detectors has opened-up new avenues for addressing some of long-standing challenges in electron imaging. One of these challenges is how to…
Electrical impedance tomography (EIT) is highly affected by modeling errors regarding electrode positions and the shape of the imaging domain. In this work, we propose a new inclusion detection technique that is completely independent of…
Spatially resolved electron energy-loss spectroscopy (EELS) in a scanning transmission electron microscope (STEM) has been used to investigate as fluidic phase in nanoubbles embedded in a metallic Pd90Pt10 matrix. Using the 1s->2p…
Electron channeling contrast imaging (ECCI) is a scanning electron microscopy (SEM) based technique that enables bulk-sample characterization of crystallographic defects (e.g. dislocations, stacking faults, low angle boundaries). Despite…
Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. However, the classical approach of…
Accurately determining the crystallographic structure of a material, organic or inorganic, is a critical primary step in material development and analysis. The most common practices involve analysis of diffraction patterns produced in…
In this work, a data-driven modeling framework of switched dynamical systems under time-dependent switching is proposed. The learning technique utilized to model system dynamics is Extreme Learning Machine (ELM). First, a method is…
Live-cell imaging of multiple subcellular structures is essential for understanding subcellular dynamics. However, the conventional multi-color sequential fluorescence microscopy suffers from significant imaging delays and limited number of…
Recent advancements in high-resolution spectroscopy analyses within the scanning transmission electron microscope (STEM) have paved the way for measuring the concentration of chemical species in crystalline materials at the atomic scale.…
In the domain of battery research, the processing of high-resolution microscopy images is a challenging task, as it involves dealing with complex images and requires a prior understanding of the components involved. The utilization of deep…
Virtual beam diagnostics relies on computationally intensive beam dynamics simulations where high-dimensional charged particle beams evolve through the accelerator. We propose Latent Evolution Model (LEM), a hybrid machine learning…
Modern computational organic chemistry is becoming increasingly data-driven. There remain a large number of important unsolved problems in this area such as product prediction given reactants, drug discovery, and metric-optimized molecule…
The photon flux resulting from high-energy electron beam interactions with high field systems, such as in the upcoming FACET-II experiments at SLAC National Accelerator Laboratory, may give deep insight into the electron beam's underlying…
Automated analysis of electron microscopy datasets poses multiple challenges, such as limitation in the size of the training dataset, variation in data distribution induced by variation in sample quality and experiment conditions, etc. It…