Related papers: Autonomous Polycrystalline Material Decomposition …
We present a geometry-aware method for heterogeneous single-particle cryogenic electron microscopy (cryo-EM) reconstruction that predicts atomic backbone conformations. To incorporate protein-structure priors, we represent the backbone as a…
Due to the energy-dependent nature of the attenuation coefficient and the polychromaticity of the X-ray source, beam hardening effect occurs when X-ray photons penetrate through an object, causing a nonlinear projection data. When a linear…
Recent advances in scanning transmission electron and scanning tunneling microscopies allow researchers to measure materials structural and electronic properties, such as atomic displacements and charge density modulations, at an Angstrom…
In the study of condensed matter physics, spectral information plays an important role for understand the mechanism of materials. However, it is difficult to obtain the spectrum directly through experiments or simulation. For example, the…
Materials with tailored quantum properties can be engineered from atomic scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here we…
Dual energy computerized tomography has gained great interest because of its ability to characterize the chemical composition of a material rather than simply providing relative attenuation images as in conventional tomography. The purpose…
Optoelectronic devices based on graphene and other two-dimensional (2D) materials, such as transition metal dichalcogenides (TMDs) are the focus of wide research interest. The characterization these emerging atomically thin materials and…
We introduce a new method, rooted in estimation theory, to detect individual atoms in site-resolved images of microtrap arrays, such as optical lattices or optical tweezers arrays. Using labelled test images, we demonstrate drastic…
Supervised machine learning algorithms, such as graph neural networks (GNN), have successfully predicted material properties. However, the superior performance of GNN usually relies on end-to-end learning on large material datasets, which…
With the flourishing development of nanophotonics, Cherenkov radiation pattern can be designed to achieve superior performance in particle detection by fine-tuning the properties of metamaterials such as photonic crystals (PCs) surrounding…
Atomically thin polycrystalline transition-metal dichalcogenides (TMDs) are relevant to both fundamental science investigation and applications. TMD thin-films present uniquely difficult challenges to effective nanoscale crystalline…
Machine learning techniques have recently gained prominence in physics, yielding a host of new results and insights. One key concept is that of backpropagation, which computes the exact gradient of any output of a program with respect to…
Based on experimental and simulation methods we helped develop, we are advancing mechanistic understanding of how self-assembled NC metamaterials can produce distinctive near- and far-field optical properties not readily achievable in…
Raman spectroscopy is frequently used to identify composition, structure and layer thickness of 2D materials. Here, we describe an efficient first-principles workflow for calculating resonant first-order Raman spectra of solids within…
Ferromagnetic resonance (FMR) spectroscopy is a powerful method for quantifying internal magnetic anisotropy fields in nanoparticles, which is important in a wide range of biomedical and storage applications. The interpretation of FMR…
Determining atomic structure from spectroscopic data is central to materials science but remains restricted to a limited set of techniques and material classes, largely due to the computational cost and complexity of structural refinement.…
Scientific researchers frequently use the in situ synchrotron high-energy powder X-ray diffraction (XRD) technique to examine the crystallographic structures of materials in functional devices such as rechargeable battery materials. We…
Dual-energy computed tomography (DECT) enables material-specific imaging through acquisitions at two different X-ray energy spectra. Material decomposition from DECT data is an ill-posed inverse problem that is highly sensitive to noise…
Nowadays, modern electron microscopes deliver images at atomic scale. The precise atomic structure encodes information about material properties. Thus, an important ingredient in the image analysis is to locate the centers of the atoms…
Curvilinear structures frequently appear in microscopy imaging as the object of interest. Crystallographic defects, i.e., dislocations, are one of the curvilinear structures that have been repeatedly investigated under transmission electron…