Online measurement method for dimensions of disk parts based on machine vision.

Online measurement of disk part dimensions by the standard industrial camera features low cost, high efficiency and good universality, but the impact of projection distortion and end face chamfer on measurement is needed to overcome. Present work presents a measurement method to resolve above issues based on machine vision. To improve the measurement accuracy, lower end face of a disk part is determined as calibration plane and the upper end face is measurement plane. To reduce the impact of projection distortion and chamfer on measurement, the measurement points are reconstructed on the measurement plane by re-projection. Then, the inner and outer diameters of disk parts are measured by circle geometric fitting, and the thickness is calculated by the measurement plane position. The experimental results show that the method can online measure disk part dimensions just by a single image, and accuracy meets the requirements of universal grade disk parts.

Real space iterative reconstruction for vector tomography (RESIRE-V).

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V .

Three-dimensional atomic structure and local chemical order of medium- and high-entropy nanoalloys.

Medium- and high-entropy alloys (M/HEAs) mix several principal elements with near-equiatomic composition and represent a model-shift strategy for designing previously unknown materials in metallurgy1-8, catalysis9-14 and other fields15-18. One of the core hypotheses of M/HEAs is lattice distortion5,19,20, which has been investigated by different numerical and experimental techniques21-26. However, determining the three-dimensional (3D) lattice distortion in M/HEAs remains a challenge. Moreover, the presumed random elemental mixing in M/HEAs has been questioned by X-ray and neutron studies27, atomistic simulations28-30, energy dispersive spectroscopy31,32 and electron diffraction33,34, which suggest the existence of local chemical order in M/HEAs. However, direct experimental observation of the 3D local chemical order has been difficult because energy dispersive spectroscopy integrates the composition of atomic columns along the zone axes7,32,34 and diffuse electron reflections may originate from planar defects instead of local chemical order35. Here we determine the 3D atomic positions of M/HEA nanoparticles using atomic electron tomography36 and quantitatively characterize the local lattice distortion, strain tensor, twin boundaries, dislocation cores and chemical short-range order (CSRO). We find that the high-entropy alloys have larger local lattice distortion and more heterogeneous strain than the medium-entropy alloys and that strain is correlated to CSRO. We also observe CSRO-mediated twinning in the medium-entropy alloys, that is, twinning occurs in energetically unfavoured CSRO regions but not in energetically favoured CSRO ones, which represents, to our knowledge, the first experimental observation of correlating local chemical order with structural defects in any material. We expect that this work will not only expand our fundamental understanding of this important class of materials but also provide the foundation for tailoring M/HEA properties through engineering lattice distortion and local chemical order.

In Situ and Emerging Transmission Electron Microscopy for Catalysis Research.

Catalysts are the primary facilitator in many dynamic processes. Therefore, a thorough understanding of these processes has vast implications for a myriad of energy systems. The scanning/transmission electron microscope (S/TEM) is a powerful tool not only for atomic-scale characterization but also in situ catalytic experimentation. Techniques such as liquid and gas phase electron microscopy allow the observation of catalysts in an environment conducive to catalytic reactions. Correlated algorithms can greatly improve microscopy data processing and expand multidimensional data handling. Furthermore, new techniques including 4D-STEM, atomic electron tomography, cryogenic electron microscopy, and monochromated electron energy loss spectroscopy (EELS) push the boundaries of our comprehension of catalyst behavior. In this review, we discuss the existing and emergent techniques for observing catalysts using S/TEM. Challenges and opportunities highlighted aim to inspire and accelerate the use of electron microscopy to further investigate the complex interplay of catalytic systems.

Revealing Variable Dependences in Hexagonal Boron Nitride Synthesis via Machine Learning.

Wafer-scale monolayer two-dimensional (2D) materials have been realized by epitaxial chemical vapor deposition (CVD) in recent years. To scale up the synthesis of 2D materials, a systematic analysis of how the growth dynamics depend on the growth parameters is essential to unravel its mechanisms. However, the studies of CVD-grown 2D materials mostly adopted the control variate method and considered each parameter as an independent variable, which is not comprehensive for 2D materials growth optimization. Herein, we synthesized a representative 2D material, monolayer hexagonal boron nitride (hBN), on single-crystalline Cu (111) by epitaxial chemical vapor deposition and varied the growth parameters to regulate the hBN domain sizes. Furthermore, we explored the correlation between two growth parameters and provided the growth windows for large flake sizes by the Gaussian process. This new analysis approach based on machine learning provides a more comprehensive understanding of the growth mechanism for 2D materials.

Hollow Ptychography: Toward Simultaneous 4D Scanning Transmission Electron Microscopy and Electron Energy Loss Spectroscopy.

With the recent development of high-acquisition-speed pixelated detectors, 4D scanning transmission electron microscopy (4D-STEM) is becoming routinely available in high-resolution electron microscopy. 4D-STEM acts as a "universal" method that provides local information on materials that is challenging to extract from bulk techniques. It extends conventional STEM imaging to include super-resolution techniques and to provide quantitative phase-based information, such as differential phase contrast, ptychography, or Bloch wave phase retrieval. However, an important missing factor is the chemical and bonding information provided by electron energy loss spectroscopy (EELS). 4D-STEM and EELS cannot currently be acquired simultaneously due to the overlapping geometry of the detectors. Here, the feasibility of modifying the detector geometry to overcome this challenge for bulk specimens is demonstrated, and the use of a partial or defective detector for ptycholgaphic structural imaging is explored. Results show that structural information beyond the diffraction-limit and chemical information from the material can be extracted together, resulting in simultaneous multi-modal measurements, adding the additional dimensions of spectral information to 4D datasets.

Accurate real space iterative reconstruction (RESIRE) algorithm for tomography.

Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at  https://zenodo.org/record/7273314 .

Deep-Learning Electron Diffractive Imaging.

We report the development of deep-learning coherent electron diffractive imaging at subangstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying the trained CNNs to recover the phase images from electron diffraction patterns of twisted hexagonal boron nitride, monolayer graphene, and a gold nanoparticle with comparable quality to those reconstructed by a conventional ptychographic algorithm. Fourier ring correlation between the CNN and ptychographic images indicates the achievement of a resolution in the range of 0.70 and 0.55 Å. We further develop CNNs to recover the probe function from the experimental data. The ability to replace iterative algorithms with CNNs and perform real-time atomic imaging from coherent diffraction patterns is expected to find applications in the physical and biological sciences.

Three-dimensional topological magnetic monopoles and their interactions in a ferromagnetic meta-lattice.

Topological magnetic monopoles (TMMs), also known as hedgehogs or Bloch points, are three-dimensional (3D) non-local spin textures that are robust to thermal and quantum fluctuations due to the topology protection1-4. Although TMMs have been observed in skyrmion lattices1,5, spinor Bose-Einstein condensates6,7, chiral magnets8, vortex rings2,9 and vortex cores10, it has been difficult to directly measure the 3D magnetization vector field of TMMs and probe their interactions at the nanoscale. Here we report the creation of 138 stable TMMs at the specific sites of a ferromagnetic meta-lattice at room temperature. We further develop soft X-ray vector ptycho-tomography to determine the magnetization vector and emergent magnetic field of the TMMs with a 3D spatial resolution of 10 nm. This spatial resolution is comparable to the magnetic exchange length of transition metals11, enabling us to probe monopole-monopole interactions. We find that the TMM and anti-TMM pairs are separated by 18.3 ± 1.6 nm, while the TMM and TMM, and anti-TMM and anti-TMM pairs are stabilized at comparatively longer distances of 36.1 ± 2.4 nm and 43.1 ± 2.0 nm, respectively. We also observe virtual TMMs created by magnetic voids in the meta-lattice. This work demonstrates that ferromagnetic meta-lattices could be used as a platform to create and investigate the interactions and dynamics of TMMs. Furthermore, we expect that soft X-ray vector ptycho-tomography can be broadly applied to quantitatively image 3D vector fields in magnetic and anisotropic materials at the nanoscale.

High-entropy nanoparticles: Synthesis-structure-property relationships and data-driven discovery.

High-entropy nanoparticles have become a rapidly growing area of research in recent years. Because of their multielemental compositions and unique high-entropy mixing states (i.e., solid-solution) that can lead to tunable activity and enhanced stability, these nanoparticles have received notable attention for catalyst design and exploration. However, this strong potential is also accompanied by grand challenges originating from their vast compositional space and complex atomic structure, which hinder comprehensive exploration and fundamental understanding. Through a multidisciplinary view of synthesis, characterization, catalytic applications, high-throughput screening, and data-driven materials discovery, this review is dedicated to discussing the important progress of high-entropy nanoparticles and unveiling the critical needs for their future development for catalysis, energy, and sustainability applications.

Three-dimensional atomic packing in amorphous solids with liquid-like structure.

Liquids and solids are two fundamental states of matter. However, our understanding of their three-dimensional atomic structure is mostly based on physical models. Here we use atomic electron tomography to experimentally determine the three-dimensional atomic positions of monatomic amorphous solids, namely a Ta thin film and two Pd nanoparticles. We observe that pentagonal bipyramids are the most abundant atomic motifs in these amorphous materials. Instead of forming icosahedra, the majority of pentagonal bipyramids arrange into pentagonal bipyramid networks with medium-range order. Molecular dynamics simulations further reveal that pentagonal bipyramid networks are prevalent in monatomic metallic liquids, which rapidly grow in size and form more icosahedra during the quench from the liquid to the glass state. These results expand our understanding of the atomic structures of amorphous solids and will encourage future studies on amorphous-crystalline phase and glass transitions in non-crystalline materials with three-dimensional atomic resolution.

Revealing the Brønsted-Evans-Polanyi relation in halide-activated fast MoS2 growth toward millimeter-sized 2D crystals.

Achieving large-size two-dimensional (2D) crystals is key to fully exploiting their remarkable functionalities and application potentials. Chemical vapor deposition growth of 2D semiconductors such as monolayer MoS2 has been reported to be activated by halide salts, for which various investigations have been conducted to understand the underlying mechanism from different aspects. Here, we provide experimental evidence showing that the MoS2 growth dynamics are halogen dependent through the Brønsted-Evans-Polanyi relation, based on which we build a growth model by considering MoS2 edge passivation by halogens, and theoretically reproduce the trend of our experimental observations. These mechanistic understandings enable us to further optimize the fast growth of MoS2 and reach record-large domain sizes that should facilitate practical applications.

Capturing 3D atomic defects and phonon localization at the 2D heterostructure interface.

The three-dimensional (3D) local atomic structures and crystal defects at the interfaces of heterostructures control their electronic, magnetic, optical, catalytic, and topological quantum properties but have thus far eluded any direct experimental determination. Here, we use atomic electron tomography to determine the 3D local atomic positions at the interface of a MoS2-WSe2 heterojunction with picometer precision and correlate 3D atomic defects with localized vibrational properties at the epitaxial interface. We observe point defects, bond distortion, and atomic-scale ripples and measure the full 3D strain tensor at the heterointerface. By using the experimental 3D atomic coordinates as direct input to first-principles calculations, we reveal new phonon modes localized at the interface, which are corroborated by spatially resolved electron energy-loss spectroscopy. We expect that this work will pave the way for correlating structure-property relationships of a wide range of heterostructure interfaces at the single-atom level.

Determining the three-dimensional atomic structure of an amorphous solid.

Amorphous solids such as glass, plastics and amorphous thin films are ubiquitous in our daily life and have broad applications ranging from telecommunications to electronics and solar cells1-4. However, owing to the lack of long-range order, the three-dimensional (3D) atomic structure of amorphous solids has so far eluded direct experimental determination5-15. Here we develop an atomic electron tomography reconstruction method to experimentally determine the 3D atomic positions of an amorphous solid. Using a multi-component glass-forming alloy as proof of principle, we quantitatively characterize the short- and medium-range order of the 3D atomic arrangement. We observe that, although the 3D atomic packing of the short-range order is geometrically disordered, some short-range-order structures connect with each other to form crystal-like superclusters and give rise to medium-range order. We identify four types of crystal-like medium-range order-face-centred cubic, hexagonal close-packed, body-centred cubic and simple cubic-coexisting in the amorphous sample, showing translational but not orientational order. These observations provide direct experimental evidence to support the general framework of the efficient cluster packing model for metallic glasses10,12-14,16. We expect that this work will pave the way for the determination of the 3D structure of a wide range of amorphous solids, which could transform our fundamental understanding of non-crystalline materials and related phenomena.

Nondestructive, high-resolution, chemically specific 3D nanostructure characterization using phase-sensitive EUV imaging reflectometry.

Next-generation nano- and quantum devices have increasingly complex 3D structure. As the dimensions of these devices shrink to the nanoscale, their performance is often governed by interface quality or precise chemical or dopant composition. Here, we present the first phase-sensitive extreme ultraviolet imaging reflectometer. It combines the excellent phase stability of coherent high-harmonic sources, the unique chemical sensitivity of extreme ultraviolet reflectometry, and state-of-the-art ptychography imaging algorithms. This tabletop microscope can nondestructively probe surface topography, layer thicknesses, and interface quality, as well as dopant concentrations and profiles. High-fidelity imaging was achieved by implementing variable-angle ptychographic imaging, by using total variation regularization to mitigate noise and artifacts in the reconstructed image, and by using a high-brightness, high-harmonic source with excellent intensity and wavefront stability. We validate our measurements through multiscale, multimodal imaging to show that this technique has unique advantages compared with other techniques based on electron and scanning probe microscopies.

X-ray linear dichroic ptychography.

Biominerals such as seashells, coral skeletons, bone, and tooth enamel are optically anisotropic crystalline materials with unique nanoscale and microscale organization that translates into exceptional macroscopic mechanical properties, providing inspiration for engineering new and superior biomimetic structures. Using Seriatopora aculeata coral skeleton as a model, here, we experimentally demonstrate X-ray linear dichroic ptychography and map the c-axis orientations of the aragonite (CaCO3) crystals. Linear dichroic phase imaging at the oxygen K-edge energy shows strong polarization-dependent contrast and reveals the presence of both narrow (<35°) and wide (>35°) c-axis angular spread in the coral samples. These X-ray ptychography results are corroborated by four-dimensional (4D) scanning transmission electron microscopy (STEM) on the same samples. Evidence of co-oriented, but disconnected, corallite subdomains indicates jagged crystal boundaries consistent with formation by amorphous nanoparticle attachment. We expect that the combination of X-ray linear dichroic ptychography and 4D STEM could be an important multimodal tool to study nano-crystallites, interfaces, nucleation, and mineral growth of optically anisotropic materials at multiple length scales.

Author Correction: Chemical trends of deep levels in van der Waals semiconductors.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20151-x.

Chemical trends of deep levels in van der Waals semiconductors.

Properties of semiconductors are largely defined by crystal imperfections including native defects. Van der Waals (vdW) semiconductors, a newly emerged class of materials, are no exception: defects exist even in the purest materials and strongly affect their electrical, optical, magnetic, catalytic and sensing properties. However, unlike conventional semiconductors where energy levels of defects are well documented, they are experimentally unknown in even the best studied vdW semiconductors, impeding the understanding and utilization of these materials. Here, we directly evaluate deep levels and their chemical trends in the bandgap of MoS2, WS2 and their alloys by transient spectroscopic study. One of the deep levels is found to follow the conduction band minimum of each host, attributed to the native sulfur vacancy. A switchable, DX center - like deep level has also been identified, whose energy lines up instead on a fixed level across different hosts, explaining a persistent photoconductivity above 400 K.