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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.
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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.
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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.
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Nucleation plays a critical role in many physical and biological phenomena that range from crystallization, melting and evaporation to the formation of clouds and the initiation of neurodegenerative diseases1-3. However, nucleation is a challenging process to study experimentally, especially in its early stages, when several atoms or molecules start to form a new phase from a parent phase. A number of experimental and computational methods have been used to investigate nucleation processes4-17, but experimental determination of the three-dimensional atomic structure and the dynamics of early-stage nuclei has been unachievable. Here we use atomic electron tomography to study early-stage nucleation in four dimensions (that is, including time) at atomic resolution. Using FePt nanoparticles as a model system, we find that early-stage nuclei are irregularly shaped, each has a core of one to a few atoms with the maximum order parameter, and the order parameter gradient points from the core to the boundary of the nucleus. We capture the structure and dynamics of the same nuclei undergoing growth, fluctuation, dissolution, merging and/or division, which are regulated by the order parameter distribution and its gradient. These experimental observations are corroborated by molecular dynamics simulations of heterogeneous and homogeneous nucleation in liquid-solid phase transitions of Pt. Our experimental and molecular dynamics results indicate that a theory beyond classical nucleation theory1,2,18 is needed to describe early-stage nucleation at the atomic scale. We anticipate that the reported approach will open the door to the study of many fundamental problems in materials science, nanoscience, condensed matter physics and chemistry, such as phase transition, atomic diffusion, grain boundary dynamics, interface motion, defect dynamics and surface reconstruction with four-dimensional atomic resolution.
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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.
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Antozoários/química , Biomimética , Biomineralização , Cristalinas/química , Animais , Anisotropia , Antozoários/ultraestrutura , Carbonato de Cálcio/química , Cristalinas/ultraestrutura , Microscopia Eletrônica de Transmissão e Varredura , Minerais/química , Radiografia , Engenharia Tecidual , Raios XRESUMO
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.
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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.
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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.
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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.
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Aprendizado Profundo , Nanopartículas Metálicas , Elétrons , Ouro , Redes Neurais de Computação , AlgoritmosRESUMO
Perfect crystals are rare in nature. Real materials often contain crystal defects and chemical order/disorder such as grain boundaries, dislocations, interfaces, surface reconstructions and point defects. Such disruption in periodicity strongly affects material properties and functionality. Despite rapid development of quantitative material characterization methods, correlating three-dimensional (3D) atomic arrangements of chemical order/disorder and crystal defects with material properties remains a challenge. On a parallel front, quantum mechanics calculations such as density functional theory (DFT) have progressed from the modelling of ideal bulk systems to modelling 'real' materials with dopants, dislocations, grain boundaries and interfaces; but these calculations rely heavily on average atomic models extracted from crystallography. To improve the predictive power of first-principles calculations, there is a pressing need to use atomic coordinates of real systems beyond average crystallographic measurements. Here we determine the 3D coordinates of 6,569 iron and 16,627 platinum atoms in an iron-platinum nanoparticle, and correlate chemical order/disorder and crystal defects with material properties at the single-atom level. We identify rich structural variety with unprecedented 3D detail including atomic composition, grain boundaries, anti-phase boundaries, anti-site point defects and swap defects. We show that the experimentally measured coordinates and chemical species with 22 picometre precision can be used as direct input for DFT calculations of material properties such as atomic spin and orbital magnetic moments and local magnetocrystalline anisotropy. This work combines 3D atomic structure determination of crystal defects with DFT calculations, which is expected to advance our understanding of structure-property relationships at the fundamental level.
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The electronic, optical and chemical properties of two-dimensional transition metal dichalcogenides strongly depend on their three-dimensional atomic structure and crystal defects. Using Re-doped MoS2 as a model system, here we present scanning atomic electron tomography as a method to determine three-dimensional atomic positions as well as positions of crystal defects such as dopants, vacancies and ripples with a precision down to 4 pm. We measure the three-dimensional bond distortion and local strain tensor induced by single dopants. By directly providing these experimental three-dimensional atomic coordinates to density functional theory, we obtain more accurate electronic band structures than derived from conventional density functional theory calculations that relies on relaxed three-dimensional atomic coordinates. We anticipate that scanning atomic electron tomography not only will be generally applicable to determine the three-dimensional atomic coordinates of two-dimensional materials, but also will enable ab initio calculations to better predict the physical, chemical and electronic properties of these materials.
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Attosecond science has been transforming our understanding of electron dynamics in atoms, molecules, and solids. However, to date almost all of the attoscience experiments have been based on spectroscopic measurements because attosecond pulses have intrinsically very broad spectra due to the uncertainty principle and are incompatible with conventional imaging systems. Here we report an important advance towards achieving attosecond coherent diffractive imaging. Using simulated attosecond pulses, we simultaneously reconstruct the spectrum, 17 probes, and 17 spectral images of extended objects from a set of ptychographic diffraction patterns. We further confirm the principle and feasibility of this method by successfully performing a ptychographic coherent diffractive imaging experiment using a light-emitting diode with a broad spectrum. We believe this work clears the way to an unexplored domain of attosecond imaging science, which could have a far-reaching impact across different disciplines.
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Since the involute profile error of a gear shaft influences its transmission performance, it is desirable to accurately and quickly measure its involute profiles. With the advantages of low cost, universal applicability and in situ detection, a vision measuring method for multiple involute profiles of a gear shaft is developed only using one image in this study. The base circle radius and initial position angle of the involute are obtained by geometrically fitting the involute profile. The correctness and reliability of the method are tested by measuring the pitch deviation of the gear shaft; a specialized experiment is carried out; and the factors affecting the measurement accuracy also are analyzed.
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In this paper, we report the development of the generalized proximal smoothing (GPS) algorithm for phase retrieval of noisy data. GPS is a optimization-based algorithm, in which we relax both the Fourier magnitudes and support constraint. We relax the support constraint by incorporating the Moreau-Yosida regularization and heat kernel smoothing, and derive the associated proximal mapping. We also relax the magnitude constraint into a least squares fidelity term, whose proximal mapping is available as well. GPS alternatively iterates between the two proximal mappings in primal and dual spaces, respectively. Using both numerical simulation and experimental data, we show that GPS algorithm consistently outperforms the classical phase retrieval algorithms such as hybrid input-output (HIO) and oversampling smoothness (OSS), in terms of the convergence speed, consistency of the phase retrieval, and robustness to noise.
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Alternating projection based methods, such as ePIE and rPIE, have been used widely in ptychography. However, they only work well if there are adequate measurements (diffraction patterns); in the case of sparse data (i.e. fewer measurements) alternating projection underperforms and might not even converge. In this paper, we propose semi-implicit relaxed Douglas-Rachford (sDR), an accelerated iterative method, to solve the classical ptychography problem. Using both simulated and experimental data, we show that sDR improves the convergence speed and the reconstruction quality relative to extended ptychographic iterative engine (ePIE) and regularized ptychographic iterative engine (rPIE). Furthermore, in certain cases when sparsity is high, sDR converges while ePIE and rPIE fail or encounter slow convergence. To facilitate others to use the algorithm, we post the Matlab source code of sDR on a public website (www.physics.ucla.edu/research/imaging/sDR/index.html). We anticipate that this algorithm can be generally applied to the ptychographic reconstruction of a wide range of samples in the physical and biological sciences.
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Dislocations and their interactions strongly influence many material properties, ranging from the strength of metals and alloys to the efficiency of light-emitting diodes and laser diodes. Several experimental methods can be used to visualize dislocations. Transmission electron microscopy (TEM) has long been used to image dislocations in materials, and high-resolution electron microscopy can reveal dislocation core structures in high detail, particularly in annular dark-field mode. A TEM image, however, represents a two-dimensional projection of a three-dimensional (3D) object (although stereo TEM provides limited information about 3D dislocations). X-ray topography can image dislocations in three dimensions, but with reduced resolution. Using weak-beam dark-field TEM and scanning TEM, electron tomography has been used to image 3D dislocations at a resolution of about five nanometres (refs 15, 16). Atom probe tomography can offer higher-resolution 3D characterization of dislocations, but requires needle-shaped samples and can detect only about 60 per cent of the atoms in a sample. Here we report 3D imaging of dislocations in materials at atomic resolution by electron tomography. By applying 3D Fourier filtering together with equal-slope tomographic reconstruction, we observe nearly all the atoms in a multiply twinned platinum nanoparticle. We observed atomic steps at 3D twin boundaries and imaged the 3D core structure of edge and screw dislocations at atomic resolution. These dislocations and the atomic steps at the twin boundaries, which appear to be stress-relief mechanisms, are not visible in conventional two-dimensional projections. The ability to image 3D disordered structures such as dislocations at atomic resolution is expected to find applications in materials science, nanoscience, solid-state physics and chemistry.
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Transmission electron microscopy is a powerful imaging tool that has found broad application in materials science, nanoscience and biology. With the introduction of aberration-corrected electron lenses, both the spatial resolution and the image quality in transmission electron microscopy have been significantly improved and resolution below 0.5 ångströms has been demonstrated. To reveal the three-dimensional (3D) structure of thin samples, electron tomography is the method of choice, with cubic-nanometre resolution currently achievable. Discrete tomography has recently been used to generate a 3D atomic reconstruction of a silver nanoparticle two to three nanometres in diameter, but this statistical method assumes prior knowledge of the particle's lattice structure and requires that the atoms fit rigidly on that lattice. Here we report the experimental demonstration of a general electron tomography method that achieves atomic-scale resolution without initial assumptions about the sample structure. By combining a novel projection alignment and tomographic reconstruction method with scanning transmission electron microscopy, we have determined the 3D structure of an approximately ten-nanometre gold nanoparticle at 2.4-ångström resolution. Although we cannot definitively locate all of the atoms inside the nanoparticle, individual atoms are observed in some regions of the particle and several grains are identified in three dimensions. The 3D surface morphology and internal lattice structure revealed are consistent with a distorted icosahedral multiply twinned particle. We anticipate that this general method can be applied not only to determine the 3D structure of nanomaterials at atomic-scale resolution, but also to improve the spatial resolution and image quality in other tomography fields.
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A number of important reactions such as the oxygen evolution reaction (OER) are catalyzed by transition metal oxides (TMOs), the surface reactivity of which is rather elusive. Therefore, rationally tailoring adsorption energy of intermediates on TMOs to achieve desirable catalytic performance still remains a great challenge. Here we show the identification of a general and tunable surface structure, coordinatively unsaturated metal cation (MCUS), as a good surface reactivity descriptor for TMOs in OER. Surface reactivity of a given TMO increases monotonically with the density of MCUS, and thus the increase in MCUS improves the catalytic activity for weak-binding TMOs but impairs that for strong-binding ones. The electronic origin of the surface reactivity can be well explained by a new model proposed in this work, wherein the energy of the highest-occupied d-states relative to the Fermi level determines the intermediates' bonding strength by affecting the filling of the antibonding states. Our model for the first time well describes the reactivity trends among TMOs, and would initiate viable design principles for, but not limited to, OER catalysts.
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In situ X-ray diffraction (XRD) and transmission electron microscopy (TEM) have been used to investigate many physical science phenomena, ranging from phase transitions, chemical reactions and crystal growth to grain boundary dynamics. A major limitation of in situ XRD and TEM is a compromise that has to be made between spatial and temporal resolution. Here, we report the development of in situ X-ray nanodiffraction to measure high-resolution diffraction patterns from single grains with up to 5 ms temporal resolution. We observed, for the first time, grain rotation and lattice deformation in chemical reactions induced by X-ray photons: Br(-) + hv â Br + e(-) and e(-) + Ag(+) â Ag(0). The grain rotation and lattice deformation associated with the chemical reactions were quantified to be as fast as 3.25 rad s(-1) and as large as 0.5 Å, respectively. The ability to measure high-resolution diffraction patterns from individual grains with a temporal resolution of several milliseconds is expected to find broad applications in materials science, physics, chemistry and nanoscience.