Three-dimensional coordinates of individual atoms in materials revealed by electron tomography

Tracking the extensive three-dimensional motion of single ions by an engineered point-spread function

Three-dimensional (3D) imaging of individual atoms is a critical tool for discovering new physical phenomena and developing new technologies in microscopic systems. However, the current single-atom-resolved 3D imaging methods are limited to static circumstances or a shallow detection range. Here, we demonstrate a generic dynamic 3D imaging method to track the extensive motion of single ions by exploiting the engineered point-spread function (PSF). We show that the image of a single ion can be engineered into a helical PSF, thus enabling single-snapshot acquisition of the position information of the ion in the trap. A preliminary application of this technique is demonstrated by recording the 3D motion trajectory of a single trapped ion and reconstructing the 3D dynamical configuration transition between the zig and zag structures of a 5-ion crystal. This work opens the path for studies on single-atom-resolved dynamics in both trapped-ion and neutral-atom systems.

Atomic-Scale 3D Structure of a Supported Pd Nanoparticle Revealed by Electron Tomography with Convolution Neural Network-Based Image Inpainting

Electron tomography based on scanning transmission electron microscopy (STEM) is used to analyze 3D structures of metal nanoparticles on the atomic scale. However, in the case of supported metal nanoparticle catalysts, the supporting material may interfere with the 3D reconstruction of metal nanoparticles. In this study, a deep learning-based image inpainting method is applied to high-angle annular dark field (HAADF)-STEM images of a supported metal nanoparticle to predict and remove the background image of the support. The inpainting method can separate an 11 nm Pd nanoparticle from the θ-Al2O3 support in HAADF-STEM images of the θ-Al2O3-supported Pd catalyst. 3D reconstruction of the extracted images of the Pd nanoparticle reveals that the Pd nanoparticle adopts a deformed structure of the cuboctahedron model particle, resulting in high index surfaces, which account for the high catalytic activity for methane combustion. Using the xyz coordinate of each Pd atom, the local Pd-Pd bond distance and its variance in a real supported Pd nanoparticle are visualized, showing large strain and disorder at the Pd-Al2O3 interface. The results demonstrate that 3D atomic-scale analysis enables atomic structure-based understanding and design of supported metal catalysts.

Revealing the three-dimensional arrangement of polar topology in nanoparticles

In the early 2000s, low dimensional ferroelectric systems were predicted to have topologically nontrivial polar structures, such as vortices or skyrmions, depending on mechanical or electrical boundary conditions. A few variants of these structures have been experimentally observed in thin film model systems, where they are engineered by balancing electrostatic charge and elastic distortion energies. However, the measurement and classification of topological textures for general ferroelectric nanostructures have remained elusive, as it requires mapping the local polarization at the atomic scale in three dimensions. Here we unveil topological polar structures in ferroelectric BaTiO3 nanoparticles via atomic electron tomography, which enables us to reconstruct the full three-dimensional arrangement of cation atoms at an individual atom level. Our three-dimensional polarization maps reveal clear topological orderings, along with evidence of size-dependent topological transitions from a single vortex structure to multiple vortices, consistent with theoretical predictions. The discovery of the predicted topological polar ordering in nanoscale ferroelectrics, independent of epitaxial strain, widens the research perspective and offers potential for practical applications utilizing contact-free switchable toroidal moments.

Imaging 3D chemistry at 1 nm resolution with fused multi-modal electron tomography

Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment is completed. Even larger doses are required to achieve high resolution. Thus, chemical mapping in 3D has been unachievable except at lower resolution with the most radiation-hard materials. Here, high-resolution 3D chemical imaging is achieved near or below one-nanometer resolution in an Au-Fe3O4 metamaterial within an organic ligand matrix, Co3O4-Mn3O4 core-shell nanocrystals, and ZnS-Cu0.64S0.36 nanomaterial using fused multi-modal electron tomography. Multi-modal data fusion enables high-resolution chemical tomography often with 99% less dose by linking information encoded within both elastic (HAADF) and inelastic (EDX/EELS) signals. We thus demonstrate that sub-nanometer 3D resolution of chemistry is measurable for a broad class of geometrically and compositionally complex materials.

Support-facet-dependent morphology of small Pt particles on ceria

Direct atomic scale information on how the structure of supported nanoparticles is affected by the metal-support interaction is rare. Using scanning transmission electron microscopy, we provide direct evidence of a facet-dependent support interaction for Pt nanoparticles on CeO2, governing the dimensionality of small platinum particles. Our findings indicate that particles consisting of less than ∼130 atoms prefer a 3D shape on CeO2(111) facets, while 2D raft structures are favored on CeO2(100) facets. Measurements of stationary particles on both surface facets are supplemented by time resolved measurements following a single particle with atomic resolution as it migrates from CeO2(111) to CeO2(100), undergoing a dimensionality change from 3D to 2D. The intricate transformation mechanism reveals how the 3D particle disassembles and completely wets a neighboring CeO2(100) facet. Density functional theory calculations confirm the structure-trend and reveal the thermodynamic driving force for the migration of small particles. Knowledge of the presented metal-support interactions is crucial to establish structure-function relationships in a range of applications based on supported nanostructures.

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.

Solving complex nanostructures with ptychographic atomic electron tomography

Transmission electron microscopy (TEM) is essential for determining atomic scale structures in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined from thousands of identical particles using phase-contrast TEM. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform ptychographic electron tomography from 34.5 million diffraction patterns to reconstruct an atomic resolution tilt series of a double wall-carbon nanotube (DW-CNT) encapsulating a complex ZrTe sandwich structure. Class averaging the resulting tilt series images and subpixel localization of the atomic peaks reveals a Zr11Te50 structure containing a previously unobserved ZrTe2 phase in the core. The experimental realization of atomic resolution ptychographic electron tomography will allow for the structural determination of a wide range of beam-sensitive nanomaterials containing light elements.

Accurate Force Fields for Atomistic Simulations of Oxides, Hydroxides, and Organic Hybrid Materials up to the Micrometer Scale

The simulation of metals, oxides, and hydroxides can accelerate the design of therapeutics, alloys, catalysts, cement-based materials, ceramics, bioinspired composites, and glasses. Here we introduce the INTERFACE force field (IFF) and surface models for α-Al2O3, α-Cr2O3, α-Fe2O3, NiO, CaO, MgO, β-Ca(OH)2, β-Mg(OH)2, and β-Ni(OH)2. The force field parameters are nonbonded, including atomic charges for Coulomb interactions, Lennard-Jones (LJ) potentials for van der Waals interactions with 12-6 and 9-6 options, and harmonic bond stretching for hydroxide ions. The models outperform DFT calculations and earlier atomistic models (Pedone, ReaxFF, UFF, CLAYFF) up to 2 orders of magnitude in reliability, compatibility, and interpretability due to a quantitative representation of chemical bonding consistent with other compounds across the periodic table and curated experimental data for validation. The IFF models exhibit average deviations of 0.2% in lattice parameters, <10% in surface energies (to the extent known), and 6% in bulk moduli relative to experiments. The parameters and models can be used with existing parameters for solvents, inorganic compounds, organic compounds, biomolecules, and polymers in IFF, CHARMM, CVFF, AMBER, OPLS-AA, PCFF, and COMPASS, to simulate bulk oxides, hydroxides, electrolyte interfaces, and multiphase, biological, and organic hybrid materials at length scales from atoms to micrometers. The nonbonded character of the models also enables the analysis of mixed oxides, glasses, and certain chemical reactions, and well-performing nonbonded models for silica phases, SiO2, are introduced. Automated model building is available in the CHARMM-GUI Nanomaterial Modeler. We illustrate applications of the models to predict the structure of mixed oxides, and energy barriers of ion migration, as well as binding energies of water and organic molecules in outstanding agreement with experimental data and calculations at the CCSD(T) level. Examples of model building for hydrated, pH-sensitive oxide surfaces to simulate solid-electrolyte interfaces are discussed.

Accelerating Quantum Materials Development with Advances in Transmission Electron Microscopy

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, superconductors, quantum dots, color center-hosting semiconductors, and other types of strongly correlated materials can exhibit exotic properties such as edge conductivity, multiferroicity, magnetoresistance, superconductivity, single photon emission, and optical-spin locking. These emergent properties arise and depend strongly on the material's detailed atomic-scale structure, including atomic defects, dopants, and lattice stacking. In this review, we describe how progress in the field of electron microscopy (EM), including in situ and in operando EM, can accelerate advances in quantum materials and quantum excitations. We begin by describing fundamental EM principles and operation modes. We then discuss various EM methods such as (i) EM spectroscopies, including electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and electron energy gain spectroscopy (EEGS); (ii) four-dimensional scanning transmission electron microscopy (4D-STEM); (iii) dynamic and ultrafast EM (UEM); (iv) complementary ultrafast spectroscopies (UED, XFEL); and (v) atomic electron tomography (AET). We describe how these methods could inform structure-function relations in quantum materials down to the picometer scale and femtosecond time resolution, and how they enable precision positioning of atomic defects and high-resolution manipulation of quantum materials. For each method, we also describe existing limitations to solve open quantum mechanical questions, and how they might be addressed to accelerate progress. Among numerous notable results, our review highlights how EM is enabling identification of the 3D structure of quantum defects; measuring reversible and metastable dynamics of quantum excitations; mapping exciton states and single photon emission; measuring nanoscale thermal transport and coupled excitation dynamics; and measuring the internal electric field and charge density distribution of quantum heterointerfaces- all at the quantum materials' intrinsic atomic and near atomic-length scale. We conclude by describing open challenges for the future, including achieving stable sample holders for ultralow temperature (below 10K) atomic-scale spatial resolution, stable spectrometers that enable meV energy resolution, and high-resolution, dynamic mapping of magnetic and spin fields. With atomic manipulation and ultrafast characterization enabled by EM, quantum materials will be poised to integrate into many of the sustainable and energy-efficient technologies needed for the 21st century.

Advanced techniques in automated high-resolution scanning transmission electron microscopy

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using an all-piezo sample stage applied to large-scale imaging of nanoparticles and multimodal data acquisition. The system is available as part of the user program of the Molecular Foundry at Lawrence Berkeley National Laboratory.

Autonomous Electron Tomography Reconstruction with Machine Learning

Modern electron tomography has progressed to higher resolution at lower doses by leveraging compressed sensing (CS) methods that minimize total variation (TV). However, these sparsity-emphasized reconstruction algorithms introduce tunable parameters that greatly influence the reconstruction quality. Here, Pareto front analysis shows that high-quality tomograms are reproducibly achieved when TV minimization is heavily weighted. However, in excess, CS tomography creates overly smoothed three-dimensional (3D) reconstructions. Adding momentum to the gradient descent during reconstruction reduces the risk of over-smoothing and better ensures that CS is well behaved. For simulated data, the tedious process of tomography parameter selection is efficiently solved using Bayesian optimization with Gaussian processes. In combination, Bayesian optimization with momentum-based CS greatly reduces the required compute time-an 80% reduction was observed for the 3D reconstruction of SrTiO3 nanocubes. Automated parameter selection is necessary for large-scale tomographic simulations that enable the 3D characterization of a wider range of inorganic and biological materials.

Lattice-Strain Engineering for Heterogenous Electrocatalytic Oxygen Evolution Reaction

The energy efficiency of metal-air batteries and water-splitting techniques is severely constrained by multiple electronic transfers in the heterogenous oxygen evolution reaction (OER), and the high overpotential induced by the sluggish kinetics has become an uppermost scientific challenge. Numerous attempts are devoted to enabling high activity, selectivity, and stability via tailoring the surface physicochemical properties of nanocatalysts. Lattice-strain engineering as a cutting-edge method for tuning the electronic and geometric configuration of metal sites plays a pivotal role in regulating the interaction of catalytic surfaces with adsorbate molecules. By defining the d-band center as a descriptor of the structure-activity relationship, the individual contribution of strain effects within state-of-the-art electrocatalysts can be systematically elucidated in the OER optimization mechanism. In this review, the fundamentals of the OER and the advancements of strain-catalysts are showcased and the innovative trigger strategies are enumerated, with particular emphasis on the feedback mechanism between the precise regulation of lattice-strain and optimal activity. Subsequently, the modulation of electrocatalysts with various attributes is categorized and the impediments encountered in the practicalization of strained effect are discussed, ending with an outlook on future research directions for this burgeoning field.

A highly accurate quantum optimization algorithm for CT image reconstruction based on sinogram patterns

Computed tomography (CT) has been developed as a nondestructive technique for observing minute internal images in samples. It has been difficult to obtain photorealistic (clean or clear) CT images due to various unwanted artifacts generated during the CT scanning process, along with the limitations of back-projection algorithms. Recently, an iterative optimization algorithm has been developed that uses an entire sinogram to reduce errors caused by artifacts. In this paper, we introduce a new quantum algorithm for reconstructing CT images. This algorithm can be used with any type of light source as long as the projection is defined. Assuming an experimental sinogram produced by a Radon transform, to find the CT image of this sinogram, we express the CT image as a combination of qubits. After acquiring the Radon transform of the undetermined CT image, we combine the actual sinogram and the optimized qubits. The global energy optimization value used here can determine the value of qubits through a gate model quantum computer or quantum annealer. In particular, the new algorithm can also be used for cone-beam CT image reconstruction and for medical imaging.

Thermodynamics and Kinetics in Anisotropic Growth of One-Dimensional Midentropy Nanoribbons

One-dimensional (1D) materials demonstrate anisotropic in-plane physical properties that enable a wide range of functionalities in electronics, photonics, valleytronics, optoelectronics, and catalysis. Here, we undertake an in-depth study of the growth mechanism for equimolar midentropy alloy of (NbTaTi)_0.33S₃ nanoribbons as a model system for 1D transition metal trichalcogenide structures. To understand the thermodynamic and kinetic effects in the growth process, the energetically preferred phases at different synthesis temperatures and times are investigated, and the phase evolution is inspected at a sequence of growth steps. It is uncovered that the dynamics of the growth process occurs at four different stages via preferential incorporation of chemical species at high-surface-energy facets. Also, a sequence of temperature and time dependent nonuniform to uniform phase evolutions has emerged in the composition and structure of (NbTaTi)_0.33S₃ which is described based on an anisotropic vapor-solid (V-S) mechanism. Furthermore, direct evidence for the 3D structure of the charge density wave (CDW) phase (width less than 100 nm) is provided by three-dimensional electron diffraction (3DED) in individual nanoribbons at cryogenic temperature, and detailed comparisons are made between the phases obtained before and after CDW transformation. This study provides important fundamental information for the design and synthesis of future 1D alloy structures.

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.

Cones and spirals: Multi-axis acquisition for scalar and vector electron tomography

Electron tomography (ET) has become an important tool for understanding the 3D nature of nanomaterials, with recent developments enabling not only scalar reconstructions of electron density, but also vector reconstructions of magnetic fields. However, whilst new signals have been incorporated into the ET toolkit, the acquisition schemes have largely kept to conventional single-axis tilt series for scalar ET, and dual-axis schemes for magnetic vector ET. In this work, we explore the potential of using multi-axis tilt schemes including conical and spiral tilt schemes to improve reconstruction fidelity in scalar and magnetic vector ET. Through a combination of systematic simulations and a proof-of-concept experiment, we show that spiral and conical tilt schemes have the potential to produce substantially improved reconstructions, laying the foundations of a new approach to electron tomography acquisition and reconstruction.

Probing the atomically diffuse interfaces in Pd@Pt core-shell nanoparticles in three dimensions

Deciphering the three-dimensional atomic structure of solid-solid interfaces in core-shell nanomaterials is the key to understand their catalytical, optical and electronic properties. Here, we probe the three-dimensional atomic structures of palladium-platinum core-shell nanoparticles at the single-atom level using atomic resolution electron tomography. We quantify the rich structural variety of core-shell nanoparticles with heteroepitaxy in 3D at atomic resolution. Instead of forming an atomically-sharp boundary, the core-shell interface is found to be atomically diffuse with an average thickness of 4.2 Å, irrespective of the particle's morphology or crystallographic texture. The high concentration of Pd in the diffusive interface is highly related to the free Pd atoms dissolved from the Pd seeds, which is confirmed by atomic images of Pd and Pt single atoms and sub-nanometer clusters using cryogenic electron microscopy. These results advance our understanding of core-shell structures at the fundamental level, providing potential strategies into precise nanomaterial manipulation and chemical property regulation.

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 .

Revealing 3D Ripple Structure and Its Dynamics in Freestanding Monolayer MoSe2 by Single-Frame 2D Atomic Image Reconstruction

An atomic-scale ripple structure has been revealed by electron tomography based on sequential projected atomic-resolution images, but it requires harsh imaging conditions with negligible structure evolution of the imaged samples. Here, we demonstrate that the ripple structure in monolayer MoSe₂ can be facilely reconstructed from a single-frame scanning transmission electron microscopy (STEM) image collected at designated collection angles. The intensity and shape of each Se₂ atomic column in the single-frame projected STEM image are synergistically combined to precisely map the slight misalignments of two Se atoms induced by rippling, which is then converted to three-dimensional (3D) ripple distortions. The dynamics of 3D ripple deformation can thus be directly visualized at the atomic scale by sequential STEM imaging. In addition, the reconstructed images provide the first opportunity for directly testing the validity of the classical theory of thermal fluctuations. Our method paves the way for a 3D reconstruction of a dynamical process in two-dimensional materials with a reasonable temporal resolution.

Probing Electron Beam Induced Transformations on a Single-Defect Level via Automated Scanning Transmission Electron Microscopy

A robust approach for real-time analysis of the scanning transmission electron microscopy (STEM) data streams, based on ensemble learning and iterative training (ELIT) of deep convolutional neural networks, is implemented on an operational microscope, enabling the exploration of the dynamics of specific atomic configurations under electron beam irradiation via an automated experiment in STEM. Combined with beam control, this approach allows studying beam effects on selected atomic groups and chemical bonds in a fully automated mode. Here, we demonstrate atomically precise engineering of single vacancy lines in transition metal dichalcogenides and the creation and identification of topological defects in graphene. The ELIT-based approach facilitates direct on-the-fly analysis of the STEM data and engenders real-time feedback schemes for probing electron beam chemistry, atomic manipulation, and atom by atom assembly.

Direct strain correlations at the single-atom level in three-dimensional core-shell interface structures

Nanomaterials with core-shell architectures are prominent examples of strain-engineered materials. The lattice mismatch between the core and shell materials can cause strong interface strain, which affects the surface structures. Therefore, surface functional properties such as catalytic activities can be designed by fine-tuning the misfit strain at the interface. To precisely control the core-shell effect, it is essential to understand how the surface and interface strains are related at the atomic scale. Here, we elucidate the surface-interface strain relations by determining the full 3D atomic structure of Pd@Pt core-shell nanoparticles at the single-atom level via atomic electron tomography. Full 3D displacement fields and strain profiles of core-shell nanoparticles were obtained, which revealed a direct correlation between the surface and interface strain. The strain distributions show a strong shape-dependent anisotropy, whose nature was further corroborated by molecular statics simulations. From the observed surface strains, the surface oxygen reduction reaction activities were predicted. These findings give a deep understanding of structure-property relationships in strain-engineerable core-shell systems, which can lead to direct control over the resulting catalytic properties.

Understanding 3D interfacial strain at the atomic level has been a long-sought challenge in the field of core-shell nanomaterials. Here, the authors address this challenge by revealing the full 3D atomic structures of Pd@Pt core-shell nanoparticles

High-Resolution Electron Tomography of Ultrathin Boerdijk-Coxeter-Bernal Nanowire Enabled by Superthin Metal Surface Coating

The rapid advancement of transmission electron microscopy has resulted in revolutions in a variety of fields, including physics, chemistry, and materials science. With single-atom resolution, 3D information of each atom in nanoparticles is revealed, while 4D electron tomography is shown to capture the atomic structural kinetics in metal nanoparticles after phase transformation. Quantitative measurements of physical and chemical properties such as chemical coordination, defects, dislocation, and local strain have been made. However, due to the incompatibility of high dose rate with other ultrathin morphologies, such as nanowires, atomic electron tomography has been primarily limited to quasi-spherical nanoparticles. Herein, the 3D atomic structure of a complex core-shell nanowire composed of an ultrathin Boerdijk-Coxeter-Bernal (BCB) core nanowire and a noble metal thin layer shell deposited on the BCB nanowire surface is discovered. Furthermore, it is demonstrated that a new superthin noble metal layer deposition on an ultrathin BCB nanowire could mitigate electron beam damage using an in situ transmission electron microscope and atomic resolution electron tomography. The colloidal coating method developed for electron tomography can be broadly applied to protect the ultrathin nanomaterials from electron beam damage, benefiting both the advanced material characterizations and enabling fundamental in situ mechanistic studies.

Precisely Picking Nanoparticles by a "Nano-Scalpel" for 360° Electron Tomography

Electron tomography (ET) has gained increasing attention for the 3D characterization of nanoparticles. However, the missing wedge problem due to a limited tilt angle range is still the main challenge for accurate reconstruction in most experimental TEM setups. Advanced algorithms could in-paint or compensate to some extent the missing wedge artifacts, but cannot recover the missing structural information completely. 360° ET provides an option to solve this problem by tilting a needle-shaped specimen over the full tilt range and thus filling the missing information. However, sample preparation especially for fine powders to perform full-range ET is still challenging, thus limiting its application. In this work, we propose a new universal sample preparation method that enables the transfer of selected individual nanoparticle or a few separated nanoparticles by cutting a piece of carbon film supporting the specimen particles and mounting them onto the full-range tomography holder tip with the help of an easily prepared sharp tungsten tip. This method is demonstrated by 360° ET of Pt@TiO2 hollow cage catalyst showing high quality reconstruction without missing wedge.

Beam-driven Dynamics of Aluminium Dopants in Graphene

Substituting heteroatoms into graphene can tune its properties for applications ranging from catalysis to spintronics. The further recent discovery that covalent impurities in graphene can be manipulated at atomic precision using a focused electron beam may open avenues towards sub-nanometer device architectures. However, the preparation of clean samples with a high density of dopants is still very challenging. Here, we report vacancy-mediated substitution of aluminium into laser-cleaned graphene, and without removal from our ultra-high vacuum apparatus, study their dynamics under 60 keV electron irradiation using aberration-corrected scanning transmission electron microscopy and spectroscopy. Three- and four-coordinated Al sites are identified, showing excellent agreement with ab initio predictions including binding energies and electron energy-loss spectrum simulations. We show that the direct exchange of carbon and aluminium atoms predicted earlier occurs under electron irradiation, although unexpectedly it is less probable than the same process for silicon. We also observe a previously unknown nitrogen-aluminium exchange that occurs at Al─N double-dopant sites at graphene divacancies created by our plasma treatment.

Direct Observation of Three-Dimensional Atomic Structure of Twinned Metallic Nanoparticles and Their Catalytic Properties

We determined a full 3D atomic structure of a dumbbell-shaped Pt nanoparticle formed by a coalescence of two nanoclusters using deep learning assisted atomic electron tomography. Formation of a double twin boundary was clearly observed at the interface, while substantial anisotropy and disorder were also found throughout the nanodumbbell. This suggests that the diffusion of interfacial atoms mainly governed the coalescence process, but other dynamic processes such as surface restructuring and plastic deformation were also involved. A full 3D strain tensor was clearly mapped, which allows direct calculation of the oxygen reduction reaction activity at the surface. Strong tensile strain was found at the protruded region of the nanodumbbell, which results in an improved catalytic activity on {100} facets. This work provides important clues regarding the coalescence mechanism and the relation between the atomic structure and catalytic property at the single-atom level.

Simultaneous Successive Twinning Captured by Atomic Electron Tomography

Shape-controlled synthesis of multiply twinned nanostructures is heavily emphasized in nanoscience, in large part due to the desire to control the size, shape, and terminating facets of metal nanoparticles for applications in catalysis. Direct control of the size and shape of solution-grown nanoparticles relies on an understanding of how synthetic parameters alter nanoparticle structures during synthesis. However, while outcome populations can be effectively studied with standard electron microscopy methods, transient structures that appear during some synthetic routes are difficult to study using conventional high resolution imaging methods due to the high complexity of the 3D nanostructures. Here, we have studied the prevalence of transient structures during growth of multiply twinned particles and employed atomic electron tomography to reveal the atomic-scale three-dimensional structure of a Pd nanoparticle undergoing a shape transition. By identifying over 20 000 atoms within the structure and classifying them according to their local crystallographic environment, we observe a multiply twinned structure consistent with a simultaneous successive twinning from a decahedral to icosahedral structure.

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 nano-scale lattice distortions in implanted material with 3D Bragg ptychography

Small ion-irradiation-induced defects can dramatically alter material properties and speed up degradation. Unfortunately, most of the defects irradiation creates are below the visibility limit of state-of-the-art microscopy. As such, our understanding of their impact is largely based on simulations with major unknowns. Here we present an x-ray crystalline microscopy approach, able to image with high sensitivity, nano-scale 3D resolution and extended field of view, the lattice strains and tilts in crystalline materials. Using this enhanced Bragg ptychography tool, we study the damage helium-ion-irradiation produces in tungsten, revealing a series of crystalline details in the 3D sample. Our results lead to the conclusions that few-atom-large 'invisible' defects are likely isotropic in orientation and homogeneously distributed. A partially defect-denuded region is observed close to a grain boundary. These findings open up exciting perspectives for the modelling of irradiation damage and the detailed analysis of crystalline properties in complex materials.

Recent Advances and Prospects in Colloidal Nanomaterials

Colloidal nanomaterials of metals, metal oxides, and metal chalcogenides have attracted great attention in the past decade owing to their potential applications in optoelectronics, catalysis, and energy conversion. Introduction of various synthetic routes has resulted in diverse colloidal nanostructured materials with well-controlled size, shape, and composition, enabling the systematic study of their intriguing physicochemical, optoelectronic, and chemical properties. Furthermore, developments in the instrumentation have offered valuable insights into the nucleation and growth mechanism of these nanomaterials, which are crucial in designing prospective materials with desired properties. In this perspective, recent advances in the colloidal synthesis and mechanism studies of nanomaterials of metal chalcogenides, metals, and metal oxides are discussed. In addition, challenges in the characterization and future direction of the colloidal nanomaterials are provided.

Making the Most of your Electrons: Challenges and Opportunities in Characterizing Hybrid Interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated soft-hard interfaces have recently evoked significant interest. Soft matter is typically dominated by fluctuations even at room temperature, while hard matter (which often serves as the substrate or anchor for the soft component) is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices and metal organic frameworks to name a few, have delivered promising insights into the areas of catalysis, environmental remediation, optoelectronics, medicine, and beyond. The interfacial structure between these hard and soft phases exists across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing the classical structure-property relationships especially difficult. These include challenges associated with preparing electron-transparent samples and obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. We discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or atomic-level understanding of these interfaces. These solutions present a host of opportunities for investigating and understanding the role interfaces play in this unique class of functional materials.

Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning

Due to their ability to recognize complex patterns, neural networks can drive a paradigm shift in the analysis of materials science data. Here, we introduce ARISE, a crystal-structure identification method based on Bayesian deep learning. As a major step forward, ARISE is robust to structural noise and can treat more than 100 crystal structures, a number that can be extended on demand. While being trained on ideal structures only, ARISE correctly characterizes strongly perturbed single- and polycrystalline systems, from both synthetic and experimental resources. The probabilistic nature of the Bayesian-deep-learning model allows to obtain principled uncertainty estimates, which are found to be correlated with crystalline order of metallic nanoparticles in electron tomography experiments. Applying unsupervised learning to the internal neural-network representations reveals grain boundaries and (unapparent) structural regions sharing easily interpretable geometrical properties. This work enables the hitherto hindered analysis of noisy atomic structural data from computations or experiments.

Three-Dimensional Insights into Interfacial Segregation at the Atomic Scale in a Nanocrystalline Glass-Ceramic

The distribution of dopant atoms plays a key role in the effectiveness of doping, thereby requiring delicate characterizations. In this study, we found that energy-dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS) techniques in scanning transmission electron microscopy (STEM) were not adequate to reveal the distribution of yttrium and the chemical composition of the ZrO₂/SiO₂ heterophase interface in an yttrium-doped ZrO₂-SiO₂ nanocrystalline glass-ceramic. Atom probe tomography (APT) is rarely utilized to characterize ceramics due to some inherent difficulties. However, we successfully revealed the three-dimensional distribution of ZrO₂ nanocrystallites and SiO₂ matrix at the atomic scale with APT under optimized and well-controlled conditions. We also found that the ZrO₂ nanocrystallites had a special core-shell structure, with a thin Zr/Si interfacial layer as a shell and a ZrO₂ solid solution as a core. Yttrium dopants showed interfacial segregation at both ZrO₂ grain boundaries and the ZrO₂/SiO₂ heterophase interfaces.

Advances and Applications of Atomic-Resolution Scanning Transmission Electron Microscopy

Although scanning transmission electron microscopy (STEM) images of individual heavy atoms were reported 50 years ago, the applications of atomic-resolution STEM imaging became wide spread only after the practical realization of aberration correctors on field-emission STEM/TEM instruments to form sub-Ångstrom electron probes. The innovative designs and advances of electron optical systems, the fundamental understanding of electron–specimen interaction processes, and the advances in detector technology all played a major role in achieving the goal of atomic-resolution STEM imaging of practical materials. It is clear that tremendous advances in computer technology and electronics, image acquisition and processing algorithms, image simulations, and precision machining synergistically made atomic-resolution STEM imaging routinely accessible. It is anticipated that further hardware/software development is needed to achieve three-dimensional atomic-resolution STEM imaging with single-atom chemical sensitivity, even for electron-beam-sensitive materials. Artificial intelligence, machine learning, and big-data science are expected to significantly enhance the impact of STEM and associated techniques on many research fields such as materials science and engineering, quantum and nanoscale science, physics and chemistry, and biology and medicine. This review focuses on advances of STEM imaging from the invention of the field-emission electron gun to the realization of aberration-corrected and monochromated atomic-resolution STEM and its broad applications.

NUDIM: A non-uniform fast Fourier transform based dual-space constraint iterative reconstruction method in biological electron tomography

Electron tomography, a powerful imaging tool for studying 3D structures of macromolecular assemblies, always suffers from imperfect reconstruction with limited resolution due to the intrinsic low signal-to-noise ratio (SNR) and inaccessibility to certain tilt angles induced by radiation damage or mechanical limitation. In order to compensate for such insufficient data with low SNR and further improve imaging resolution, prior knowledge constraints about the objects in both real space and reciprocal space are thus exploited during tomographic reconstruction. However, direct Fast Fourier transform (FFT) between real space and reciprocal space remains extraordinarily challenging owing to their inconsistent grid sampling modes, e.g. regular and uniform grid sampling in real space whereas radial or polar grid sampling in reciprocal space. In order to solve such problem, a technique of non-uniform fast Fourier transform (NFFT) has been developed to transform efficiently between non-uniformly sampled grids in real and reciprocal space with sufficient accuracy. In this work, a Non-Uniform fast Fourier transform based Dual-space constraint Iterative reconstruction Method (NUDIM) applicable to biological electron tomography is proposed with a combination of basic concepts from equally sloped tomography (EST) and NFFT based reconstruction. In NUDIM, the use of NFFT can circumvent such grid sampling inconsistency and thus alleviate the stringent equally-sloped sampling requirement in EST reconstruction, while the dual-space constraint iterative procedure can dramatically enhance reconstruction quality. In comparison with conventional reconstruction methods, NUDIM is numerically and experimentally demonstrated to produce superior reconstruction quality with higher contrast, less noise and reduced missing wedge artifacts. More importantly, it is also capable of retrieving part of missing information from a limited number of projections.

Contrasting the EXAFS obtained under air and H2 environments to reveal details of the surface structure of Pt-Sn nanoparticles

Understanding the surface structure of bimetallic nanoparticles is crucial for heterogeneous catalysis. Although surface contraction has been established in monometallic systems, less is known for bimetallic systems, especially of nanoparticles. In this work, the bond length contraction on the surface of bimetallic nanoparticles is revealed by XAS in H2 at room temperature on dealloyed Pt-Sn nanoparticles, where most Sn atoms were oxidized and segregated to the surface when measured in air. The average Sn-Pt bond length is found to be ∼0.09 Å shorter than observed in the bulk. To ascertain the effect of the Sn location on the decrease of the average bond length, Pt-Sn samples with lower surface-to-bulk Sn ratios than the dealloyed Pt-Sn were studied. The structural information specifically from the surface was extracted from the averaged XAS results using an improved fitting model combining the data measured in H2 and in air. Two samples prepared so as to ensure the absence of Sn in the bulk were also studied in the same fashion. The bond length of surface Sn-Pt and the corresponding coordination number obtained in this study show a nearly linear correlation, the origin of which is discussed and attributed to the poor overlap between the Sn 5p orbitals and the available orbitals of the Pt surface atoms.

Bragg Coherent Diffraction Imaging for In Situ Studies in Electrocatalysis

Electrocatalysis is at the heart of a broad range of physicochemical applications that play an important role in the present and future of a sustainable economy. Among the myriad of different electrocatalysts used in this field, nanomaterials are of ubiquitous importance. An increased surface area/volume ratio compared to bulk makes nanoscale catalysts the preferred choice to perform electrocatalytic reactions. Bragg coherent diffraction imaging (BCDI) was introduced in 2006 and since has been applied to obtain 3D images of crystalline nanomaterials. BCDI provides information about the displacement field, which is directly related to strain. Lattice strain in the catalysts impacts their electronic configuration and, consequently, their binding energy with reaction intermediates. Even though there have been significant improvements since its birth, the fact that the experiments can only be performed at synchrotron facilities and its relatively low resolution to date (∼10 nm spatial resolution) have prevented the popularization of this technique. Herein, we will briefly describe the fundamentals of the technique, including the electrocatalysis relevant information that we can extract from it. Subsequently, we review some of the computational experiments that complement the BCDI data for enhanced information extraction and improved understanding of the underlying nanoscale electrocatalytic processes. We next highlight success stories of BCDI applied to different electrochemical systems and in heterogeneous catalysis to show how the technique can contribute to future studies in electrocatalysis. Finally, we outline current challenges in spatiotemporal resolution limits of BCDI and provide our perspectives on recent developments in synchrotron facilities as well as the role of machine learning and artificial intelligence in addressing them.

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 cells^1-4. However, owing to the lack of long-range order, the three-dimensional (3D) atomic structure of amorphous solids has so far eluded direct experimental determination^5-15. 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 glasses^10,12-14,16. 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.

Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography

Functional properties of nanomaterials strongly depend on their surface atomic structures, but they often become largely different from their bulk structures, exhibiting surface reconstructions and relaxations. However, most of the surface characterization methods are either limited to 2D measurements or not reaching to true 3D atomic-scale resolution, and single-atom level determination of the 3D surface atomic structure for general 3D nanomaterials still remains elusive. Here we demonstrate the measurement of 3D atomic structure at 15 pm precision using a Pt nanoparticle as a model system. Aided by a deep learning-based missing data retrieval combined with atomic electron tomography, the surface atomic structure was reliably measured. We found that <\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$100$$\end{document}100> and <\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$111$$\end{document}111> facets contribute differently to the surface strain, resulting in anisotropic strain distribution as well as compressive support boundary effect. The capability of single-atom level surface characterization will not only deepen our understanding of the functional properties of nanomaterials but also open a new door for fine tailoring of their performance.

Precise determination of surface atomic structure of metallic nanoparticles is key to unlock their surface/interface properties. Here the authors introduce a neural network-assisted atomic electron tomography approach that provides a three-dimensional reconstruction of metallic nanoparticles at individual atom level.

Lanthanide-Based Nanosensors: Refining Nanoparticle Responsiveness for Single Particle Imaging of Stimuli

Lanthanide nanoparticles (LNPs) are promising sensors of chemical, mechanical, and temperature changes; they combine the narrow-spectral emission and long-lived excited states of individual lanthanide ions with the high spatial resolution and controlled energy transfer of nanocrystalline architectures. Despite considerable progress in optimizing LNP brightness and responsiveness for dynamic sensing, detection of stimuli with a spatial resolution approaching that of individual nanoparticles remains an outstanding challenge. Here, we highlight the existing capabilities and outstanding challenges of LNP sensors, en-route to nanometer-scale, single particle sensor resolution. First, we summarize LNP sensor read-outs, including changes in emission wavelength, lifetime, intensity, and spectral ratiometric values that arise from modified energy transfer networks within nanoparticles. Then, we describe the origins of LNP sensor imprecision, including sensitivity to competing conditions, interparticle heterogeneities, such as the concentration and distribution of dopant ions, and measurement noise. Motivated by these sources of signal variance, we describe synthesis characterization feedback loops to inform and improve sensor precision, and introduce noise-equivalent sensitivity as a figure of merit of LNP sensors. Finally, we project the magnitudes of chemical and pressure stimulus resolution achievable with single LNPs at nanoscale resolution. Our perspective provides a roadmap for translating ensemble LNP sensing capabilities to the single particle level, enabling nanometer-scale sensing in biology, medicine, and sustainability.

Topology of transition metal dichalcogenides: the case of the core-shell architecture

Non-planar architectures of the traditionally flat 2D materials are emerging as an intriguing paradigm to realize nascent properties within the family of transition metal dichalcogenides (TMDs). These non-planar forms encompass a diversity of curvatures, morphologies, and overall 3D architectures that exhibit unusual characteristics across the hierarchy of length-scales. Topology offers an integrated and unified approach to describe, harness, and eventually tailor non-planar architectures through both local and higher order geometry. Topological design of layered materials intrinsically invokes elements highly relevant to property manipulation in TMDs, such as the origin of strain and its accommodation by defects and interfaces, which have broad implications for improved material design. In this review, we discuss the importance and impact of geometry on the structure and properties of TMDs. We present a generalized geometric framework to classify and relate the diversity of possible non-planar TMD forms. We then examine the nature of curvature in the emerging core-shell architecture, which has attracted high interest due to its versatility and design potential. We consider the local structure of curved TMDs, including defect formation, strain, and crystal growth dynamics, and factors affecting the morphology of core-shell structures, such as synthesis conditions and substrate morphology. We conclude by discussing unique aspects of TMD architectures that can be leveraged to engineer targeted, exotic properties and detail how advanced characterization tools enable detection of these features. Varying the topology of nanomaterials has long served as a potent methodology to engineer unusual and exotic properties, and the time is ripe to apply topological design principles to TMDs to drive future nanotechnology innovation.

Using Atom Dynamics to Map the Defect Structure Around an Impurity in Nano-Hematite

The bulk behavior of materials is often controlled by minor impurities that create nonperiodic localized defect structures due to ionic size, symmetry, and charge balance mismatches. Here, we used transmission electron microscopy (TEM) of atom-resolved dynamics to directly map the topology of Fe vacancy clusters surrounding structurally incorporated U⁶⁺ in nanohematite (α-Fe₂O₃). Ab initio molecular dynamic simulations provided additional independent constraints on coupled U, Fe, and vacancy mobility in the solid. A clearer understanding of how such an apparently incompatible element can be accommodated by hematite emerged. The results were readily interpretable without the need for sophisticated data reconstruction methods, model structures, or ultrathin samples, and with the proliferation of aberration-corrected TEM facilities, the approach is accessible. Given sufficient z-contrast, the ability to observe impurity-vacancy structures by means of atom hopping can be used to directly probe the association of impurities and such defects in other materials, with promising applications across a broad range of disciplines.

Correlating the three-dimensional atomic defects and electronic properties of two-dimensional transition metal dichalcogenides

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.

Interpretable molecular models for molybdenum disulfide and insight into selective peptide recognition

Molybdenum disulfide (MoS2) is a layered material with outstanding electrical and optical properties. Numerous studies evaluate the performance in sensors, catalysts, batteries, and composites that can benefit from guidance by simulations in all-atom resolution. However, molecular simulations remain difficult due to lack of reliable models. We introduce an interpretable force field for MoS2 with record performance that reproduces structural, interfacial, and mechanical properties in 0.1% to 5% agreement with experiments. The model overcomes structural instability, deviations in interfacial and mechanical properties by several 100%, and empirical fitting protocols in earlier models. It is compatible with several force fields for molecular dynamics simulation, including the interface force field (IFF), CVFF, DREIDING, PCFF, COMPASS, CHARMM, AMBER, and OPLS-AA. The parameters capture polar covalent bonding, X-ray structure, cleavage energy, infrared spectra, bending stability, bulk modulus, Young's modulus, and contact angles with polar and nonpolar solvents. We utilized the models to uncover the binding mechanism of peptides to the MoS2 basal plane. The binding strength of several 7mer and 8mer peptides scales linearly with surface contact and replacement of surface-bound water molecules, and is tunable in a wide range from -86 to -6 kcal mol-1. The binding selectivity is multifactorial, including major contributions by van-der-Waals coordination and charge matching of certain side groups, orientation of hydrophilic side chains towards water, and conformation flexibility. We explain the relative attraction and role of the 20 amino acids using computational and experimental data. The force field can be used to screen and interpret the assembly of MoS2-based nanomaterials and electrolyte interfaces up to a billion atoms with high accuracy, including multiscale simulations from the quantum scale to the microscale.

Electron tomography imaging methods with diffraction contrast for materials research

Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable the visualization of three-dimensional (3D) microstructures ranging from atomic to micrometer scales using 3D reconstruction techniques based on computed tomography algorithms. This 3D microscopy method is called electron tomography (ET) and has been utilized in the fields of materials science and engineering for more than two decades. Although atomic resolution is one of the current topics in ET research, the development and deployment of intermediate-resolution (non-atomic-resolution) ET imaging methods have garnered considerable attention from researchers. This research trend is probably not irrelevant due to the fact that the spatial resolution and functionality of 3D imaging methods of scanning electron microscopy (SEM) and X-ray microscopy have come to overlap with those of ET. In other words, there may be multiple ways to carry out 3D visualization using different microscopy methods for nanometer-scale objects in materials. From the above standpoint, this review paper aims to (i) describe the current status and issues of intermediate-resolution ET with regard to enhancing the effectiveness of TEM/STEM imaging and (ii) discuss promising applications of state-of-the-art intermediate-resolution ET for materials research with a particular focus on diffraction contrast ET for crystalline microstructures (superlattice domains and dislocations) including a demonstration of in situ dislocation tomography.

Critical differences in 3D atomic structure of individual ligand-protected nanocrystals in solution

Precise three-dimensional (3D) atomic structure determination of individual nanocrystals is a prerequisite for understanding and predicting their physical properties. Nanocrystals from the same synthesis batch display what are often presumed to be small but possibly important differences in size, lattice distortions, and defects, which can only be understood by structural characterization with high spatial 3D resolution. We solved the structures of individual colloidal platinum nanocrystals by developing atomic-resolution 3D liquid-cell electron microscopy to reveal critical intrinsic heterogeneity of ligand-protected platinum nanocrystals in solution, including structural degeneracies, lattice parameter deviations, internal defects, and strain. These differences in structure lead to substantial contributions to free energies, consequential enough that they must be considered in any discussion of fundamental nanocrystal properties or applications.