Heptatic liquid quasi-crystals by colloidal lithographic pre-assembly

HYPOTHESIS

We hypothesize that pre-assembled lithographic Brownian seven-fold quasi-crystals (QCs) of colloidal tiles at high densities can exhibit a heptatic liquid quasi-crystal (LQC) phase upon release; such heptatic LQCs can undergo heterogeneous dynamics at different length scales, reflecting the underlying symmetry, corrugation, and hierarchy of local sets of tiles.

EXPERIMENTS

We design, fabricate, and release a seven-fold QC composed of three differently shaped rhombic tiles using the method of lithographically pre-assembled monolayers (litho-PAMs). High resolution optical microscopy enables spatio-temporal particle tracking of Brownian fluctuations of many tiles in a large area over a long time. We develop an edge-proximity tessellation method for analyzing nearest neighboring particles that can be applied to assemblies and dense systems of complex shapes.

FINDINGS

A fluctuating heptatic LQC phase is identified at high tile area fractions. Heterogenous dynamics and order at different length scales indicate diverse, hierarchical motif structures. We show that certain motifs can collectively rotate without any cage breaking, leading to alterations of the local tile-structure reminiscent of phason-flips in atomic QCs; this rotation causes a slow decline in the system's spatial order. We anticipate that edge-proximity tessellation will help elucidate phase transitions of other systems made of diverse building blocks having significant geometrical complexity at multiple length scales.

Evolution of intrinsic defects and ring structures on the surface of fused silica optics after CO2 laser conditioning

Recently and interestingly, experiments show that the CO2 laser conditioning can significantly increase the laser-induced damage threshold (LIDT) of fused silica optics, but its underlying mechanism has not been clearly revealed. This Letter reports the experimental studies on the evolution of the intrinsic point defects and intrinsic ring structures on the surface of fused silica optics under the CO2 laser irradiation. The laser conditioning can effectively reduce the intrinsic defect contents in the surface layer of mechanically processed fused silica. However, the suppression effect of defects can be affected by the initial surface state. If there are micro-cracks on the component surface, the effect of the laser conditioning would be limited. The evolution of the intrinsic ring structures indicate that most of the intrinsic defects tend to recombine as short (Si-O)n ring structures during the laser healing of the micro-fractures. The observed recombination behavior and suppression of the intrinsic defects can help find out the reason for the increase of the LIDT of the fused silica optics.

A multiscale generative model to understand disorder in domain boundaries

A continuing challenge in atomic resolution microscopy is to identify significant structural motifs and their assembly rules in synthesized materials with limited observations. Here, we propose and validate a simple and effective hybrid generative model capable of predicting unseen domain boundaries in a potassium sodium niobate thin film from only a small number of observations, without expensive first-principles calculations or atomistic simulations of domain growth. Our results demonstrate that complicated domain boundary structures spanning 1 to 100 nanometers can arise from simple interpretable local rules played out probabilistically. We also found previously unobserved, significant, tileable boundary motifs that may affect the piezoelectric response of the material system, and evidence that our system creates domain boundaries with the highest configurational entropy. More broadly, our work shows that simple yet interpretable machine learning models could pave the way to describe and understand the nature and origin of disorder in complex materials, therefore improving functional materials design.

Tuning the Sharing Modes and Composition in a Tetrahedral GeX2 (X = S, Se) System via One-Dimensional Confinement

The packing and connectivity of tetrahedral units are central themes in the structural and electronic properties of a host of solids. Here, we report one-dimensional (1D) chains of GeX₂ (X = S or Se) with modification of the tetrahedral connectivity at the single-chain limit. Precise tuning of the edge- and corner-sharing modes between GeX₂ blocks is achieved by diameter-dependent 1D confinement inside a carbon nanotube. Atomic-resolution scanning transmission electron microscopy directly confirms the existence of two distinct types of GeX₂ chains. Density functional theory calculations corroborate the diameter-dependent stability of the system and reveal an intriguing electronic structure that sensitively depends on tetrahedral connectivity and composition. GeS_2(1-x)Se_2x compound chains are also realized, which demonstrate the tunability of the system's semiconducting properties through composition engineering.

Disorder-tuned conductivity in amorphous monolayer carbon

Correlating atomic configurations-specifically, degree of disorder (DOD)-of an amorphous solid with properties is a long-standing riddle in materials science and condensed matter physics, owing to difficulties in determining precise atomic positions in 3D structures1-5. To this end, 2D systems provide insight to the puzzle by allowing straightforward imaging of all atoms6,7. Direct imaging of amorphous monolayer carbon (AMC) grown by laser-assisted depositions has resolved atomic configurations, supporting the modern crystallite view of vitreous solids over random network theory8. Nevertheless, a causal link between atomic-scale structures and macroscopic properties remains elusive. Here we report facile tuning of DOD and electrical conductivity in AMC films by varying growth temperatures. Specifically, the pyrolysis threshold temperature is the key to growing variable-range-hopping conductive AMC with medium-range order (MRO), whereas increasing the temperature by 25 °C results in AMC losing MRO and becoming electrically insulating, with an increase in sheet resistance of 109 times. Beyond visualizing highly distorted nanocrystallites embedded in a continuous random network, atomic-resolution electron microscopy shows the absence/presence of MRO and temperature-dependent densities of nanocrystallites, two order parameters proposed to fully describe DOD. Numerical calculations establish the conductivity diagram as a function of these two parameters, directly linking microstructures to electrical properties. Our work represents an important step towards understanding the structure-property relationship of amorphous materials at the fundamental level and paves the way to electronic devices using 2D amorphous materials.

Deep-Learning Pipeline for Statistical Quantification of Amorphous Two-Dimensional Materials

Aberration-corrected transmission electron microscopy enables imaging of two-dimensional (2D) materials with atomic resolution. However, dissecting the short-range-ordered structures in radiation-sensitive and amorphous 2D materials remains a significant challenge due to low atomic contrast and laborious manual evaluation. Here, we imaged carbon-based 2D materials with strong contrast, which is enabled by chromatic and spherical aberration correction at a low acceleration voltage. By constructing a deep-learning pipeline, atomic registry in amorphous 2D materials can be precisely determined, providing access to a full spectrum of quantitative data sets, including bond length/angle distribution, pair distribution function, and real-space polygon mapping. Accurate segmentation of micropores and surface contamination, together with robustness against background inhomogeneity, guaranteed the quantification validity in complex experimental images. The automated image analysis provides quantitative metrics with high efficiency and throughput, which may shed light on the structural understanding of short-range-ordered structures. In addition, the convolutional neural network can be readily generalized to crystalline materials, allowing for automatic defect identification and strain mapping.

2D honeycomb transformation into dodecagonal quasicrystals driven by electrostatic forces

Dodecagonal oxide quasicrystals are well established as examples of long-range aperiodic order in two dimensions. However, despite investigations by scanning tunneling microscopy (STM), low-energy electron diffraction (LEED), low-energy electron microscopy (LEEM), photoemission spectroscopy as well as density functional theory (DFT), their structure is still controversial. Furthermore, the principles that guide the formation of quasicrystals (QCs) in oxides are elusive since the principles that are known to drive metallic QCs are expected to fail for oxides. Here we demonstrate the solution of the oxide QC structure by synchrotron-radiation based surface x-ray diffraction (SXRD) refinement of its largest-known approximant. The oxide QC formation is forced by large alkaline earth metal atoms and the reduction of their mutual electrostatic repulsion. It drives the n = 6 structure of the 2D Ti₂O₃ honeycomb arrangement via Stone-Wales transformations into an ordered structure with empty n = 4, singly occupied n = 7 and doubly occupied n = 10 rings, as supported by DFT.

Exploring the configurational space of amorphous graphene with machine-learned atomic energies

Two-dimensionally extended amorphous carbon ("amorphous graphene") is a prototype system for disorder in 2D, showing a rich and complex configurational space that is yet to be fully understood. Here we explore the nature of amorphous graphene with an atomistic machine-learning (ML) model. We create structural models by introducing defects into ordered graphene through Monte-Carlo bond switching, defining acceptance criteria using the machine-learned local, atomic energies associated with a defect, as well as the nearest-neighbor (NN) environments. We find that physically meaningful structural models arise from ML atomic energies in this way, ranging from continuous random networks to paracrystalline structures. Our results show that ML atomic energies can be used to guide Monte-Carlo structural searches in principle, and that their predictions of local stability can be linked to short- and medium-range order in amorphous graphene. We expect that the former point will be relevant more generally to the study of amorphous materials, and that the latter has wider implications for the interpretation of ML potential models.

Liquid-like atoms in dense-packed solid glasses

Revealing the microscopic structural and dynamic pictures of glasses is a long-standing challenge for scientists^1,2. Extensive studies on the structure and relaxation dynamics of glasses have constructed the current classical picture^3-5: glasses consist of some 'soft zones' of loosely bound atoms embedded in a tightly bound atomic matrix. Recent experiments have found an additional fast process in the relaxation spectra^6-9, but the underlying physics of this process remains unclear. Here, combining extensive dynamic experiments and computer simulations, we reveal that this fast relaxation is associated with string-like diffusion of liquid-like atoms, which are inherited from the high-temperature liquids. Even at room temperature, some atoms in dense-packed metallic glasses can diffuse just as easily as they would in liquid states, with an experimentally determined viscosity as low as 10⁷ Pa·s. This finding extends our current microscopic picture of glass solids and might help establish the dynamics-property relationship of glasses⁴.

Direct Atomic Observation of Reversible Orientation Switch in Monoatomic-Layered Gold Membrane Conducted by Dynamic Vortex

Controlling the material structure at an atomic scale to tune their physicochemical and nanoengineering properties is a major driving force of nanotechnology. However, manipulating the structural variation in monoatomic-layered metals remains a challenge, hindering the full application of their novel properties. Here, we show by experiments and simulations that a reversible orientation rotation of monoatomic-layered gold membrane embedded in the gold crystal is performed through dynamic vortexing that is comprised of the circular motion of atoms. A pair of dynamic vortices are successively generated and together span the entire gold membrane to accomplish the orientation switch. Density functional theory calculations demonstrate that the gold membrane exhibits a Rashba-type spin splitting, while the spin direction reversibly flips with the switching orientation of the gold membrane. The results provide a conceptual approach for constructing a novel electronic system with monoatomic-layered metals and the reversible spin-flip has inspiring applications for future spintronics.

Optimal acceleration voltage for near-atomic resolution imaging of layer-stacked 2D polymer thin films

Despite superb instrumental resolution in modern transmission electron microscopes (TEM), high-resolution imaging of organic two-dimensional (2D) materials is a formidable task. Here, we present that the appropriate selection of the incident electron energy plays a crucial role in reducing the gap between achievable resolution in the image and the instrumental limit. Among a broad range of electron acceleration voltages (300 kV, 200 kV, 120 kV, and 80 kV) tested, we found that the highest resolution in the HRTEM image is achieved at 120 kV, which is 1.9 Å. In two imine-based 2D polymer thin films, unexpected molecular interstitial defects were unraveled. Their structural nature is identified with the aid of quantum mechanical calculations. Furthermore, the increased image resolution and enhanced image contrast at 120 kV enabled the detection of functional groups at the pore interfaces. The experimental setup has also been employed for an amorphous organic 2D material.

High-resolution imaging of organic 2D materials using transmission electron microscopes is challenging. Here, the authors find the optimal electron acceleration voltage, and demonstrate 1.9 Å resolution, enabling detection of interstitial defects and functional groups in 2D polymer thin films.

Two-Dimensional Ultrathin Silica Films

Two-dimensional (2D) ultrathin silica films have the potential to reach technological importance in electronics and catalysis. Several well-defined 2D-silica structures have been synthesized so far. The silica bilayer represents a 2D material with SiO₂ stoichiometry. It consists of precisely two layers of tetrahedral [SiO₄] building blocks, corner connected via oxygen bridges, thus forming a self-saturated silicon dioxide sheet with a thickness of ∼0.5 nm. Inspired by recent successful preparations and characterizations of these 2D-silica model systems, scientists now can forge novel concepts for realistic systems, particularly by atomic-scale studies with the most powerful and advanced surface science techniques and density functional theory calculations. This Review provides a solid introduction to these recent developments, breakthroughs, and implications on ultrathin 2D-silica films, including their atomic/electronic structures, chemical modifications, atom/molecule adsorptions, and catalytic reactivity properties, which can help to stimulate further investigations and understandings of these fundamentally important 2D materials.

Formation of a two-dimensional oxide via oxidation of a layered material

We investigate the oxidation mechanism of the layered model system GeAs. In situ X-ray photoelectron spectroscopy experiments performed by irradiating an individual flake with synchrotron radiation in the presence of oxygen show that while As leaves the GeAs surface upon oxidation, a Ge-rich ultrathin oxide film is being formed in the topmost layer of the flake. We develop a theoretical model that supports the layer-by-layer oxidation of GeAs, with a logarithmic kinetics. Finally, assuming that the activation energy for the oxidation process changes linearly with coverage, we estimate that the activation energy for As oxidation is almost twice that for Ge at room temperature.

Predicting the failure of two-dimensional silica glasses

Being able to predict the failure of materials based on structural information is a fundamental issue with enormous practical and industrial relevance for the monitoring of devices and components. Thanks to recent advances in deep learning, accurate failure predictions are becoming possible even for strongly disordered solids, but the sheer number of parameters used in the process renders a physical interpretation of the results impossible. Here we address this issue and use machine learning methods to predict the failure of simulated two dimensional silica glasses from their initial undeformed structure. We then exploit Gradient-weighted Class Activation Mapping (Grad-CAM) to build attention maps associated with the predictions, and we demonstrate that these maps are amenable to physical interpretation in terms of topological defects and local potential energies. We show that our predictions can be transferred to samples with different shape or size than those used in training, as well as to experimental images. Our strategy illustrates how artificial neural networks trained with numerical simulation results can provide interpretable predictions of the behavior of experimentally measured structures.

The sheer number of parameters in deep learning makes the physical interpretation of failure predictions in glasses challenging. Here the authors use Grad-CAM to reveal the role of topological defects and local potential energies in failure predictions.

A high-speed variable-temperature ultrahigh vacuum scanning tunneling microscope with spiral scan capabilities

We present the design and development of a variable-temperature high-speed scanning tunneling microscope (STM). The setup consists of a two-chamber ultra-high vacuum system, including a preparation and a main chamber. The preparation chamber is equipped with standard preparation tools for sample cleaning and film growth. The main chamber hosts the STM that is located within a continuous flow cryostat for counter-cooling during high-temperature measurements. The microscope body is compact, rigid, and highly symmetric to ensure vibrational stability and low thermal drift. We designed a hybrid scanner made of two independent tube piezos for slow and fast scanning, respectively. A commercial STM controller is used for slow scanning, while a high-speed Versa Module Eurocard bus system controls fast scanning. Here, we implement non-conventional spiral geometries for high-speed scanning, which consist of smooth sine and cosine signals created by an arbitrary waveform generator. The tip scans in a quasi-constant height mode, where the logarithm of the tunneling current signal can be regarded as roughly proportional to the surface topography. Scan control and data acquisition have been programmed in the experimental physics and industrial control system framework. With the spiral scans, we atomically resolved diffusion processes of oxygen atoms on the Ru(0001) surface and achieved a time resolution of 8.3 ms per frame at different temperatures. Variable-temperature measurements reveal an influence of the temperature on the oxygen diffusion rate.

Tracking the sliding of grain boundaries at the atomic scale

Grain boundaries (GBs) play an important role in the mechanical behavior of polycrystalline materials. Despite decades of investigation, the atomic-scale dynamic processes of GB deformation remain elusive, particularly for the GBs in polycrystals, which are commonly of the asymmetric and general type. We conducted an in situ atomic-resolution study to reveal how sliding-dominant deformation is accomplished at general tilt GBs in platinum bicrystals. We observed either direct atomic-scale sliding along the GB or sliding with atom transfer across the boundary plane. The latter sliding process was mediated by movements of disconnections that enabled the transport of GB atoms, leading to a previously unrecognized mode of coupled GB sliding and atomic plane transfer. These results enable an atomic-scale understanding of how general GBs slide in polycrystalline materials.

Free-standing homochiral 2D monolayers by exfoliation of molecular crystals

Two-dimensional materials with monolayer thickness and extreme aspect ratios are sought for their high surface areas and unusual physicochemical properties¹. Liquid exfoliation is a straightforward and scalable means of accessing such materials², but has been restricted to sheets maintained by strong covalent, coordination or ionic interactions^3-10. The exfoliation of molecular crystals, in which repeat units are held together by weak non-covalent bonding, could generate a greatly expanded range of two-dimensional crystalline materials with diverse surfaces and structural features. However, at first sight, these weak forces would seem incapable of supporting such intrinsically fragile morphologies. Against this expectation, we show here that crystals composed of discrete supramolecular coordination complexes can be exfoliated by sonication to give free-standing monolayers approximately 2.3 nanometres thick with aspect ratios up to approximately 2,500:1, sustained purely by apolar intermolecular interactions. These nanosheets are characterized by atomic force microscopy and high-resolution transmission electron microscopy, confirming their crystallinity. The monolayers possess complex chiral surfaces derived partly from individual supramolecular coordination complex components but also from interactions with neighbours. In this respect, they represent a distinct type of material in which molecular components are all equally exposed to their environment, as if in solution, yet with properties arising from cooperation between molecules, because of crystallinity. This unusual nature is reflected in the molecular recognition properties of the materials, which bind carbohydrates with strongly enhanced enantiodiscrimination relative to individual molecules or bulk three-dimensional crystals.

Phonons as a platform for non-Abelian braiding and its manifestation in layered silicates

Topological phases of matter have revolutionised the fundamental understanding of band theory and hold great promise for next-generation technologies such as low-power electronics or quantum computers. Single-gap topologies have been extensively explored, and a large number of materials have been theoretically proposed and experimentally observed. These ideas have recently been extended to multi-gap topologies with band nodes that carry non-Abelian charges, characterised by invariants that arise by the momentum space braiding of such nodes. However, the constraints placed by the Fermi-Dirac distribution to electronic systems have so far prevented the experimental observation of multi-gap topologies in real materials. Here, we show that multi-gap topologies and the accompanying phase transitions driven by braiding processes can be readily observed in the bosonic phonon spectra of known monolayer silicates. The associated braiding process can be controlled by means of an electric field and epitaxial strain, and involves, for the first time, more than three bands. Finally, we propose that the band inversion processes at the Γ point can be tracked by following the evolution of the Raman spectrum, providing a clear signature for the experimental verification of the band inversion accompanied by the braiding process.

Unconventional grain growth suppression in oxygen-rich metal oxide nanoribbons

Nanograined metal oxides are requisite for diverse applications that use large surface area, such as gas sensors and catalysts. However, nanoscale grains are thermodynamically unstable and tend to coarsen at elevated temperatures. Here, we report effective grain growth suppression in metal oxide nanoribbons annealed at high temperature (900°C) by tuning the metal-to-oxygen ratio and confining the nanoribbons. Despite the high annealing temperatures, the average grain size was maintained at ~6 nm, which also retained their structural integrity. We observe that excess oxygen in amorphous tin oxide nanoribbons prevents merging of small grains during crystallization, leading to suppressed grain growth. As an exemplary application, we demonstrate a gas sensor using grain growth–suppressed tin oxide nanoribbons, which exhibited both high sensitivity and unusual long-term operation stability. Our findings provide a previously unknown pathway to simultaneously achieve high performance and excellent thermal stability in nanograined metal oxide nanostructures.

Glass Dynamics Deep in the Energy Landscape

When a liquid is cooled, progress down the energy landscape is arrested near the glass transition temperature T_g. In principle, lower energy states can be accessed by waiting for further equilibration, but the rough energy landscape of glasses quickly leads to kinetics on geologically slow time scales below T_g. Over the past decade, progress has been made probing deeper into the energy landscape via several techniques. By looking at bulk and surface diffusion, using layered deposition that promotes equilibration, imaging glass surfaces with faster dynamics below T_g, and optically exciting glasses, experiments have moved into a regime of ultrastable, low energy glasses that was difficult to access in the past. At the same time, both simulations and energy landscape theory based on a random first order transition (RFOT) have tackled systems that include surfaces, optical excitation, and interfacial dynamics. Here we review some of the recent experimental work, and how energy landscape theory illuminates glassy dynamics well below the glass transition temperature by making direct connections between configurational entropy, energy landscape barriers, and the resulting dynamics.

Direct observation of atomic-level fractal structure in a metallic glass membrane

Determination and conceptualization of atomic structures of metallic glasses or amorphous alloys remain a grand challenge. Structural models proposed for bulk metallic glasses are still controversial owing to experimental difficulties in directly imaging the atom positions in three-dimensional structures. With the advanced atomic-resolution imaging, here we directly observed the atomic arrangements in atomically thin metallic glassy membranes obtained by vapor deposition. The atomic packing in the amorphous membrane is shown to have a fractal characteristic, with the fractal dimension depending on the atomic density. Locally, the atomic configuration for the metallic glass membrane is composed of many types of polygons with the bonding angles concentrated on 45°-55°. The fractal atomic structure is consistent with the analysis by the percolation theory, and may account for the enhanced relaxation dynamics and the easiness of glass transition as reported for the thin metallic glassy films or glassy surface.

Atomic-Level Structural Engineering of Graphene on a Mesoscopic Scale

Structural engineering is the first step toward changing properties of materials. While this can be at relative ease done for bulk materials, for example, using ion irradiation, similar engineering of 2D materials and other low-dimensional structures remains a challenge. The difficulties range from the preparation of clean and uniform samples to the sensitivity of these structures to the overwhelming task of sample-wide characterization of the subjected modifications at the atomic scale. Here, we overcome these issues using a near ultrahigh vacuum system comprised of an aberration-corrected scanning transmission electron microscope and setups for sample cleaning and manipulation, which are combined with automated atomic-resolution imaging of large sample areas and a convolutional neural network approach for image analysis. This allows us to create and fully characterize atomically clean free-standing graphene with a controlled defect distribution, thus providing the important first step toward atomically tailored two-dimensional materials.

Exploring order parameters and dynamic processes in disordered systems via variational autoencoders

We suggest and implement an approach for the bottom-up description of systems undergoing large-scale structural changes and chemical transformations from dynamic atomically resolved imaging data, where only partial or uncertain data on atomic positions are available. This approach is predicated on the synergy of two concepts, the parsimony of physical descriptors and general rotational invariance of noncrystalline solids, and is implemented using a rotationally invariant extension of the variational autoencoder applied to semantically segmented atom-resolved data seeking the most effective reduced representation for the system that still contains the maximum amount of original information. This approach allowed us to explore the dynamic evolution of electron beam-induced processes in a silicon-doped graphene system, but it can be also applied for a much broader range of atomic scale and mesoscopic phenomena to introduce the bottom-up order parameters and explore their dynamics with time and in response to external stimuli.

Training artificial neural networks for precision orientation and strain mapping using 4D electron diffraction datasets

Techniques for training artificial neural networks (ANNs) and convolutional neural networks (CNNs) using simulated dynamical electron diffraction patterns are described. The premise is based on the following facts. First, given a suitable crystal structure model and scattering potential, electron diffraction patterns can be simulated accurately using dynamical diffraction theory. Secondly, using simulated diffraction patterns as input, ANNs can be trained for the determination of crystal structural properties, such as crystal orientation and local strain. Further, by applying the trained ANNs to four-dimensional diffraction datasets (4D-DD) collected using the scanning electron nanodiffraction (SEND) or 4D scanning transmission electron microscopy (4D-STEM) techniques, the crystal structural properties can be mapped at high spatial resolution. Here, we demonstrate the ANN-enabled possibilities for the analysis of crystal orientation and strain at high precision and benchmark the performance of ANNs and CNNs by comparing with previous methods. A factor of thirty improvement in angular resolution at 0.009˚ (0.16 mrad) for orientation mapping, sensitivity at 0.04% or less for strain mapping, and improvements in computational performance are demonstrated.

Stone-Wales defects preserve hyperuniformity in amorphous two-dimensional networks

Disordered hyperuniformity (DHU) is a recently discovered novel state of many-body systems that possesses vanishing normalized infinite-wavelength density fluctuations similar to a perfect crystal and an amorphous structure like a liquid or glass. Here, we discover a hyperuniformity-preserving topological transformation in two-dimensional (2D) network structures that involves continuous introduction of Stone-Wales (SW) defects. Specifically, the static structure factor [Formula: see text] of the resulting defected networks possesses the scaling [Formula: see text] for small wave number k, where [Formula: see text] monotonically decreases as the SW defect concentration p increases, reaches [Formula: see text] at [Formula: see text], and remains almost flat beyond this p. Our findings have important implications for amorphous 2D materials since the SW defects are well known to capture the salient feature of disorder in these materials. Verified by recently synthesized single-layer amorphous graphene, our network models reveal unique electronic transport mechanisms and mechanical behaviors associated with distinct classes of disorder in 2D materials.

Revealing Spatial Distribution of Al-Coordinated Species in a Phase-Separated Aluminosilicate Glass by STEM-EELS

Structure determination of glass remains an important issue in glass science. The electron microscope with its high spatial resolution and versatile functions has been widely applied to observe phase separation and structural heterogeneity in glass. While elemental analysis such as energy dispersive spectroscopy (EDS) and electron energy loss spectroscopy (EELS) may provide local compositional information with nanometer-scale resolution, structural information in a glass network cannot be directly obtained. Here, a novel way to probe local coordination is employed using electron energy loss fine structure (ELNES) in the scanning transmission electron microscope (STEM). The method is demonstrated in a phase-separated aluminosilicate glass with multiple Al-coordinated species. With the support of ab initio calculation, two exciton-like peaks in the Al L_2,3-edge at around 77 and 80 eV are attributed to 4-fold and 5,6-fold Al excitations, respectively. Mapping of the relative intensity ratio for two peaks in a phase-separated microstructure reveals a heterogeneous distribution of highly coordinated Al species in real space. The finding is in agreement with previous MD simulation that 5- and 6-fold Al species are favored to form in the Al-rich phase. This work has demonstrated that complex network structure within the phase-separated region can now be studied via STEM-EELS.

Deciphering the intrinsic dynamics from the beam-induced atomic motions in oxide glasses

Probing the microscopic slow structural relaxation in oxide glasses by X-ray photon correlation spectroscopy (XPCS) revealed faster than expected dynamics induced by the X-ray illumination. The fast beam-induced dynamics mask true slow structural relaxation in glasses and challenges application of XPCS to probe the atomic dynamics in oxide glasses. Here an approach that allows estimation of the true relaxation time of the sample in the presence of beam-induced dynamics is presented. The method requires two measurements either with different X-ray beam intensities or at different temperatures. Using numerical simulations it is shown that the slowest estimated true relaxation time is limited by the accuracy of the measured relaxation times of the sample. By analyzing the reported microscopic dynamics in SiO₂, GeO₂ and B₂O₃ glasses, it is concluded that the beam-induced dynamics show rich behavior depending on the sample.

Origin of reversible and irreversible atomic-scale rearrangements in a model two-dimensional network glass

In this contribution, we investigate the fundamental mechanism of plasticity in a model two-dimensional network glass. The glass is generated by using a Monte Carlo bond-switching algorithm and subjected to athermal simple shear deformation, followed by subsequent unloading at selected deformation states. This enables us to investigate the topological origin of reversible and irreversible atomic-scale rearrangements. It is shown that some events that are triggered during loading recover during unloading, while some do not. Thus, two kinds of elementary plastic events are observed, which can be linked to the network topology of the model glass.

Tunable Mechanical Property and Structural Transition of Silicon Nitride Nanowires Induced by Focused Ion Beam Irradiation

Tailoring mechanical properties of the nanowire (NW) with intricate composite structure helps to design nanodevices with novel functionalities. Here, we performed in situ tensile deformation electron microscopy for the evaluation of the mechanical properties of the focused ion beam (FIB) irradiated silicon nitride (Si₃N₄) nanowires (NWs). Young's modulus of the FIB-fabricated NWs was mediated between the range of 522 and 65 GPa by modifying the shell thickness of the core-shell structure. The ion-beam-induced amorphization is found to induce the structural transition from an utter crystalline state to a composite NW with an amorphous shell, which results in a brittle-to-ductile transition and an unexpected plastic deformation. These results have practical implications for optimizing nanostructures with the desired mechanical properties, which are of fundamental relevance in designing and fabricating nanomechanical devices.

Deep Learning Enabled Strain Mapping of Single-Atom Defects in Two-Dimensional Transition Metal Dichalcogenides with Sub-Picometer Precision

Two-dimensional (2D) materials offer an ideal platform to study the strain fields induced by individual atomic defects, yet challenges associated with radiation damage have so far limited electron microscopy methods to probe these atomic-scale strain fields. Here, we demonstrate an approach to probe single-atom defects with sub-picometer precision in a monolayer 2D transition metal dichalcogenide, WSe_2-2xTe_2x. We utilize deep learning to mine large data sets of aberration-corrected scanning transmission electron microscopy images to locate and classify point defects. By combining hundreds of images of nominally identical defects, we generate high signal-to-noise class averages which allow us to measure 2D atomic spacings with up to 0.2 pm precision. Our methods reveal that Se vacancies introduce complex, oscillating strain fields in the WSe_2-2xTe_2x lattice that correspond to alternating rings of lattice expansion and contraction. These results indicate the potential impact of computer vision for the development of high-precision electron microscopy methods for beam-sensitive materials.

Nanoengineering Microstructure of Hybrid C-S-H/Silicene Gel

Two-dimensional (2D) materials have been incorporated into calcium silicate hydrate (C-S-H) gel to enhance its mechanical performance for decades, while the modified C-S-H gel exhibits poor toughness, tensile strength, and ductility. In this work, we report a new design strategy and synthesis route to strengthen C-S-H interface by intercalating a silicene sheet of one atom thickness. The hybrid C-S-H/Silicene gel shows superb mechanical properties, with a remarkable enhancement in strength and other functional properties. By using density functional theory (DFT) and molecular dynamics (MD) simulations, we have demonstrated that Si-O bonds between silicene and C-S-H are stable and covalent, and the interaction energy of this bilayer gel nearly doubles by forming a 3D covalent network with a strong bridging effect. Owing to its better crystallinity enrichment and its induced dislocation dissipation mechanism, the hybrid C-S-H/Silicene gel possesses a higher tensile ductility (∼118% average enhancement and ∼228% in the c direction) and a much smaller elastic stiffness (59.04 GPa for average Young's modulus). This work offers an ingenuous route in turning brittle C-S-H gel into a soft gel, which provides opportunities for fabricating ultrahigh performance cementitious materials.

A Silica Bilayer Supported on Ru(0001): Following the Crystalline-to Vitreous Transformation in Real Time with Spectro-microscopy

The crystalline‐to‐vitreous phase transformation of a SiO₂ bilayer supported on Ru(0001) was studied by time‐dependent LEED, local XPS, and DFT calculations. The silica bilayer system has parallels to 3D silica glass and can be used to understand the mechanism of the disorder transition. DFT simulations show that the formation of a Stone–Wales‐type of defect follows a complex mechanism, where the two layers show decoupled behavior in terms of chemical bond rearrangements. The calculated activation energy of the rate‐determining step for the formation of a Stone—Wales‐type of defect (4.3 eV) agrees with the experimental value. Charge transfer between SiO₂ bilayer and Ru(0001) support lowers the activation energy for breaking the Si−O bond compared to the unsupported film. Pre‐exponential factors obtained in UHV and in O₂ atmospheres differ significantly, suggesting that the interfacial ORu underneath the SiO₂ bilayer plays a role on how the disordering propagates within the film.

Disordered hyperuniformity in two-dimensional amorphous silica

Disordered hyperuniformity (DHU) is a recently proposed new state of matter, which has been observed in a variety of classical and quantum many-body systems. DHU systems are characterized by vanishing infinite-wavelength normalized density fluctuations and are endowed with unique novel physical properties. Here, we report the discovery of disordered hyperuniformity in atomic-scale two-dimensional materials, i.e., amorphous silica composed of a single layer of atoms, based on spectral-density analysis of high-resolution transmission electron microscopy images. Moreover, we show via large-scale density functional theory calculations that DHU leads to almost complete closure of the electronic bandgap compared to the crystalline counterpart, making the material effectively a metal. This is in contrast to the conventional wisdom that disorder generally diminishes electronic transport and is due to the unique electron wave localization induced by the topological defects in the DHU state.

Elementary plastic events in amorphous silica

Plastic instabilities in amorphous materials are often studied using idealized models of binary mixtures that do not capture accurately molecular interactions and bonding present in real glasses. Here we study atomic-scale plastic instabilities in a three-dimensional molecular dynamics model of silica glass under quasistatic shear. We identify two distinct types of elementary plastic events, one is a standard quasilocalized atomic rearrangement while the second is a bond-breaking event that is absent in simplified models of fragile glass formers. Our results show that both plastic events can be predicted by a drop of the lowest nonzero eigenvalue of the Hessian matrix that vanishes at a critical strain. Remarkably, we find very high correlation between the associated eigenvectors and the nonaffine displacement fields accompanying the bond-breaking event, predicting the locus of structural failure. Both eigenvectors and nonaffine displacement fields display an Eshelby-like quadrupolar structure for both failure modes, rearrangement, and bond breaking. Our results thus clarify the nature of atomic-scale plastic instabilities in silica glasses, providing useful information for the development of mesoscale models of amorphous plasticity.

Multi-scale dynamics at the glassy silica surface

Silica-based glass is a household name, providing insulation for windows to microelectronics. The debate over the types of motions thought to occur in or on SiO₂ glass well below the glass transition temperature continues. Here, we form glassy silica films by oxidizing the Si(100) surface (from 0.5 to 1.5 nm thick, to allow tunneling). We then employ scanning tunneling microscopy in situ to image and classify these motions at room temperature on a millisecond to hour time scale and 50-pm to 5-nm length scale. We observe two phenomena on different time scales. Within minutes, compact clusters with an average diameter of several SiO₂ glass-forming units (GFUs) hop between a few (mostly two) configurations, hop cooperatively (facilitation), and merge into larger clusters (aging) or split into smaller clusters (rejuvenation). Within seconds, Si-O-Si bridges connect two GFUs within a single cluster flip, providing a vibrational fine structure to the energy landscape. We assign the vibrational fine structure using electronic structure calculations. Calculations also show that our measured barrier height for whole cluster hopping at the glass surface (configurational dynamics) is consistent with the configurational entropy predicted by thermodynamic models of the glass transition and that the vibrational entropy for GFU flipping and configurational entropy for cluster hopping are comparable (on a per GFU basis).

Direct imaging of structural disordering and heterogeneous dynamics of fullerene molecular liquid

Structural rearrangements govern the various properties of disordered systems and visualization of these dynamical processes can provide critical information on structural deformation and phase transformation of the systems. However, direct imaging of individual atoms or molecules in a disordered state is quite challenging. Here, we prepare a model molecular system of C₇₀ molecules on graphene and directly visualize the structural and dynamical evolution using aberration-corrected transmission electron microscopy. E-beam irradiation stimulates dynamics of fullerene molecules, which results in the first-order like structural transformation from the molecular crystal to molecular liquid. The real-time tracking of individual molecules using an automatic molecular identification process elucidates the relaxation behavior of a stretched exponential functional form. Moreover, the directly observed heterogeneous dynamics bear similarity to the dynamical heterogeneity in supercooled liquids near the glass transition. Fullerenes on graphene can serve as a new model system, which allows investigation of molecular dynamics in disordered phases.

Towards quantitative treatment of electron pair distribution function

The pair distribution function (PDF) is a versatile tool to describe the structure of disordered and amorphous materials. Electron PDF (ePDF) uses the advantage of strong scattering of electrons, thus allowing small volumes to be probed and providing unique information on structure variations at the nano-scale. The spectrum of ePDF applications is rather broad: from ceramic to metallic glasses and mineralogical to organic samples. The quantitative interpretation of ePDF relies on knowledge of how structural and instrumental effects contribute to the experimental data. Here, a broad overview is given on the development of ePDF as a structure analysis method and its applications to diverse materials. Then the physical meaning of the PDF is explained and its use is demonstrated with several examples. Special features of electron scattering regarding the PDF calculations are discussed. A quantitative approach to ePDF data treatment is demonstrated using different refinement software programs for a nanocrystalline anatase sample. Finally, a list of available software packages for ePDF calculation is provided.

The destructive spontaneous ingression of tunable silica nanosheets through cancer cell membranes

Beyond conventional therapies, the sharp edge ingress of ‘thin’ silica nanosheets treats cancer via mechanical scalpelling, albeit with limited oxidative stress.

Robust inorganic graphene analogues with atomic level sharp edges have seldom been investigated to decipher the interaction of two-dimensional materials with the cell membrane. Silica nanosheets (NSs) with four different thicknesses between 2.9 nm and 11.1 nm were synthesized by microwave irradiation and these colloidal NSs were able to spontaneously penetrate the cell membrane leaving membrane perforations at their sites of entry. The NS-ingression was most effective with the thinnest NSs, when studied in vitro. The atomistic details of the NS-membrane interaction were revealed by molecular dynamics (MD) simulations, which showed that the extraction of phospholipids was most favored when NSs were oriented vertically with respect to the membrane surface. While the folic acid modified NSs demonstrated a riveting tendency to penetrate the cancer cell membrane, co-modification with doxorubicin (DOX) unexpectedly reduced their capability. Migrating away from a conventional drug delivery approach, here we show that silica NSs can kill cancer cells primarily by mechanical scalpelling. Targeted ingress could be achieved through antibody conjugation on the NSs and thus only cancerous HeLa cells are affected by this treatment, leaving the normal HEK-293 cells intact. This destructive ingress through limited oxidative stress offers a previously unexplored route to treat fatal diseases without the necessity of transporting expensive drugs or radiation therapy, thereby bypassing deleterious side effects on healthy cells.

Chemistry in confined space through the eyes of surface science-2D porous materials

There are a rapidly growing number of studies showing exciting new opportunities in the way confinement effects on surfaces affect the properties of materials and their chemistry. These effects have been observed recently under two-dimensional (2D) van der Waals materials such as a graphene and boron nitride and for the case of supported 2D-porous oxides, including silicates, aluminosilicates and zeolite nanosheets. This review summarizes the current state of the art in this area of research and how confinement effects in 2D systems relate to those found in 3D porous and layered materials. The focus of this review is put in 2D-materials with inherent porosity, such as 2D-porous oxides. An outlook is also given for the future of this exciting emerging area.

In situ tuning of crystallization pathways by electron beam irradiation and heating in amorphous bismuth ferrite films

The sculpting of crystalline materials from amorphous films by electron beam irradiation in transmission electron microscopy (TEM) offers an effective way for fabrication of nanostructure and devices. However, the synthesis of multifunctional complex oxide and related composites for possible device application is difficult to achieve. Here, we show that the crystallization pathways of amorphous bismuth ferrite films could be tuned by controlled electron beam irradiation and in situ heating in TEM. The results show that Bi segregates from amorphous films and then aggregates into crystalline nanoparticles (the particle size can be tuned by electron dose rates) under electron beam irradiation below 100 °C, while Bi2Fe4O9 nanocrystals are observed at boundary areas between quasi-liquid Bi nanoparticles at 300 °C due to the cooperative effect of electron beam irradiation and thermal heating. Moreover, the Bi/Bi2Fe4O9 metal/semiconductor solid state heterostructure with nearly atomically sharp interfaces emerges when cooling down to room temperature. This finding expands the variety of nanostructures synthesized by electron bombardment and offers a new way to fabricate complex architectures and possible functional devices at the nanometer scale with direct in situ TEM observation and monitoring.

Surface microstructure engenders unusual hydrophobicity in phyllosilicates

We present a mechanism of intriguing polar hydrophobicity of a series of naturally formed minerals: their surface cavities can effectively trap water molecules, and the water trapping remarkably disrupts the hydrogen bond interaction among interfacial water and leads to considerable hydrophobicity. Diminishing water trapping by decreasing surface roughness can considerably enhance wettability, which illustrates that a Wenzel model is no longer valid for polar materials with atomic-scale roughness.

Feature extraction via similarity search: application to atom finding and denoising in electron and scanning probe microscopy imaging

We develop an algorithm for feature extraction based on structural similarity and demonstrate its application for atom and pattern finding in high-resolution electron and scanning probe microscopy images. The use of the combined local identifiers formed from an image subset and appended Fourier, or other transform, allows tuning selectivity to specific patterns based on the nature of the recognition task. The proposed algorithm is implemented in Pycroscopy, a community-driven scientific data analysis package, and is accessible through an interactive Jupyter notebook available on GitHub.

Superplastic nanoscale pore shaping by ion irradiation

Exposed to ionizing radiation, nanomaterials often undergo unusual transformations compared to their bulk form. However, atomic-level mechanisms of such transformations are largely unknown. This work visualizes and quantifies nanopore shrinkage in nanoporous alumina subjected to low-energy ion beams in a helium ion microscope. Mass transport in porous alumina is thus simultaneously induced and imaged with nanoscale precision, thereby relating nanoscale interactions to mesoscopic deformations. The interplay between chemical bonds, disorders, and ionization-induced transformations is analyzed. It is found that irradiation-induced diffusion is responsible for mass transport and that the ionization affects mobility of diffusive entities. The extraordinary room temperature superplasticity of the normally brittle alumina is discovered. These findings enable the effective manipulation of chemical bonds and structural order by nanoscale ion-matter interactions to produce mesoscopic structures with nanometer precision, such as ultra-high density arrays of sub-10-nm pores with or without the accompanying controlled plastic deformations.

When nanomaterials are exposed to ionizing radiation, they often sustain mesoscopic changes not seen in their bulk form. Here, the authors use a helium ion microscope to induce and examine transformations in nanoporous alumina, drawing connections between atomic structure and nano- and microscale behavior in materials under irradiation.

The bouncing threshold in silica nanograin collisions

Using molecular dynamics simulations, we study collisions between amorphous silica nanoparticles. Our silica model contains uncontaminated surfaces, that is, the effect of surface hydroxylation or of adsorbed water layers is excluded. For central collisions, we characterize the boundary between sticking and bouncing collisions as a function of impact velocity and particle size and quantify the coefficient of restitution. We show that the traditional Johnson-Kendall-Roberts (JKR) model provides a valid description of the ingoing trajectory of two grains up to the moment of maximum compression. The distance of closest approach is slightly underestimated by the JKR model, due to the appearance of plasticity in the grains, which shows up in the form of localized shear transformation zones. The JKR model strongly underestimates the contact radius and the collision duration during the outgoing trajectory, evidencing that the breaking of covalent bonds during grain separation is not well described by this model. The adhesive neck formed between the two grains finally collapses while creating narrow filaments joining the grains, which eventually tear.