Atomic-resolution Microscopy Research Articles

On‐Chip Synthesis of Quasi‐2D Semimetals from Multi‐Layer Chalcogenides

AbstractReducing the dimensions of materials from three to two, or quasi‐two, provides a fertile platform for exploring emergent quantum phenomena and developing next‐generation electronic devices. However, growing high‐quality, ultrathin, quasi2D materials in a templated fashion on an arbitrary substrate is challenging. Here, the study demonstrates a simple and reproducible on‐chip approach for synthesizing non‐layered, nanometer‐thick, quasi‐2D semimetals. In one implementation, this method starts with thin semiconducting InSe flakes of below 20 nm in thickness with nickel deposited on top, followed by a low‐temperature annealing step that results in a controlled transformation of the layered InSe to a non‐layered, crystalline semimetal via reaction with the laterally diffusing nickel. Atomic resolution microscopy reveals the transformed semimetal to be Ni3In2Se2 with a Kagome‐lattice structure. Moreover, it is demonstrated that this synthesis method is generalizable by transforming 2D layered chalcogenides such as SnS and SnSe employing Ni and Co to non‐layered semimetals, paving the way for engineering novel types of devices.

Mineralogical characterization of magnesium-based nanoparticles recovered from a swirl-stabilized magnesium flame by analytical and scanning/transmission electron microscopy

Abstract. The current climate emergency and the related energy transition require the development of technology producing zero-carbon energy. One viable option entails the utilization of recyclable metal fuels. The primary energy stored by the reduction in metal oxides can be transported and later released by metal combustion. Mg is among the most promising metal as a regenerable energetic vector, having an energy density of 25 MJ kg−1. The exploitation of the Mg oxidation and reduction loop has recently been demonstrated, and the loop combustion products are made of metal oxides. The mineralogical characterization of the MgO crystals generated by the Mg combustion is of utter importance for the optimization of the particle trapping capacity in the combustion system during the closed oxidation and reduction loop. In this paper we characterize MgO particles generated in a swirl-stabilized Mg flame by using powder X-ray diffraction, transmission electron microscopy and selected area electron diffraction, and atomic-resolution microscopy combined with energy-dispersive X-ray spectroscopy and dual-electron energy-loss spectroscopy. The MgO combustion products were chemically homogeneous at this level of investigation. Three representative morphologies (cubic, truncated octahedron, and spherical) and two isostructural phases were identified in the MgO combustion product. These findings may contribute to the optimization of system development, particularly in terms of the collection efficiency of the combustion end product.

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.

Nitrogen Pretreatment of Growth Substrates for Vacancy-Saturated MoS2.

Two-dimensional transition-metal dichalcogenides (2D TMDCs) are considered promising materials for optoelectronics due to their unique optical and electric properties. However, their potential has been limited by the occurrence of atomic vacancies during synthesis. While post-treatment processes have demonstrated the passivation of such vacancies, they increase process complexity and affect the TMDC's quality. We here introduce the concept of pretreatment as a facile and powerful route to solve the problem of vacancies in MoS2. Low-temperature nitridation of the sapphire substrate prior to growth provides a nondestructive method to MoS2 modification without introducing new processing steps or increasing the thermal budget. Spectroscopic characterization and atomic-resolution microscopy reveal the incorporation of nitrogen from the sapphire surface layer into chalcogen vacancies. The resulting MoS2 with nitrogen-saturated defects shows a decrease in midgap states and more intrinsic doping as confirmed by ab initio calculations and optoelectronic measurements. The demonstrated pretreatment method opens up new routes toward future, high-performance 2D electronics, as evidenced by a 3-fold reduction in contact resistance and a 10-fold improved performance of 2D photodetectors.

Bonding-Driven Crystallization of Dimensionally Resolved Nanostructures Based on Quasi-1D Van Der Waals Building Blocks

The discovery of complex phenomena and strongly correlated behavior in the solid state has incessantly relied upon the creation of stable low-dimensional lattices approaching the atomic limit. Whereas 2D van der Waals (vdW) materials with atomic scale thicknesses have gained widespread interest, very little has been known about the chemistry and physics of their more confined 1D counterparts in the solid state. In these length scales and dimensionalities, unique physical properties arising from finite size effects such as ballistic electrical transport, size-dependent optical resonance modes, long carrier lifetimes, and exotic higher-order topological states become realizable. To this end, I will present the recent efforts in my group towards elucidating the chemical bonding interactions which define the structure and nanoscale dimensionality of structures derived from lattices which are comprised of 1D chains with sub-nm diameters that are held together by weak vdW interactions. By gaining anisotropy-driven control over these interactions via bottom-up chemical vapor growth, we demonstrate the creation of dimensionally-resolved nanostructures with various thicknesses ranging from 1D nanowire bundles to quasi-2D nanoribbons and nanosheets, all based on a the same 1D vdW lattice motif. Extensive electron diffraction and atomic-resolution microscopy of these resulting nanostructures reveal the strong dependence of the size and dimensionality of the 1D and quasi-2D nanostructures on anisotropic inter-chain vdW bonding interactions, precursor ratios, and growth temperatures. Using these results, we propose a crystallization mechanism defined by the competition between covalent and vdW bonding interactions and epitaxy. As physical properties directly correlate to the structure, dimensionality, and size in the solid state, I will also talk about how the unique topographies of resulting freestanding nanostructures dictate their electronic properties. I will describe how the synthetic control over the structural attributes led to our discovery of emergent properties such as the elusive indirect-to-direct band gap transition and higher-order topological states in 1D vdW nanostructures. Through these efforts, we define for the first time the anisotropy-driven growth of these emergent 1D vdW-derived nanostructures and how nanoscale morphologies in these nanostructures dictate their electronic structures. Altogether, this precise control over crystalline and electronic structure poises these emergent low-dimensional solids as building blocks towards programmable electrocatalysts, densified electronic and quantum devices in sensing, photonic, energy storage and conversion, and spintronic technologies.

Ultra-small gold particles via Citrus × sinensis: Theoretical and experimental SERS study

In this study, we have addressed the green synthesis of sub-nanostructured gold species using Citrus × sinensis. Absorption bands in the ultraviolet region (338 nm) were observed. Analysis by atomic resolution microscopy revealed the identification of sub-nanostructured Au species with particle sizes of about 0.9 nm. With favorable results, these systems were tested as substrates for surface-enhanced Raman spectroscopy (SERS) using pyridine. The chemical enhancement mechanism was studied as the source of the SERS effect. Complementarily, the interaction between gold clusters (Au2n, with n = 1–5) and pyridine was modeled using Density Functional at the Becke-3-parameter-Lee-Yang-Parr level of approximation in combination with the LANL2DZ basis set. A correlation between the adsorption energy and the SERS enhancement factor was analyzed as a function of the Au-N interaction distance.

On the role of interfacial segregation on graphite shape in cast irons

Understanding spheroidal graphite growth in cast irons is a long standing problem for which several mechanisms have been proposed. During the last decade, observations using transmission electron microscopy added new information about the stacking of graphite layers, leading eventually to propose other mechanisms than previously thought of such as repeated 2D-nucleation of new growth blocks and their lateral extension at the surface of the spheroids. Furthermore, it has been recently realized that elements known to strongly affect graphite shape are also those that are surface active. This is illustrated here in the case of antimony which is known to lead to spheroidal graphite degeneration when added at some tens of ppm. Using atomic resolution microscopy, segregation of antimony could be evidenced at the graphite/matrix interface of both spheroids and protuberances. This strongly suggests that accumulation of antimony repelled magnesium from the graphite surface until growth of spiky protuberances replaced spheroidal growth.

Quenching-Induced Defects Liberate the Latent Reversible Capacity of Lithium Titanate Anode.

Interest in defect engineering for lithium-ion battery (LIB) materials is sparked by its ability to tailor electrical conductivity and introduce extra active sites for electrochemical reactions. However, harvesting excessive intrinsic defects in the bulk of the electrodes rather than near their surface remains a long-standing challenge. Here, a versatile strategy of quenching is demonstrated, which is exercised in lithium titanate (Li4 Ti5 O12 , LTO), a renowned anode for LIBs, to achieve off-stoichiometry in the interior region. In situ synchrotron analysis and atomic-resolution microscopy reveal the enriched oxygen vacancies and cation redistribution after ice-water quenching, which can facilitate the native unextractable Li ions to participate in reversible cycling. The fabricated LTO anode delivers a sustained capacity of 202 mAh g-1 in the 1.0-2.5V range with excellent rate capability and overcomes the poor cycling stability seen in conventional defective electrodes. The feasibility of tuning the degree of structural defectiveness via quenching agents is also proven, which can open up an intriguing avenue of research to harness the intrinsic defects for improving the energy density of rechargeable batteries.

Atomic-scale characterization of structural damage and recovery in Sn ion-implanted β-Ga2O3

β-Ga2O3 is an emerging ultra-wide bandgap semiconductor, holding a tremendous potential for power-switching devices for next-generation high power electronics. The performance of such devices strongly relies on the precise control of electrical properties of β-Ga2O3, which can be achieved by implantation of dopant ions. However, a detailed understanding of the impact of ion implantation on the structure of β-Ga2O3 remains elusive. Here, using aberration-corrected scanning transmission electron microscopy, we investigate the nature of structural damage in ion-implanted β-Ga2O3 and its recovery upon heat treatment with the atomic-scale spatial resolution. We reveal that upon Sn ion implantation, Ga2O3 films undergo a phase transformation from the monoclinic β-phase to the defective cubic spinel γ-phase, which contains high-density antiphase boundaries. Using the planar defect models proposed for the γ-Al2O3, which has the same space group as β-Ga2O3, and atomic-resolution microscopy images, we identify that the observed antiphase boundaries are the {100}1/4 ⟨110⟩ type in cubic structure. We show that post-implantation annealing at 1100 °C under the N2 atmosphere effectively recovers the β-phase; however, nano-sized voids retained within the β-phase structure and a γ-phase surface layer are identified as remanent damage. Our results offer an atomic-scale insight into the structural evolution of β-Ga2O3 under ion implantation and high-temperature annealing, which is key to the optimization of semiconductor processing conditions for relevant device design and the theoretical understanding of defect formation and phase stability.

Irradiation-induced grain boundary facet motion: In situ observations and atomic-scale mechanisms.

Metals subjected to irradiation environments undergo microstructural evolution and concomitant degradation, yet the nanoscale mechanisms for such evolution remain elusive. Here, we combine in situ heavy ion irradiation, atomic resolution microscopy, and atomistic simulation to elucidate how radiation damage and interfacial defects interplay to control grain boundary (GB) motion. While classical notions of boundary evolution under irradiation rest on simple ideas of curvature-driven motion, the reality is far more complex. Focusing on an ion-irradiated Pt Σ3 GB, we show how this boundary evolves by the motion of 120° facet junctions separating nanoscale {112} facets. Our analysis considers the short- and mid-range ion interactions, which roughen the facets and induce local motion, and longer-range interactions associated with interfacial disconnections, which accommodate the intergranular misorientation. We suggest how climb of these disconnections could drive coordinated facet junction motion. These findings emphasize that both local and longer-range, collective interactions are important to understanding irradiation-induced interfacial evolution.

Transient Solid-State Laser Activation of Indium for High-Performance Reduction of CO2 to Formate.

Deficiencies in understanding the local environment of active sites and limited synthetic skills challenge the delivery of industrially-relevant current densities with low overpotentials and high selectivity for CO2 reduction. Here, a transient laser induction of metal salts can stimulate extreme conditions and rapid kinetics to produce defect-rich indium nanoparticles (L-In) is reported. Atomic-resolution microscopy and X-ray absorption disclose the highly defective and undercoordinated local environment in L-In. In a flow cell, L-In shows a very small onset overpotential of ≈92mV and delivers a current density of ≈360mA cm-2 with a formate Faradaic efficiency of 98% at a low potential of -0.62V versus RHE. The formation rate of formate reaches up to 6364.4µmol h-1 , which is nearly 39 folds higher than that of commercial In (160.7µmol h-1 ), outperforming most of the previous results that have been reported under KHCO3 environments. Density function theory calculations suggest that the defects facilitate the formation of *OCHO intermediate and stabilize the *HCOOH while inhibiting hydrogen adsorption. This study suggests that transient solid-state laser induction provides a facile and cost-effective approach to form ligand-free and defect-rich materials with tailored activities.

Learning motifs and their hierarchies in atomic resolution microscopy.

Characterizing materials to atomic resolution and first-principles structure-property prediction are two pillars for accelerating functional materials discovery. However, we are still lacking a rapid, noise-robust framework to extract multilevel atomic structural motifs from complex materials to complement, inform, and guide our first-principles models. Here, we present a machine learning framework that rapidly extracts a hierarchy of complex structural motifs from atomically resolved images. We demonstrate how such motif hierarchies can rapidly reconstruct specimens with various defects. ing complex specimens with simplified motifs enabled us to discover a previously unidentified structure in a Mo─V─Te─Nb polyoxometalate (POM) and quantify the relative disorder in a twisted bilayer MoS2. In addition, these motif hierarchies provide statistically grounded clues about the favored and frustrated pathways during self-assembly. The motifs and their hierarchies in our framework coarse-grain disorder in a manner that allows us to understand a much broader range of multiscale samples with functional imperfections and nontrivial topological phases.

Ingrained: An Automated Framework for Fusing Atomic-Scale Image Simulations into Experiments.

To fully leverage the power of image simulation to corroborate and explain patterns and structures in atomic resolution microscopy, an initial correspondence between the simulation and experimental image must be established at the outset of further high accuracy simulations or calculations. Furthermore, if simulation is to be used in context of highly automated processes or high-throughput optimization, the process of finding this correspondence itself must be automated. In this work, "ingrained," an open-source automation framework which solves for this correspondence and fuses atomic resolution image simulations into the experimental images to which they correspond, is introduced. Herein, the overall "ingrained" workflow, focusing on its application to interface structure approximations, and the development of an experimentally rationalized forward model for scanning tunneling microscopy simulation aredescribed.

Direct observation of zonal dislocation in complex materials by atomic-resolution scanning transmission electron microscopy

Dislocation glide to carry plastic deformation in simple metals and alloys is a well-understood process, but the process in materials with complex crystal structures is not yet understood completely as it can be very complicated often involving multiple atomic planes during dislocation glide. The zonal dislocation is one of the examples predicted to operate in complex materials, and during glide it involves multiple atomic planes called shear zone, in which non-uniform atom shuffling occurs. We report direct observation made by Z-contrast atomic-resolution microscopy of the zonal dislocation in the σ phase FeCr. The result confirms the zonal dislocation indeed operates in this material. Knowledge gained on the dislocation core structure will lead to improved understanding of deformation mechanisms in this and other complex crystal structures and provide ways to improve the brittleness of these complex materials.

Evolution of the Interfacial Layer and Its Impact on Electric-Field-Cycling Behaviors in Ferroelectric Hf1-xZrxO2.

Doped HfO2 thin films, which exhibit robust ferroelectricity even with aggressive thickness scaling, could potentially enable ultralow-power logic and memory devices. The ferroelectric properties of such materials are strongly intertwined with the voltage-cycling-induced electrical and structural changes, leading to wake-up and fatigue effects. Such field-cycling-dependent behaviors are crucial to evaluate the reliability of HfO2-based functional devices; however, its genuine nature remains elusive. Herein, we demonstrate the coupling mechanism between the dynamic change of the interfacial layer and wake-up/fatigue phenomena in ferroelectric Hf1-xZrxO2 (HZO) thin films. Comprehensive atomic-resolution microscopy studies have revealed that the interfacial layer between the HZO and neighboring nonoxide electrode experienced a thickness/composition evolution during electrical cycling. Two theoretical models associated with the depolarization field are adopted, giving consistent results with the thickening of the interfacial layer during electrical cycling. Furthermore, we found that the electrical properties of the HZO devices can be manipulated by controlling the interface properties, e.g., through the choice of electrode match and hybrid cycling process. Our results unambiguously reveal the relationship between the interfacial layer and field-cycling behaviors in HZO, which would further permit the reliability improvement in HZO-based ferroelectric devices through interface engineering.

Site-selective doping mechanisms for the enhanced photocatalytic activity of tin oxide nanoparticles

The addition of transition metal dopants into metal oxide nanoparticles (MO NPs) is an universal strategy to engineer the electronic and chemical properties of NPs. Although doping phenomena strongly rely on interactions with compositional and electronic degrees of freedom, fully understanding the site-specific doping behavior in the lattice framework of MO NP on atomic scale remains challenging. Here, we directly resolve the atomic site-selective (substitutional or interstitial) doping behaviors of Cr and Fe in SnO2, revealing their different roles in photocatalytic activities. Atomic-resolution microscopy combined with spectroscopy reveals two contrasting doping behaviors: Cr3+ substitutes for Sn4+ associated with the formation of oxygen vacancies, whereas Fe3+ occupies interstitial sites accompanied by lattice strain. Theoretical calculations indicate that substitutional dopant-vacancy cooperation and interstitial dopant-strain coupling can be energetically favorable routes for enhancing catalytic properties. Our results provide fundamental insights into atomic-scale doping mechanisms and engineering strategies for high-performance doped MO NPs.

Segmentation of Static and Dynamic Atomic-Resolution Microscopy Data Sets with Unsupervised Machine Learning Using Local Symmetry Descriptors.

We present an unsupervised machine learning approach for segmentation of static and dynamic atomic-resolution microscopy data sets in the form of images and video sequences. In our approach, we first extract local features via symmetry operations. Subsequent dimension reduction and clustering analysis are performed in feature space to assign pattern labels to each pixel. Furthermore, we propose the stride and upsampling scheme as well as separability analysis to speed up the segmentation process of image sequences. We apply our approach to static atomic-resolution scanning transmission electron microscopy images and video sequences. Our code is released as a python module that can be used as a standalone program or as a plugin to other microscopy packages.

Pinpointing active sites for water splitting

Microscopic defects on a catalyst made of carbon and iron actively drive the hydrogen evolution reaction, one of the key steps in liberating hydrogen from water, according to a study that combines electrochemical analysis with atomic resolution microscopy ( Nat. Catal. 2021, DOI: 10.1038/s41929-021-00682-2 ). If scientists can find catalysts that efficiently split water into hydrogen and oxygen , then the oceans could serve as a nearly limitless supply of clean-burning, carbon-free hydrogen fuel for transportation and other uses. Precious metals work well as catalysts, but they’re expensive. So a team led by Stefano Agnoli and Gaetano Granozzi of the University of Padua examined inexpensive model catalysts consisting of thin films of graphene and iron. Sandwiches made from those films can be highly active electrocatalysts for hydrogen evolution, but how they work is unclear. The researchers used electrochemical scanning tunneling microscopy to examine the films while they mediated the catalytic

Rapid and Large-Area Visualization of Grain Boundaries in MoS2 on SiO2 Using Vapor Hydrofluoric Acid.

Grain boundaries in two-dimensional (2D) material layers have an impact on their electrical, optoelectronic, and mechanical properties. Therefore, the availability of simple large-area characterization approaches that can directly visualize grains and grain boundaries in 2D materials such as molybdenum disulfide (MoS2) is critical. Previous approaches for visualizing grains and grain boundaries in MoS2 are typically based on atomic resolution microscopy or optical imaging techniques (i.e., Raman spectroscopy or photoluminescence), which are complex or limited to the characterization of small, micrometer-sized areas. Here, we show a simple approach for an efficient large-area visualization of the grain boundaries in continuous chemical vapor-deposited films and domains of MoS2 that are grown on a silicon dioxide (SiO2) substrate. In our approach, the MoS2 layer on a SiO2/Si substrate is exposed to vapor hydrofluoric acid (VHF), resulting in the differential etching of SiO2 at the MoS2 grain boundaries and SiO2 underneath the MoS2 grains as a result of VHF diffusing through the defects in the MoS2 layer at the grain boundaries. The location of the grain boundaries can be seen by the resulting SiO2 pattern using optical microscopy, scanning electron microscopy, or Raman spectroscopy. This method allows for a simple and rapid evaluation of grain sizes in 2D material films over large areas, thereby potentially facilitating the optimization of synthesis processes and advancing applications of 2D materials in science and technology.

Halide Perovskites – Optoelectronic and Structural Characterization Methods

Halide Perovskites – Optoelectronic and Structural Characterization Methods