Giant energy storage and power density negative capacitance superlattices.

Dielectric electrostatic capacitors1, because of their ultrafast charge-discharge, are desirable for high-power energy storage applications. Along with ultrafast operation, on-chip integration can enable miniaturized energy storage devices for emerging autonomous microelectronics and microsystems2-5. Moreover, state-of-the-art miniaturized electrochemical energy storage systems-microsupercapacitors and microbatteries-currently face safety, packaging, materials and microfabrication challenges preventing on-chip technological readiness2,3,6, leaving an opportunity for electrostatic microcapacitors. Here we report record-high electrostatic energy storage density (ESD) and power density, to our knowledge, in HfO2-ZrO2-based thin film microcapacitors integrated into silicon, through a three-pronged approach. First, to increase intrinsic energy storage, atomic-layer-deposited antiferroelectric HfO2-ZrO2 films are engineered near a field-driven ferroelectric phase transition to exhibit amplified charge storage by the negative capacitance effect7-12, which enhances volumetric ESD beyond the best-known back-end-of-the-line-compatible dielectrics (115 J cm-3) (ref. 13). Second, to increase total energy storage, antiferroelectric superlattice engineering14 scales the energy storage performance beyond the conventional thickness limitations of HfO2-ZrO2-based (anti)ferroelectricity15 (100-nm regime). Third, to increase the storage per footprint, the superlattices are conformally integrated into three-dimensional capacitors, which boosts the areal ESD nine times and the areal power density 170 times that of the best-known electrostatic capacitors: 80 mJ cm-2 and 300 kW cm-2, respectively. This simultaneous demonstration of ultrahigh energy density and power density overcomes the traditional capacity-speed trade-off across the electrostatic-electrochemical energy storage hierarchy1,16. Furthermore, the integration of ultrahigh-density and ultrafast-charging thin films within a back-end-of-the-line-compatible process enables monolithic integration of on-chip microcapacitors5, which can unlock substantial energy storage and power delivery performance for electronic microsystems17-19.

Ultrathin ferroic HfO2-ZrO2 superlattice gate stack for advanced transistors.

With the scaling of lateral dimensions in advanced transistors, an increased gate capacitance is desirable both to retain the control of the gate electrode over the channel and to reduce the operating voltage1. This led to a fundamental change in the gate stack in 2008, the incorporation of high-dielectric-constant HfO2 (ref. 2), which remains the material of choice to date. Here we report HfO2-ZrO2 superlattice heterostructures as a gate stack, stabilized with mixed ferroelectric-antiferroelectric order, directly integrated onto Si transistors, and scaled down to approximately 20 ångströms, the same gate oxide thickness required for high-performance transistors. The overall equivalent oxide thickness in metal-oxide-semiconductor capacitors is equivalent to an effective SiO2 thickness of approximately 6.5 ångströms. Such a low effective oxide thickness and the resulting large capacitance cannot be achieved in conventional HfO2-based high-dielectric-constant gate stacks without scavenging the interfacial SiO2, which has adverse effects on the electron transport and gate leakage current3. Accordingly, our gate stacks, which do not require such scavenging, provide substantially lower leakage current and no mobility degradation. This work demonstrates that ultrathin ferroic HfO2-ZrO2 multilayers, stabilized with competing ferroelectric-antiferroelectric order in the two-nanometre-thickness regime, provide a path towards advanced gate oxide stacks in electronic devices beyond conventional HfO2-based high-dielectric-constant materials.

Enhanced ferroelectricity in ultrathin films grown directly on silicon.

Ultrathin ferroelectric materials could potentially enable low-power perovskite ferroelectric tetragonality logic and nonvolatile memories1,2. As ferroelectric materials are made thinner, however, the ferroelectricity is usually suppressed. Size effects in ferroelectrics have been thoroughly investigated in perovskite oxides-the archetypal ferroelectric system3. Perovskites, however, have so far proved unsuitable for thickness scaling and integration with modern semiconductor processes4. Here we report ferroelectricity in ultrathin doped hafnium oxide (HfO2), a fluorite-structure oxide grown by atomic layer deposition on silicon. We demonstrate the persistence of inversion symmetry breaking and spontaneous, switchable polarization down to a thickness of one nanometre. Our results indicate not only the absence of a ferroelectric critical thickness but also enhanced polar distortions as film thickness is reduced, unlike in perovskite ferroelectrics. This approach to enhancing ferroelectricity in ultrathin layers could provide a route towards polarization-driven memories and ferroelectric-based advanced transistors. This work shifts the search for the fundamental limits of ferroelectricity to simpler transition-metal oxide systems-that is, from perovskite-derived complex oxides to fluorite-structure binary oxides-in which 'reverse' size effects counterintuitively stabilize polar symmetry in the ultrathin regime.

Publisher Correction: Enhanced ferroelectricity in ultrathin films grown directly on silicon.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Probing Defectivity Beneath the Hydrocarbon Blanket in 2D hBN Using TEM-EELS.

The controlled creation and manipulation of defects in 2D materials has become increasingly popular as a means to design and tune new material functionalities. However, defect characterization by direct atomic-scale imaging is often severely limited by surface contamination due to a blanket of hydrocarbons. Thus, analysis techniques that can characterize atomic-scale defects despite the contamination layer are advantageous. In this work, we take inspiration from X-ray absorption spectroscopy and use broad-beam electron energy loss spectroscopy (EELS) to characterize defect structures in 2D hexagonal boron nitride (hBN) based on averaged fine structure in the boron K-edge. Since EELS is performed in a transmission electron microscope (TEM), imaging can be performed in-situ to assess contamination levels and other factors such as tears in the fragile 2D sheets, which can affect the spectroscopic analysis. We demonstrate the TEM-EELS technique for 2D hBN samples irradiated with different ion types and doses, finding spectral signatures indicative of boron-oxygen bonding that can be used as a measure of sample defectiveness depending on the ion beam treatment. We propose that even in cases where surface contamination has been mitigated, the averaging-based TEM-EELS technique can be useful for efficient sample surveys to support atomically resolved EELS experiments.

The 4D Camera: An 87 kHz Direct Electron Detector for Scanning/Transmission Electron Microscopy.

We describe the development, operation, and application of the 4D Camera-a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ∼480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10-700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

Enhanced Exciton-to-Trion Conversion by Proton Irradiation of Atomically Thin WS2.

Defect engineering of van der Waals semiconductors has been demonstrated as an effective approach to manipulate the structural and functional characteristics toward dynamic device controls, yet correlations between physical properties with defect evolution remain underexplored. Using proton irradiation, we observe an enhanced exciton-to-trion conversion of the atomically thin WS2. The altered excitonic states are closely correlated with nanopore induced atomic displacement, W nanoclusters, and zigzag edge terminations, verified by scanning transmission electron microscopy, photoluminescence, and Raman spectroscopy. Density functional theory calculation suggests that nanopores facilitate formation of in-gap states that act as sinks for free electrons to couple with excitons. The ion energy loss simulation predicts a dominating electron ionization effect upon proton irradiation, providing further evidence on band perturbations and nanopore formation without destroying the overall crystallinity. This study provides a route in tuning the excitonic properties of van der Waals semiconductors using an irradiation-based defect engineering approach.

Steam-Assisted Selective CO2 Hydrogenation to Ethanol over Ru-In Catalysts.

Multicomponent catalysts can be designed to synergistically combine reaction intermediates at interfacial active sites, but restructuring makes systematic control and understanding of such dynamics challenging. We here unveil how reducibility and mobility of indium oxide species in Ru-based catalysts crucially control the direct, selective conversion of CO2 to ethanol. When uncontrolled, reduced indium oxide species occupy the Ru surface, leading to deactivation. With the addition of steam as a mild oxidant and using porous polymer layers to control In mobility, Ru-In2O3 interface sites are stabilized, and ethanol can be produced with superior overall selectivity (70 %, rest CO). Our work highlights how engineering of bifunctional active ensembles enables cooperativity and synergy at tailored interfaces, which unlocks unprecedented performance in heterogeneous catalysts.

EELS Studies of Cerium Electrolyte Reveal Substantial Solute Concentration Effects in Graphene Liquid Cells.

Graphene liquid cell transmission electron microscopy is a powerful technique to visualize nanoscale dynamics and transformations at atomic resolution. However, the solution in liquid cells is known to be affected by radiolysis, and the stochastic formation of graphene liquid cells raises questions about the solution chemistry in individual pockets. In this study, electron energy loss spectroscopy (EELS) was used to evaluate a model encapsulated solution, aqueous CeCl3. First, the ratio between the O K-edge and Ce M-edge was used to approximate the concentration of cerium salt in the graphene liquid cell. It was determined that the ratio between oxygen and cerium was orders of magnitude lower than what is expected for a dilute solution, indicating that the encapsulated solution is highly concentrated. To probe how this affects the chemistry within graphene liquid cells, the oxidation of Ce3+ was measured using time-resolved parallel EELS. It was determined that Ce3+ oxidizes faster under high electron fluxes, but reaches the same steady-state Ce4+ concentration regardless of flux. The time-resolved concentration profiles enabled direct comparison to radiolysis models, which indicate rate constants and g-values of certain molecular species are substantially different in the highly concentrated environment. Finally, electron flux-dependent gold nanocrystal etching trajectories showed that gold nanocrystals etch faster at higher electron fluxes, correlating well with the Ce3+ oxidation kinetics. Understanding the effects of the highly concentrated solution in graphene liquid cells will provide new insight on previous studies and may open up opportunities to systematically study systems in highly concentrated solutions at high resolution.

Templated encapsulation of platinum-based catalysts promotes high-temperature stability to 1,100 °C.

Stable catalysts are essential to address energy and environmental challenges, especially for applications in harsh environments (for example, high temperature, oxidizing atmosphere and steam). In such conditions, supported metal catalysts deactivate due to sintering-a process where initially small nanoparticles grow into larger ones with reduced active surface area-but strategies to stabilize them can lead to decreased performance. Here we report stable catalysts prepared through the encapsulation of platinum nanoparticles inside an alumina framework, which was formed by depositing an alumina precursor within a separately prepared porous organic framework impregnated with platinum nanoparticles. These catalysts do not sinter at 800 °C in the presence of oxygen and steam, conditions in which conventional catalysts sinter to a large extent, while showing similar reaction rates. Extending this approach to Pd-Pt bimetallic catalysts led to the small particle size being maintained at temperatures as high as 1,100 °C in air and 10% steam. This strategy can be broadly applied to other metal and metal oxides for applications where sintering is a major cause of material deactivation.

Deep-Learning Electron Diffractive Imaging.

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

Strain fields in twisted bilayer graphene.

Van der Waals heteroepitaxy allows deterministic control over lattice mismatch or azimuthal orientation between atomic layers to produce long-wavelength superlattices. The resulting electronic phases depend critically on the superlattice periodicity and localized structural deformations that introduce disorder and strain. In this study we used Bragg interferometry to capture atomic displacement fields in twisted bilayer graphene with twist angles <2°. Nanoscale spatial fluctuations in twist angle and uniaxial heterostrain were statistically evaluated, revealing the prevalence of short-range disorder in moiré heterostructures. By quantitatively mapping strain tensor fields, we uncovered two regimes of structural relaxation and disentangled the electronic contributions of constituent rotation modes. Further, we found that applied heterostrain accumulates anisotropically in saddle-point regions, generating distinctive striped strain phases. Our results establish the reconstruction mechanics underpinning the twist-angle-dependent electronic behaviour of twisted bilayer graphene and provide a framework for directly visualizing structural relaxation, disorder and strain in moiré materials.

4D-STEM of Beam-Sensitive Materials.

ConspectusScanning electron nanobeam diffraction, or 4D-STEM (four-dimensional scanning transmission electron microscopy), is a flexible and powerful approach to elucidate structure from "soft" materials that are challenging to image in the transmission electron microscope because their structure is easily damaged by the electron beam. In a 4D-STEM experiment, a converged electron beam is scanned across the sample, and a pixelated camera records a diffraction pattern at each scan position. This four-dimensional data set can be mined for various analyses, producing maps of local crystal orientation, structural distortions, crystallinity, or different structural classes. Holding the sample at cryogenic temperatures minimizes diffusion of radicals and the resulting damage and disorder caused by the electron beam. The total fluence of incident electrons can easily be controlled during 4D-STEM experiments by careful use of the beam blanker, steering of the localized electron dose, and by minimizing the fluence in the convergent beam thus minimizing beam damage. This technique can be applied to both organic and inorganic materials that are known to be beam-sensitive; they can be highly crystalline, semicrystalline, mixed phase, or amorphous.One common example is the case for many organic materials that have a π-π stacking of polymer chains or rings on the order of 3.4-4.2 Å separation. If these chains or rings are aligned in some regions, they will produce distinct diffraction spots (as would other crystalline spacings in this range), though they may be weak or diffuse for disordered or weakly scattering materials. We can reconstruct the orientation of the π-π stacking, the degree of π-π stacking in the sample, and the domain size of the aligned regions. This Account summarizes illumination conditions and experimental parameters for 4D-STEM experiments with the goal of producing images of structural features for materials that are beam-sensitive. We will discuss experimental parameters including sample cooling, probe size and shape, fluence, and cameras. 4D-STEM has been applied to a variety of materials, not only as an advanced technique for model systems, but as a technique for the beginning microscopist to answer materials science questions. It is noteworthy that the experimental data acquisition does not require an aberration-corrected TEM but can be produced on a variety of instruments with the right attention to experimental parameters.

Scattering Matrix Determination in Crystalline Materials from 4D Scanning Transmission Electron Microscopy at a Single Defocus Value.

Recent work has revived interest in the scattering matrix formulation of electron scattering in transmission electron microscopy as a stepping stone toward atomic-resolution structure determination in the presence of multiple scattering. We discuss ways of visualizing the scattering matrix that make its properties clear. Through a simulation-based case study incorporating shot noise, we shown how regularizing on this continuity enables the scattering matrix to be reconstructed from 4D scanning transmission electron microscopy (STEM) measurements from a single defocus value. Intriguingly, for crystalline samples, this process also yields the sample thickness to nanometer accuracy with no a priori knowledge about the sample structure. The reconstruction quality is gauged by using the reconstructed scattering matrix to simulate STEM images at defocus values different from that of the data from which it was reconstructed.

Fast Grain Mapping with Sub-Nanometer Resolution Using 4D-STEM with Grain Classification by Principal Component Analysis and Non-Negative Matrix Factorization.

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D scanning transmission electron microscopy, or 4D-STEM) combined with high-speed direct-electron detection. An electron probe size down to 0.5 nm in diameter is used and the sample investigated is a gold­palladium nanoparticle catalyst. Computational analysis of the 4D-STEM data sets is performed using a disk registration algorithm to identify the diffraction peaks followed by feature learning to map the individual grains. Two unsupervised feature learning techniques are compared: principal component analysis (PCA) and non-negative matrix factorization (NNMF). The characteristics of the PCA versus NNMF output are compared and the potential of the 4D-STEM approach for statistical analysis of grain orientations at high spatial resolution is discussed.

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

Electroreduction of carbon monoxide to liquid fuel on oxide-derived nanocrystalline copper.

The electrochemical conversion of CO2 and H2O into liquid fuel is ideal for high-density renewable energy storage and could provide an incentive for CO2 capture. However, efficient electrocatalysts for reducing CO2 and its derivatives into a desirable fuel are not available at present. Although many catalysts can reduce CO2 to carbon monoxide (CO), liquid fuel synthesis requires that CO is reduced further, using H2O as a H(+) source. Copper (Cu) is the only known material with an appreciable CO electroreduction activity, but in bulk form its efficiency and selectivity for liquid fuel are far too low for practical use. In particular, H2O reduction to H2 outcompetes CO reduction on Cu electrodes unless extreme overpotentials are applied, at which point gaseous hydrocarbons are the major CO reduction products. Here we show that nanocrystalline Cu prepared from Cu2O ('oxide-derived Cu') produces multi-carbon oxygenates (ethanol, acetate and n-propanol) with up to 57% Faraday efficiency at modest potentials (-0.25 volts to -0.5 volts versus the reversible hydrogen electrode) in CO-saturated alkaline H2O. By comparison, when prepared by traditional vapour condensation, Cu nanoparticles with an average crystallite size similar to that of oxide-derived copper produce nearly exclusive H2 (96% Faraday efficiency) under identical conditions. Our results demonstrate the ability to change the intrinsic catalytic properties of Cu for this notoriously difficult reaction by growing interconnected nanocrystallites from the constrained environment of an oxide lattice. The selectivity for oxygenates, with ethanol as the major product, demonstrates the feasibility of a two-step conversion of CO2 to liquid fuel that could be powered by renewable electricity.

Atomic Resolution Imaging of Light Elements in a Crystalline Environment using Dynamic Hollow-Cone Illumination Transmission Electron Microscopy.

Multiple electron scattering and the nonintuitive nature of image formation with coherent radiation complicate the interpretation of conventional transmission electron microscopy images. Precession of the illuminating beam in transmission electron microscopy (TEM) can lead to more robust and interpretable images with some penalty to image contrast, a technique known as dynamic hollow-cone illumination TEM. We demonstrate direct and robust imaging of light and heavy atoms in a crystalline environment with this technique. This method is similar to the annular bright-field technique in scanning transmission electron microscopy, via the principle of reciprocity. Dynamic hollow-cone illumination TEM is challenging in practice due to sensitivity to the misalignment of the precession axis, microscope objective aperture, and crystal zone axis.

Self-Assembly of Two-Dimensional Perovskite Nanosheet Building Blocks into Ordered Ruddlesden-Popper Perovskite Phase.

The self-assembly of nanoparticles, a process whereby nanocrystal building blocks organize into even more ordered superstructures, is of great interest to nanoscience. Here we report the layer-by-layer assembly of 2D perovskite nanosheet building blocks. Structural analysis reveals that the assembled superlattice nanocrystals match with the layered Ruddlesden-Popper perovskite phase. This assembly proves reversible, as these superlattice nanocrystals can be reversibly exfoliated back into their building blocks via sonication. This study demonstrates the opportunity to further understand and exploit thermodynamics to increase order in a system of nanoparticles and to study emergent optical properties of a superlattice from 2D, weakly attracted, perovskite building blocks.

Unravelling surface and interfacial structures of a metal-organic framework by transmission electron microscopy.

Metal-organic frameworks (MOFs) are crystalline porous materials with designable topology, porosity and functionality, having promising applications in gas storage and separation, ion conduction and catalysis. It is challenging to observe MOFs with transmission electron microscopy (TEM) due to the extreme instability of MOFs upon electron beam irradiation. Here, we use a direct-detection electron-counting camera to acquire TEM images of the MOF ZIF-8 with an ultralow dose of 4.1 electrons per square ångström to retain the structural integrity. The obtained image involves structural information transferred up to 2.1 Å, allowing the resolution of individual atomic columns of Zn and organic linkers in the framework. Furthermore, TEM reveals important local structural features of ZIF-8 crystals that cannot be identified by diffraction techniques, including armchair-type surface terminations and coherent interfaces between assembled crystals. These observations allow us to understand how ZIF-8 crystals self-assemble and the subsequent influence of interfacial cavities on mass transport of guest molecules.