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Diffuse intensities in the electron diffraction patterns of concentrated face-centered cubic solid solutions have been widely attributed to chemical short-range order, although this connection has been recently questioned. This article explores the many non-ordering origins of commonly reported features using a combination of experimental electron microscopy and multislice diffraction simulations, which suggest that diffuse intensities largely represent thermal and static displacement scattering. A limited number of observations may reflect additional contributions from planar defects, surface terminations incommensurate with bulk periodicity, or weaker dynamical effects, Comment: 8 pages, 3 figures

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 approximately 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 - 300 keV. Through electron counting, the resulting sparse data sets are reduced in size by 10 - 300x 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 4D-STEM experiments to be accomplished with typical STEM scanning parameters.

In a scanning transmission electron microscope (STEM), producing a high-resolution image generally requires an electron beam focused to the smallest point possible. However, the magnetic lenses used to focus the beam are unavoidably imperfect, introducing aberrations that limit resolution. Modern STEMs overcome this by using hardware aberration correctors comprised of many multipole lenses, but these devices are complex, expensive, and can be difficult to tune. We demonstrate a design for an electrostatic phase plate that can act as an aberration corrector. The corrector is comprised of annular segments, each of which is an independent two-terminal device that can apply a constant or ramped phase shift to a portion of the electron beam. We show the improvement in image resolution using an electrostatic corrector. Engineering criteria impose that much of the beam within the probe-forming aperture be blocked by support bars, leading to large probe tails for the corrected probe that sample the specimen beyond the central lobe. We also show how this device can be used to create other STEM beam profiles such as vortex beams and beams with a high degree of phase diversity, which improve information transfer in ptychographic reconstructions., Comment: 12 pages, 10 figures

We demonstrate a new focused ion beam sample preparation method for atom probe tomography. The key aspect of the new method is that we use a neon ion beam for the final tip-shaping after conventional annulus milling using gallium ions. This dual-ion approach combines the benefits of the faster milling capability of the higher current gallium ion beam with the chemically inert and higher precision milling capability of the noble gas neon ion beam. Using a titanium-aluminum alloy and a layered aluminum/aluminum oxide material as test cases, we show that atom probe tips prepared using the combined gallium and neon ion approach are free from the gallium contamination that typically frustrates composition analysis of these materials due to implantation, diffusion, and embrittlement effects. We propose that by using a focused ion beam from a noble gas species, such as the neon ions demonstrated here, atom probe tomography can be more reliably performed on a larger range of materials than is currently possible using conventional techniques.

Nanobeam electron diffraction can probe local structural properties of complex crystalline materials including phase, orientation, tilt, strain, and polarization. Ideally, each diffraction pattern from a projected area of a few unit cells would produce clear a Bragg diffraction pattern, where the reciprocal lattice vectors can be measured from the spacing of the diffracted spots, and the spot intensities are equal to the square of the structure factor amplitudes. However, many samples are too thick for this simple interpretation of their diffraction patterns, as multiple scattering of the electron beam can produce a highly nonlinear relationship between the spot intensities and the underlying structure. Here, we develop a stacked Bloch wave method to model the diffracted intensities from thick samples with structure that varies along the electron beam. Our method reduces the large parameter space of electron scattering to just a few structural variables per probe position, making it fast enough to apply to very large fields of view. We apply our method to SrTiO$_3$/PbTiO$_3$/SrTiO$_3$ multilayer samples, and successfully disentangle specimen tilt from the mean polarization of the PbTiO$_3$ layers. We elucidate the structure of complex vortex topologies in the PbTiO$_3$ layers, demonstrating the promise of our method to extract material properties from thick samples.

In many concentrated alloys of current interest, the observation of diffuse superlattice intensities by transmission electron microscopy has been attributed to chemical short-range order. We briefly review these findings and comment on the plausibility of widespread interpretations, noting the absence of expected peaks, conflicts with theoretical predictions, and the possibility of alternative explanations., Comment: 5 pages, 3 figures

In ultrafast electron diffraction (UED) experiments, accurate retrieval of time-resolved structural parameters, such as atomic coordinates and thermal displacement parameters, requires an accurate scattering model. Unfortunately, kinematical models are often inaccurate even for relativistic electron probes, especially for dense, oriented single crystals where strong channeling and multiple scattering effects are present. This article introduces and demonstrates dynamical scattering models tailored for quantitative analysis of UED experiments performed on single-crystal films. As a case study, we examine ultrafast laser heating of single-crystal gold films. Comparison of kinematical and dynamical models reveals the strong effects of dynamical scattering within nm-scale films and their dependence on sample topography and probe kinetic energy. Applying to UED experiments on an 11 nm thick film using 750 keV electron probe pulses, the dynamical models provide a tenfold improvement over a comparable kinematical model in matching the measured UED patterns. Also, the retrieved lattice temperature rise is in very good agreement with predictions based on previously measured optical constants of gold, whereas fitting the Debye-Waller factor retrieves values that are more than three times lower. Altogether, these results show the importance of dynamical scattering theory for quantitative analysis of UED and demonstrate models that can be practically applied to single-crystal materials and heterostructures., Comment: 13 pages, 7 figures

C-H bond activation enables the facile synthesis of new chemicals. While C-H activation in short-chain alkanes has been widely investigated, it remains largely unexplored for long-chain organic molecules. Here, we report light-driven C-H activation in complex organic materials mediated by 2D transition metal dichalcogenides (TMDCs) and the resultant solid-state synthesis of luminescent carbon dots in a spatially-resolved fashion. We unravel the efficient H adsorption and a lowered energy barrier of C-C coupling mediated by 2D TMDCs to promote C-H activation. Our results shed light on 2D materials for C-H activation in organic compounds for applications in organic chemistry, environmental remediation, and photonic materials.

Medium- and high-entropy alloys based on the CrCoNi-system have been shown to display outstanding strength, tensile ductility and fracture toughness (damage-tolerance properties), especially at cryogenic temperatures. Here we examine the JIc and (back-calculated) KJIc fracture toughness values of the face-centered cubic, equiatomic CrCoNi and CrMnFeCoNi alloys at 20 K. At flow stress values of ~1.5 GPa, crack-initiation KJIc toughnesses were found to be exceptionally high, respectively 235 and 415 MPa(square-root)m for CrMnFeCoNi and CrCoNi, with the latter displaying a crack-growth toughness Kss exceeding 540 MPa(square-root)m after 2.25 mm of stable cracking, which to our knowledge is the highest such value ever reported. Characterization of the crack-tip regions in CrCoNi by scanning electron and transmission electron microscopy reveal deformation structures at 20 K that are quite distinct from those at higher temperatures and involve heterogeneous nucleation, but restricted growth, of stacking faults and fine nano-twins, together with transformation to the hexagonal closed-packed phase. The coherent interfaces of these features can promote both the arrest and transmission of dislocations to generate respectively strength and ductility which strongly contributes to sustained strain hardening. Indeed, we believe that these nominally single-phase, concentrated solid-solution alloys develop their fracture resistance through a progressive synergy of deformation mechanisms, including dislocation glide, stacking-fault formation, nano-twinning and eventually in situ phase transformation, all of which serve to extend continuous strain hardening which simultaneously elevates strength and ductility (by delaying plastic instability), leading to truly exceptional resistance to fracture., Comment: 31 pages, 10 figures, including Supplementary Information

Corrosion is a ubiquitous failure mode of materials in extreme environments. The more localized it is, the more difficult it is to detect and more deleterious its effects. Often, the progression of localized corrosion is accompanied by the evolution of porosity in materials, creating internal void-structures that facilitate the ingress of the external environment into the interior of the material, further accelerating the internal corrosion. Previously, the dominant morphology of such void-structures has been reported to be either three-dimensional (3D) or two-dimensional (2D). Here, we report a more localized form of corrosion, which we call 1D wormhole corrosion. Using electron tomography, we show multiple examples of this 1D and percolating morphology that manifests a significantly high aspect ratio differentiable from 2D and 3D corrosion. To understand the origin of this mechanism in a Ni-Cr alloy corroded by molten salt, we combined energy-filtered four-dimensional scanning transmission electron microscopy (EF-4D-STEM) and ab initio density functional theory (DFT) calculations to develop a vacancy mapping method with nanometer-resolution, identifying a remarkably high vacancy concentration in the diffusion-induced grain boundary migration (DIGM) zone, up to 100 times the equilibrium value at the melting point. These vacancy supersaturation regions act as the precursors of wormholes, and lead to the asymmetrical growth of voids along GBs. We show that similar 1D penetrating corrosion morphologies could also occur in other materials or corrosion conditions, implying the broad impact of this extremely localized corrosion mechanism. Deciphering the origins of 1D corrosion is an important step towards designing structural materials with enhanced corrosion resistance, and also offers new pathways to create ordered-porous materials for functional applications.

Implementation of a fast, robust, and fully-automated pipeline for crystal structure determination and underlying strain mapping for crystalline materials is important for many technological applications. Scanning electron nanodiffraction offers a procedure for identifying and collecting strain maps with good accuracy and high spatial resolutions. However, the application of this technique is limited, particularly in thick samples where the electron beam can undergo multiple scattering, which introduces signal nonlinearities. Deep learning methods have the potential to invert these complex signals, but previous implementations are often trained only on specific crystal systems or a small subset of the crystal structure and microscope parameter phase space. In this study, we implement a Fourier space, complex-valued deep neural network called FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. We trained the FCU-Net using over 200,000 unique simulated dynamical diffraction patterns which include many different combinations of crystal structures, orientations, thicknesses, microscope parameters, and common experimental artifacts. We evaluated the trained FCU-Net model against simulated and experimental 4D-STEM diffraction datasets, where it substantially out-performs conventional analysis methods. Our simulated diffraction pattern library, implementation of FCU-Net, and trained model weights are freely available in open source repositories, and can be adapted to many different diffraction measurement problems., Comment: 17 pages, 7 figures

Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We therefore have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We test the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets., Comment: 14 pages, 7 figures

In this work we present a detailed structural characterization of Si-4H, a newly discovered bulk form of hexagonal silicon (Si) with potential optoelectronic applications. Using multi-scale imaging, we reveal a hierarchical structure in the morphology of Si-4H obtained from high-pressure synthesis. We demonstrate discrete structural units, platelets, at an intermediate length-scale between the bulk pellets synthesized at high pressures and the flake-like crystallites inferred in previous studies. Direct observation of the platelets reveals their 2D structure, with planar faces spanning hundreds of nanometers to a few micrometers and thicknesses of only tens of nanometers. We separated and dispersed small packets of quasi-single platelets, which enabled us to analyze the crystalline domains within each grain. With this view, we demonstrate that Si-4H platelets represent the smallest crystalline structural units, which can bend at the single-domain level. Our characterization of the quasi-2D, flexible platelets of hexagonal Si-4H and proof of concept that the platelets can be dispersed and manipulated quite simply demonstrate opportunities to design novel optoelectronic and solar devices.

Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (e.g., due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. In this work, we developed a generalizable, physically-constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on Li$_X$FePO$_4$, a technologically-relevant battery positive electrode material. We uncovered the functional form of composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0 $\leq$ X $\leq$ 1), including inside the thermodynamically-unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.

Lithium iron phosphate (LixFePO4), a cathode material used in rechargeable Li-ion batteries, phase separates upon de/lithiation under equilibrium. The interfacial structure and chemistry within these cathode materials affects Li-ion transport, and therefore battery performance. Correlative imaging of LixFePO4 was performed using four-dimensional scanning transmission electron microscopy (4D-STEM), scanning transmission X-ray microscopy (STXM), and X-ray ptychography in order to analyze the local structure and chemistry of the same particle set. Over 50,000 diffraction patterns from 10 particles provided measurements of both structure and chemistry at a nanoscale spatial resolution (16.6-49.5 nm) over wide (several micron) fields-of-view with statistical robustness.LixFePO4 particles at varying stages of delithiation were measured to examine the evolution of structure and chemistry as a function of delithiation. In lithiated and delithiated particles, local variations were observed in the degree of lithiation even while local lattice structures remained comparatively constant, and calculation of linear coefficients of chemical expansion suggest pinning of the lattice structures in these populations. Partially delithiated particles displayed broadly core-shell-like structures, however, with highly variable behavior both locally and per individual particle that exhibited distinctive intermediate regions at the interface between phases, and pockets within the lithiated core that correspond to FePO4 in structure and chemistry.The results provide insight into the LixFePO4 system, subtleties in the scope and applicability of Vegards law (linear lattice parameter-composition behavior) under local versus global measurements, and demonstrate a powerful new combination of experimental and analytical modalities for bridging the crucial gap between local and statistical characterization., Comment: 17 pages, 4 figures

Strain engineering provides an effective way of tailoring the electronic and optoelectronic properties of semiconductor nanomaterials and nanodevices, giving rise to novel functionalities. Here, we present direct experimental evidence of strain-induced modifications of hole mobility in individual GaAs nanowires, using in situ transmission electron microscopy (TEM). The conductivity of the nanowires varied with applied uniaxial tensile stress, showing an initial decrease of ~5-20% up to a stress of 1~ 2 GPa, subsequently increasing up to the elastic limit of the nanowires. This is attributed to a hole mobility variation due to changes in the valence band structure caused by stress and strain. The corresponding lattice strain in the nanowires was quantified by in situ 4D-scanning TEM (STEM) and showed a complex spatial distribution at all stress levels. Meanwhile, a significant red shift of the band gap induced by the stress and strain was unveiled by monochromated electron energy loss spectroscopy.

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 implemented and the sample investigated is a gold-palladium 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.

Twinning in crystalline materials plays an important role in many transformation and deformation processes, where underlying mechanisms can be strongly influenced by the structural, energetic and kinetic properties of associated twin boundaries (TBs). While these properties are well characterized in common cases, the possibility that TBs can display multiple complexions with distinct properties, and phase transitions between them, has not been widely explored, even though such phenomena are established in a few more general grain boundaries. We report experimental findings that {11-24} TBs in titanium display a thick interfacial region with crystalline structure distinct from the bulk. First-principles calculations establish that this complexion is linked to a metastable polymorph of titanium, and exhibits behavior consistent with a solid-state wetting transition with compressive strain, and a first-order structural transition under tension. The findings document rich TB complexion behavior in an elemental metal, with important implications for mechanical behavior and phase-transformation pathways., Comment: 62 Pages, 17 Figures

Quantum sensing and computation can be realized with superconducting microwave circuits. Qubits are engineered quantum systems of capacitors and inductors with non-linear Josephson junctions. They operate in the single-excitation quantum regime, photons of $27 \mu$eV at 6.5 GHz. Quantum coherence is fundamentally limited by materials defects, in particular atomic-scale parasitic two-level systems (TLS) in amorphous dielectrics at circuit interfaces.[1] The electric fields driving oscillating charges in quantum circuits resonantly couple to TLS, producing phase noise and dissipation. We use coplanar niobium-on-silicon superconducting resonators to probe decoherence in quantum circuits. By selectively modifying interface dielectrics, we show that most TLS losses come from the silicon surface oxide, and most non-TLS losses are distributed throughout the niobium surface oxide. Through post-fabrication interface modification we reduced TLS losses by 85% and non-TLS losses by 72%, obtaining record single-photon resonator quality factors above 5 million and approaching a regime where non-TLS losses are dominant. [1]M\"uller, C., Cole, J. H. & Lisenfeld, J. Towards understanding two-level-systems in amorphous solids: insights from quantum circuits. Rep. Prog. Phys. 82, 124501 (2019), Comment: 10 pages, 3 figures, supplemental information 10 pages, 11 figures

One of the primary uses for transmission electron microscopy (TEM) is to measure diffraction pattern images in order to determine a crystal structure and orientation. In nanobeam electron diffraction (NBED) we scan a moderately converged electron probe over the sample to acquire thousands or even millions of sequential diffraction images, a technique that is especially appropriate for polycrystalline samples. However, due to the large Ewald sphere of TEM, excitation of Bragg peaks can be extremely sensitive to sample tilt, varying strongly for even a few degrees of sample tilt for crystalline samples. In this paper, we present multibeam electron diffraction (MBED), where multiple probe forming apertures are used to create mutiple STEM probes, all of which interact with the sample simultaneously. We detail designs for MBED experiments, and a method for using a focused ion beam (FIB) to produce MBED apertures. We show the efficacy of the MBED technique for crystalline orientation mapping using both simulations and proof-of-principle experiments. We also show how the angular information in MBED can be used to perform 3D tomographic reconstruction of samples without needing to tilt or scan the sample multiple times. Finally, we also discuss future opportunities for the MBED method., Comment: 14 pages, 6 figures

Quasi-two-dimensional transition-metal dichalcogenides are a key platform for exploring emergent nanoscale phenomena arising from complex interactions. Access to the underlying degrees-of-freedom on their natural time scales motivates the use of advanced ultrafast probes sensitive to self-organised atomic-scale patterns. Here, we report the first ultrafast investigation of TaTe2, which exhibits unique charge and lattice trimer order characterised by a transition upon cooling from stripe-like chains into a $(3 \times 3)$ superstructure of trimer clusters. Utilising MeV-scale ultrafast electron diffraction, we capture the photo-induced TaTe2 structural dynamics -- exposing a rapid $\approx\!1.4$ ps melting of its low-temperature ordered state followed by recovery via thermalisation into a hot cluster superstructure. Density-functional calculations indicate that the initial quench is triggered by intra-trimer Ta charge transfer which destabilises the clusters, unlike melting of charge density waves in other TaX2 compounds. Our work paves the way for further exploration and ultimately rapid optical and electronic manipulation of trimer superstructures., Comment: Main text and supplementary information: 30 pages, 4 main figures, 24 supplementary figures

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 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, from data wrangling to calibration to analysis to 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 have also implemented 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, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project., Comment: 32 pages, 18 figures

Traditional metallic alloys are mixtures of elements where the atoms of minority species tend to distribute randomly if they are below their solubility limit, or lead to the formation of secondary phases if they are above it. Recently, the concept of medium/high entropy alloys (MEA/HEA) has expanded this view, as these materials are single-phase solid solutions of generally equiatomic mixtures of metallic elements that have been shown to display enhanced mechanical properties. However, the question has remained as to how random these solid solutions actually are, with the influence of chemical short-range order (SRO) suggested in computational simulations but not seen experimentally. Here we report the first direct observation of SRO in the CrCoNi MEA using high resolution and energy-filtered transmission electron microscopy. Increasing amounts of SRO give rise to both higher stacking fault energy and hardness. These discoveries suggest that the degree of chemical ordering at the nanometer scale can be tailored through thermomechanical processing, providing a new avenue for tuning the mechanical properties of MEA/HEAs.

The effects of ionizing radiation on materials often reduce to "bad news." Radiation damage usually leads to detrimental effects such as embrittlement, accelerated creep, phase instability, and radiation-altered corrosion. This last point merits special attention. Elucidating synergies between radiation and corrosion has been one of the most challenging tasks impeding the deployment of advanced reactors, stemming from the combined effects of high temperature, corrosive coolants, and intense particle fluxes. Here we report that proton irradiation significantly and repeatably decelerates intergranular corrosion of Ni-Cr alloys in molten fluoride salt at 650C. We demonstrate this effect by showing that the depth of intergranular voids resulting from Cr leaching into the salt is reduced by the proton irradiation alone. Interstitial defects generated from proton irradiation result in radiation-enhanced diffusion, more rapidly replenishing corrosion-injected vacancies with alloy constituents, thus playing the crucial role in decelerating corrosion. Our results show that in industrially-relevant scenarios irradiation can have a positive impact, challenging our view that radiation damage always results in negative effects., Comment: 4 figures plus one supplementary figure, 11 pages in total

Crystalline symmetries have played a central role in the identification of topological materials. The use of symmetry indicators and band representations have enabled a classification scheme for crystalline topological materials, leading to large scale topological materials discovery. In this work we address whether amorphous topological materials, which lie beyond this classification due to the lack of long-range structural order, exist in the solid state. We study amorphous Bi$_2$Se$_3$ thin films, which show a metallic behavior and an increased bulk resistance. The observed low field magnetoresistance due to weak antilocalization demonstrates a significant number of two dimensional surface conduction channels. Our angle-resolved photoemission spectroscopy data is consistent with a dispersive two-dimensional surface state that crosses the bulk gap. Spin resolved photoemission spectroscopy shows this state has an anti-symmetric spin texture resembling that of the surface state of crystalline Bi$_2$Se$_3$. These experimental results are consistent with theoretical photoemission spectra obtained with an amorphous tight-binding model that utilizes a realistic amorphous structure. This discovery of amorphous materials with topological properties uncovers an overlooked subset of topological matter outside the current classification scheme, enabling a new route to discover materials that can enhance the development of scalable topological devices., Comment: 30 pages, 4 figures

Nanoscale strain mapping by four-dimensional scanning transmission electron microscopy (4D-STEM) relies on determining the precise locations of Bragg-scattered electrons in a sequence of diffraction patterns, a task which is complicated by dynamical scattering, inelastic scattering, and shot noise. These features hinder accurate automated computational detection and position measurement of the diffracted disks, limiting the precision of measurements of local deformation. Here, we investigate the use of patterned probes to improve the precision of strain mapping. We imprint a "bullseye" pattern onto the probe, by using a binary mask in the probe-forming aperture, to improve the robustness of the peak finding algorithm to intensity modulations inside the diffracted disks. We show that this imprinting leads to substantially improved strain-mapping precision at the expense of a slight decrease in spatial resolution. In experiments on an unstrained silicon reference sample, we observe an improvement in strain measurement precision from 2.7% of the reciprocal lattice vectors with standard probes to 0.3% using bullseye probes for a thin sample, and an improvement from 4.7% to 0.8% for a thick sample. We also use multislice simulations to explore how sample thickness and electron dose limit the attainable accuracy and precision for 4D-STEM strain measurements., Comment: 29 pages, 7 figures; revision 1

Changes in lattice structure across sub-regions of protein crystals are challenging to assess when relying on whole crystal measurements. Because of this difficulty, macromolecular structure determination from protein micro and nano crystals requires assumptions of bulk crystallinity and domain block substructure. To evaluate the fidelity of these assumptions in protein nanocrystals we map lattice structure across micron size areas of cryogenically preserved three-dimensional peptide crystals using a nano-focused electron beam. This approach produces diffraction from as few as 1,500 molecules in a crystal, is sensitive to crystal thickness and three-dimensional lattice orientation. Real-space maps reconstructed from unsupervised classification of diffraction patterns across a crystal reveal regions of crystal order/disorder and three-dimensional lattice reorientation on a 20nm scale. The lattice nano-ripples observed in micron-sized macromolecular crystals provide a direct view of their plasticity. Knowledge of these features is a first step to understanding crystalline macromolecular self-assembly and improving the determination of structures from protein nano and microcrystals from single or serial crystal diffraction., Comment: 38 pages, 3 Main text figures, 14 supplementary figure

Semiconductor heterostructures are the fundamental platform for many important device applications such as lasers, light-emitting diodes, solar cells and high-electron-mobility transistors. Analogous to traditional heterostructures, layered transition metal dichalcogenide (TMDC) heterostructures can be designed and built by assembling individual single-layers into functional multilayer structures, but in principle with atomically sharp interfaces, no interdiffusion of atoms, digitally controlled layered components and no lattice parameter constraints. Nonetheless, the optoelectronic behavior of this new type of van der Waals (vdW) semiconductor heterostructure is unknown at the single-layer limit. Specifically, it is experimentally unknown whether the optical transitions will be spatially direct or indirect in such hetero-bilayers. Here, we investigate artificial semiconductor heterostructures built from single layer WSe2 and MoS2 building blocks. We observe a large Stokes-like shift of ~100 meV between the photoluminescence peak and the lowest absorption peak that is consistent with a type II band alignment with spatially direct absorption but spatially indirect emission. Notably, the photoluminescence intensity of this spatially indirect transition is strong, suggesting strong interlayer coupling of charge carriers. The coupling at the hetero-interface can be readily tuned by inserting hexagonal BN (h-BN) dielectric layers into the vdW gap. The generic nature of this interlayer coupling consequently provides a new degree of freedom in band engineering and is expected to yield a new family of semiconductor heterostructures having tunable optoelectronic properties with customized composite layers., Comment: http://www.pnas.org/content/early/2014/04/10/1405435111.abstract

Stimulus-responsive shape memory materials have attracted tremendous research interests recently, with much effort focused on improving their mechanical actuation. Driven by the needs of nanoelectromechnical devices, materials with large mechanical strain particularly at nanoscale are therefore desired. Here we report on the discovery of a large shape memory effect in BiFeO3 at the nanoscale. A maximum strain of up to ~14% and a large volumetric work density can be achieved in association with a martensitic-like phase transformation. With a single step, control of the phase transformation by thermal activation or electric field has been reversibly achieved without the assistance of external recovery stress. Although aspects such as hysteresis, micro-cracking etc. have to be taken into consideration for real devices, the large shape memory effect in this oxide surpasses most alloys and therefore demonstrates itself as an extraordinary material for potential use in state-of-art nano-systems., Comment: Accepted by Nature Communications