Automated Crystal Orientation Mapping in py4DSTEM using Sparse Correlation Matching

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 figure

Experimental characterization of photoemission from plasmonic nanogroove arrays

Metal photocathodes are an important source of high-brightness electron beams, ubiquitous in the operation of both large-scale accelerators and table-top microscopes. When the surface of a metal is nano-engineered with patterns on the order of the optical wavelength, it can lead to the excitation and confinement of surface plasmon polariton waves which drive nonlinear photoemission. In this work, we aim to evaluate gold plasmonic nanogrooves as a concept for producing bright electron beams for accelerators via nonlinear photoemission. We do this by first comparing their optical properties to numerical calculations from first principles to confirm our ability to fabricate these nanoscale structures. Their nonlinear photoemission yield is found by measuring emitted photocurrent as the intensity of their driving laser is varied. Finally, the mean transverse energy of this electron source is found using the solenoid scan technique. Our data demonstrate the ability of these cathodes to provide a tenfold enhancement in the efficiency of photoemission over flat metals driven with a linear process. We find that these cathodes are robust and capable of reaching sustained average currents over 100 nA at optical intensities larger than 2 GW/cm$^2$ with no degradation of performance. The emittance of the generated beam is found to be highly asymmetric, a fact we can explain with calculations involving the also asymmetric roughness of the patterned surface. These results demonstrate the use of nano-engineered surfaces as enhanced photocathodes, providing a robust, air-stable source of high average current electron beams with great potential for industrial and scientific applications.Comment: 9 pages, 9 figure

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

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

Evidence for topological surface states in amorphous Bi2_{2}Se3_{3}

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: 40 pages (21 main + 19 supplemental), 15 figures (4 main + 11 supplemental

Impact of Cigarette Smoke Exposure on Innate Immunity: A Caenorhabditis elegans Model

BACKGROUND: Cigarette smoking is the major cause of chronic obstructive pulmonary disease (COPD) and lung cancer. Respiratory bacterial infections have been shown to be involved in the development of COPD along with impaired airway innate immunity. METHODOLOGY/PRINCIPAL FINDINGS: To address the in vivo impact of cigarette smoke (CS) exclusively on host innate defense mechanisms, we took advantage of Caenorhabditis elegans (C. elegans), which has an innate immune system but lacks adaptive immune function. Pseudomonas aeruginosa (PA) clearance from intestines of C. elegans was dampened by CS. Microarray analysis identified 6 candidate genes with a 2-fold or greater reduction after CS exposure, that have a human orthologue, and that may participate in innate immunity. To confirm a role of CS-down-regulated genes in the innate immune response to PA, RNA interference (RNAi) by feeding was carried out in C. elegans to inhibit the gene of interest, followed by PA infection to determine if the gene affected innate immunity. Inhibition of lbp-7, which encodes a lipid binding protein, resulted in increased levels of intestinal PA. Primary human bronchial epithelial cells were shown to express mRNA of human Fatty Acid Binding Protein 5 (FABP-5), the human orthologue of lpb-7. Interestingly, FABP-5 mRNA levels from human smokers with COPD were significantly lower (p = 0.036) than those from smokers without COPD. Furthermore, FABP-5 mRNA levels were up-regulated (7-fold) after bacterial (i.e., Mycoplasma pneumoniae) infection in primary human bronchial epithelial cell culture (air-liquid interface culture). CONCLUSIONS: Our results suggest that the C. elegans model offers a novel in vivo approach to specifically study innate immune deficiencies resulting from exposure to cigarette smoke, and that results from the nematode may provide insight into human airway epithelial cell biology and cigarette smoke exposure

Connectivity and systemic resilience of the Great Barrier Reef

Australia’s iconic Great Barrier Reef (GBR) continues to suffer from repeated impacts of cyclones, coral bleaching, and outbreaks of the coral-eating crown-of-thorns starfish (COTS), losing much of its coral cover in the process. This raises the question of the ecosystem’s systemic resilience and its ability to rebound after large-scale population loss. Here, we reveal that around 100 reefs of the GBR, or around 3%, have the ideal properties to facilitate recovery of disturbed areas, thereby imparting a level of systemic resilience and aiding its continued recovery. These reefs (1) are highly connected by ocean currents to the wider reef network, (2) have a relatively low risk of exposure to disturbances so that they are likely to provide replenishment when other reefs are depleted, and (3) have an ability to promote recovery of desirable species but are unlikely to either experience or spread COTS outbreaks. The great replenishment potential of these ‘robust source reefs’, which may supply 47% of the ecosystem in a single dispersal event, emerges from the interaction between oceanographic conditions and geographic location, a process that is likely to be repeated in other reef systems. Such natural resilience of reef systems will become increasingly important as the frequency of disturbances accelerates under climate change

The North American tree-ring fire-scar network

Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America