Reversible planar gliding and microcracking in a single-crystalline Ni-rich cathode
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The efficient preparation of single-crystalline ionic polymers and fundamental understanding of their structure–property relationships at the molecular level remains a challenge in chemistry and materials science. Herein, we observe the single-crystal structure of a highly ordered polycationic polymer (polyelectrolyte) and its proton conductivity. The polyelectrolyte single crystals can be prepared on a gram-scale in quantitative yield, by taking advantage of an ultraviolet/sunlight-induced topochemical polymerization, from a tricationic monomer—a self-complementary building block possessing a preorganized conformation. A single-crystal-to-single-crystal photopolymerization was revealed unambiguously by in situ single-crystal X-ray diffraction analysis, which was also employed to follow the progression of molecular structure from the monomer, to a partially polymerized intermediate, and, finally, to the polymer itself. Collinear polymer chains are held together tightly by multiple Coulombic interactions involving counterions to form two-dimensional lamellar sheets (1 nm in height) with sub-nanometer pores (5 Å). The polymer is extremely stable under 254 nm light irradiation and high temperature (above 500 K). The extraordinary mechanical strength and environmental stability—in combination with its impressive proton conductivity (~3 × 10 –4 S cm –1 )—endow the polymer with potential applications as a robust proton-conducting material. By marrying supramolecular chemistry with macromolecular science, the outcome represents a major step toward the controlled synthesis of single-crystalline polyelectrolyte materials with perfect tacticity.
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Ethanol is a promising platform molecule for production of a variety of fuels and chemicals. Of particular interest is producing middle distillate fuels (i.e., jet and diesel blendstock) from renewable ethanol feedstock. State-of-the-art alcohol-to-jet technology requires multiple process steps based on catalytic dehydration of ethanol to form ethylene, followed by sometimes a multi-step oligomerization, and then hydrotreatment and distillation. Here we report on a new catalytic route in which ethanol is directly converted to n-butene (1- and 2-butene mixtures) over Ag-ZrO2/SBA-16, thus offering the potential for a reduction in the number of required processing steps versus conventional alcohol-to-jet technology. This catalyst system provides the balanced metal and Lewis acid sites required to selectively facilitate a cascading sequence of reactions that includes dehydrogenation, aldol condensation, Meerwein–Ponndorf–Verley reduction, dehydration, and hydrogenation. High conversion and selectivity toward either n-butene or 1,3-butadiene is achieved by tuning the hydrogen feed partial pressure and other process/catalyst parameters. With sufficient hydrogen partial pressure 1,3-butadiene is completely and selectively hydrogenated to form n-butene. The reaction mechanism was elucidated through operando-nuclear magnetic resonance investigations coupled with reactivity measurements. Combined experimental-computational investigation reveals how changes in silver and zirconium composition and the silver oxidation state affects reactivity under controlled hydrogen partial pressures and after prolonged run times. Finally, catalyst effectiveness also was demonstrated when using wet ethanol feed, thus highlighting process flexibility in terms of feedstock purity requirements. This work was financially supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and was performed at the Pacific Northwest National Laboratory (PNNL) under Contract No. DE-AC05-76RL01830 and the National Renewable Energy Laboratory under Contract No. DE-AC36- 08GO28308. Part of the work conducted by S. A. Akhade was performed under the auspices of the U.S. DOE at Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. This work was partly supported through the PNNL-WSU Distinguished Graduate Research Program for ADW. NMR and XPS experiments were performed using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research
We present results from data acquired by the SENSEI experiment at SNOLAB after a major upgrade in May 2023, which includes deploying 16 new sensors and replacing the copper trays that house the CCDs with a new light-tight design. We observe a single-electron event rate of (1.39±0.11)×10^{-5} e^{-}/pix/day, corresponding to (39.8±3.1) e^{-}/gram/day. This is an order-of-magnitude improvement compared to the previous lowest single-electron rate in a silicon detector and the lowest for any photon detector in the wavelength range between near-infrared and ultraviolet. We use these data to obtain a 90% confidence level upper bound of 1.53×10^{-5} e^{-}/pix/day and to set constraints on sub-GeV dark matter candidates that produce single-electron events. We hypothesize that the data taken at SNOLAB in the previous run, with an older tray design for the sensors, contained a larger rate of single-electron events due to light leaks. We test this hypothesis using data from the SENSEI detector located in the MINOS cavern at Fermilab.
In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.
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Single atom catalysts have been found to exhibit superior selectivity over nanoparticulate catalysts for catalytic reactions such as hydrogenation due to their single-site nature. However, improved selectively is often accompanied by loss of activity and slow kinetics. Here we demonstrate that neighboring Pd single atom catalysts retain the high selectivity merit of sparsely isolated single atom catalysts, while the cooperative interactions between neighboring atoms greatly enhance the activity for hydrogenation of carbon-halogen bonds. Experimental results and computational calculations suggest that neighboring Pd atoms work in synergy to lower the energy of key meta-stable reactions steps, i.e., initial water desorption and final hydrogenated product desorption. The placement of neighboring Pd atoms also contribute to nearly exclusive hydrogenation of carbon-chlorine bond without altering any other bonds in organohalogens. The promising hydrogenation performance achieved by neighboring single atoms sheds light on a new approach for manipulating the activity and selectivity of single atom catalysts that are increasingly studied in multiple applications.
Single Pt atom catalysts are key targets because a high exposure of Pt substantially enhances electrocatalytic activity. In addition, PtRu alloy nanoparticles are the most active catalysts for the methanol oxidation reaction. To combine the exceptional activity of single Pt atom catalysts with an active Ru support we must overcome the synthetic challenge of forming single Pt atoms on noble metal nanoparticles. In this report we demonstrate a process that grows and spreads Pt islands on Ru branched nanoparticles to create single-Pt-atom-on-Ru catalysts. By following the spreading process by in situ TEM, we found that the formation of a stable single atom structure is thermodynamically driven by the formation of strong Pt–Ru bonds and the lowering of the surface energy of the Pt islands. The stability of the single-Pt-atom-on-Ru structure and its resilience to CO poisoning result in a high current density and mass activity for the methanol oxidation reaction over time.
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. DUNE is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. Central to achieving DUNE's physics program is a far detector that combines the many tens-of-kiloton fiducial mass necessary for rare event searches with sub-centimeter spatial resolution in its ability to image those events, allowing identification of the physics signatures among the numerous backgrounds. In the single-phase liquid argon time-projection chamber (LArTPC) technology, ionization charges drift horizontally in the liquid argon under the influence of an electric field towards a vertical anode, where they are read out with fine granularity. A photon detection system supplements the TPC, directly enhancing physics capabilities for all three DUNE physics drivers and opening up prospects for further physics explorations. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume IV presents an overview of the basic operating principles of a single-phase LArTPC, followed by a description of the DUNE implementation. Each of the subsystems is described in detail, connecting the high-level design requirements and decisions to the overriding physics goals of DUNE.
Commercial electrical conductor wires are currently produced from aluminum alloys by multi-step deformation processing involving rolling and drawing. These processes typically require 10 to 20 steps of deformation, since the plastic strain or reduction that can be imposed in a single step is limited by material workability and process mechanics. Here, we demonstrate a fundamentally different, single-step approach to produce flat wire aluminum products using machining-based deformation that also ensures adequate material workability in the formed product. Two process routes are proposed: (1) chip formation by free-machining (FM), with a post-machining, light drawing reduction (<20%) to achieve desired finish and (2) constrained chip formation by large strain extrusion machining (LSEM). Using commercially pure aluminum conductor alloys (Al 1100 and EC1350) as representative material systems, we demonstrate key features of the machining-based processing, including (a) single-step processing to achieve flat wire geometries, (b) surface finish (Ra = 0.2 to 1.0 μm) comparable to that of commercial wire products made by drawing/rolling, (c) deformation control independent of wire size, and (d) hardness increases of 50–150% over that of annealed wires, while retaining high electrical conductivity (>56% IACS). Here, the wire microstructure, which can also be varied via the large-strain deformation parameters, is correlated with mechanical and electrical properties. Implications for commercial manufacture of flat wire products are discussed.
The non-destructive readout capability of the Skipper Charge Coupled Device (CCD) has been demonstrated to reduce the noise limitation of conventional silicon devices to levels that allow single-photon or single-electron counting. The noise reduction is achieved by taking multiple measurements of the charge in each pixel. These multiple measurements come at the cost of extra readout time, which has been a limitation for the broader adoption of this technology in particle physics, quantum imaging, and astronomy applications. This work presents recent results of a novel sensor architecture that uses multiple non-destructive floating-gate amplifiers in series to achieve sub-electron readout noise in a thick, fully-depleted silicon detector to overcome the readout time overhead of the Skipper-CCD. This sensor is called the Multiple-Amplifier Sensing Charge-Coupled Device (MAS-CCD) can perform multiple independent charge measurements with each amplifier, and the measurements from multiple amplifiers can be combined to further reduce the readout noise. We will show results obtained for sensors with 8 and 16 amplifiers per readout stage in new readout operations modes to optimize its readout speed. The noise reduction capability of the new techniques will be demonstrated in terms of its ability to reduce the noise by combining the information from the different amplifiers, and to resolve signals in the order of a single photon per pixel. The first readout operation explored here avoids the extra readout time needed in the MAS-CCD to read a line of the sensor associated with the extra extent of the serial register. The second technique explore the capability of the MAS-CCD device to perform a region of interest readout increasing the number of multiple samples per amplifier in a targeted region of the active area of the device.
An outstanding hurdle for defect spin qubits in silicon carbide (SiC) is single-shot readout, a deterministic measurement of the quantum state. Here, we demonstrate single-shot readout of single defects in SiC via spin-to-charge conversion, whereby the defect’s spin state is mapped onto a long-lived charge state. With this technique, we achieve over 80% readout fidelity without pre- or postselection, resulting in a high signal-to-noise ratio that enables us to measure long spin coherence times. Combined with pulsed dynamical decoupling sequences in an isotopically purified host material, we report single-spin T 2 > 5 seconds, over two orders of magnitude greater than previously reported in this system. The mapping of these coherent spin states onto single charges unlocks both single-shot readout for scalable quantum nodes and opportunities for electrical readout via integration with semiconductor devices.
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Chalcogenides are the cornerstone of the semiconductor and thermoelectric industries and are up-and-coming materials for superconductors, catalysis, and battery applications. Challenges in synthesizing those materials emerge from the chalcogen's volatility and the tendencies of chalcogenides to react with even trace quantities of oxygen. Many techniques have been applied to the growth of chalcogenide single crystals, which are convenient for structure determinations and intrinsic property measurements. One of the recent advances in chalcogenide chemistry is the intriguing single-crystal-to-single-crystal (SCSC) transformation, leading to new metastable compositions. Post-synthetic transformations are well-known and studied for chalcogenide powders; however, examples of post-synthetic conversions that retain single crystallinity are rare. To date, the scope of SCSC reactions includes (de)intercalation in the layered compositions and ion exchange in open-framework materials, salt-inclusion chalcogenides, and layered structures. This poster will discuss the successful examples of SCSC modifications monitored by single-crystal X-ray diffraction (SC-XRD), emphasizing how post-synthetic transformations affect materials' properties.
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A comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3' RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of timeseries transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. Our data confirm that DroNcseq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.