Fission in Rapidly Rotating Nuclei

We study the effect of rotation in fission of the atomic nucleus256Fm using an independent-particle shell modelwith the mean field represented by a deformed Woods-Saxon potential and the shapes defined through the Cassinian oval parametrization. The variations of barrier height with increasing angular momentum, appearance of double hump in fission path are analysed. Our calculations explain the appearance of double hump in fission path of 256Fm nucleus. The second minimum vanishes with increase in angular momentum which hints that the fission barrier disappears at large spin

Cytosolic Phospholipase A2α and Eicosanoids Regulate Expression of Genes in Macrophages Involved in Host Defense and Inflammation

Acknowledgments: We thank Dr. Robert Barkley and Charis Uhlson for mass spectrometry analysis. Funding: This work was supported by grants from the National Institutes of Health HL34303 (to C.C.L., R.C.M. and D.L.B), DK54741 (to J.V.B.), GM5322 (to D.L.W.) and the Wellcome Trust (to N.A.R.G. and G.D.B.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Development of solar fuels photoanodes through combinatorial integration of Ni–La–Co–Ce oxide catalysts on BiVO_4

The development of an efficient photoanode remains the primary materials challenge in the establishment of a scalable technology for solar water splitting. The typical photoanode architecture consists of a semiconductor light absorber coated with a metal oxide that serves a combination of functions, including corrosion protection, electrocatalysis, light trapping, hole transport, and elimination of deleterious recombination sites. To date, such coatings have been mostly limited to simple materials such as TiO_2 and Co-Pi, with extensive experimental and theoretical effort required to provide an understanding of the physics and chemistry of the semiconductor-coating interface. To provide a more efficient exploration of metal oxide coatings for a given light absorber, we introduce a high throughput methodology wherein a uniform BiVO_4 thin film is coated with 858 unique metal oxides covering a range of metal oxide loadings and the full Ni–La–Co–Ce oxide quaternary composition space. Photoelectrochemical characterization of each photoanode reveals that approximately one third of the coatings lower the photoanode performance while select combinations of metal oxide composition and loading provide up to a 14-fold increase in the maximum photoelectrochemical power generation for oxygen evolution in pH 13 electrolyte. Particular Ce-rich coatings also exhibit an anti-reflection effect that further amplifies the performance, yielding a 20-fold enhancement in power conversion efficiency compared to bare BiVO4. By use of in situ optical spectroscopy and comparisons between the metal oxide coatings and their extrinsic optical and electrocatalytic properties, we present a suite of data-driven discoveries, including composition regions which form optimal interfaces with BiVO4 and photoanodes that are suitable for integration with a photocathode due to their excellent power conversion and solar transmission efficiencies. The high throughput experimentation and informatics provides a powerful platform for both identifying the pertinent interfaces for further study and discovering high performance photoanodes for incorporation into efficient water splitting devices

High-throughput synchrotron X-ray diffraction for combinatorial phase mapping

Discovery of new materials drives the deployment of new technologies. Complex technological requirements demand precisely tailored material functionalities, and materials scientists are driven to search for these new materials in compositionally complex and often non-equilibrium spaces containing three, four or more elements. The phase behavior of these high-order composition spaces is mostly unknown and unexplored. High-throughput methods can offer strategies for efficiently searching complex and multi-dimensional material genomes for these much needed new materials and can also suggest a processing pathway for synthesizing them. However, high-throughput structural characterization is still relatively under-developed for rapid material discovery. Here, a synchrotron X-ray diffraction and fluorescence experiment for rapid measurement of both X-ray powder patterns and compositions for an array of samples in a material library is presented. The experiment is capable of measuring more than 5000 samples per day, as demonstrated by the acquisition of high-quality powder patterns in a bismuth-vanadium-iron oxide composition library. A detailed discussion of the scattering geometry and its ability to be tailored for different material systems is provided, with specific attention given to the characterization of fiber textured thin films. The described prototype facility is capable of meeting the structural characterization needs for the first generation of high-throughput material genomic searches

Benchmarking the Acceleration of Materials Discovery by Sequential Learning

Sequential learning (SL) strategies, i.e. iteratively updating a machine learning model to guide experiments, have been proposed to significantly accelerate materials discovery and research. Applications on computational datasets and a handful of optimization experiments have demonstrated the promise of SL, motivating a quantitative evaluation of its ability to accelerate materials discovery, specifically in the case of physical experiments. The benchmarking effort in the present work quantifies the performance of SL algorithms with respect to a breadth of research goals: discovery of any “good” material, discovery of all “good” materials, and discovery of a model that accurately predicts the performance of new materials. To benchmark the effectiveness of different machine learning models against these goals, we use datasets in which the performance of all materials in the search space is known from high-throughput synthesis and electrochemistry experiments. Each dataset contains all pseudo-quaternary metal oxide combinations from a set of six elements (chemical space), the performance metric chosen is the electrocatalytic activity (overpotential) for the oxygen evolution reaction (OER). A diverse set of SL schemes is tested on four chemical spaces, each containing 2121 catalysts. The presented work suggests that research can be accelerated by up to a factor of 20 compared to random acquisition in specific scenarios. The results also show that certain choices of SL models are ill-suited for a given research goal resulting in substantial deceleration compared to random acquisition methods. The results provide quantitative guidance on how to tune an SL strategy for a given research goal and demonstrate the need for a new generation of materials-aware SL algorithms to further accelerate materials discovery

Generating Information-Rich High-Throughput Experimental Materials Genomes using Functional Clustering via Multitree Genetic Programming and Information Theory

High-throughput experimental methodologies are capable of synthesizing, screening and characterizing vast arrays of combinatorial material libraries at a very rapid rate. These methodologies strategically employ tiered screening wherein the number of compositions screened decreases as the complexity, and very often the scientific information obtained from a screening experiment, increases. The algorithm used for down-selection of samples from higher throughput screening experiment to a lower throughput screening experiment is vital in achieving information-rich experimental materials genomes. The fundamental science of material discovery lies in the establishment of composition–structure–property relationships, motivating the development of advanced down-selection algorithms which consider the information value of the selected compositions, as opposed to simply selecting the best performing compositions from a high throughput experiment. Identification of property fields (composition regions with distinct composition-property relationships) in high throughput data enables down-selection algorithms to employ advanced selection strategies, such as the selection of representative compositions from each field or selection of compositions that span the composition space of the highest performing field. Such strategies would greatly enhance the generation of data-driven discoveries. We introduce an informatics-based clustering of composition-property functional relationships using a combination of information theory and multitree genetic programming concepts for identification of property fields in a composition library. We demonstrate our approach using a complex synthetic composition-property map for a 5 at. % step ternary library consisting of four distinct property fields and finally explore the application of this methodology for capturing relationships between composition and catalytic activity for the oxygen evolution reaction for 5429 catalyst compositions in a (Ni–Fe–Co–Ce)O_x library

The role of the CeO_2/BiVO_4 interface in optimized Fe-Ce oxide coatings for solar fuels photoanodes

Solar fuel generators entail a high degree of materials integration, and efficient photoelectrocatalysis of the constituent reactions hinges upon the establishment of highly functional interfaces. The recent application of high throughput experimentation to interface discovery for solar fuels photoanodes has revealed several surprising and promising mixed-metal oxide coatings for BiVO_4. Using sputter deposition of composition and thickness gradients on a uniform BiVO_4 film, we systematically explore photoanodic performance as a function of the composition and loading of Fe–Ce oxide coatings. This combinatorial materials integration study not only enhances the performance of this new class of materials but also identifies CeO_2 as a critical ingredient that merits detailed study. A heteroepitaxial CeO_2(001)/BiVO_4(010) interface is identified in which Bi and V remain fully coordinated to O such that no surface states are formed. Ab initio calculations of the integrated materials and inspection of the electronic structure reveals mechanisms by which CeO_2 facilitates charge transport while mitigating deleterious recombination. The results support the observations that addition of Ce to BiVO_4 coatings greatly enhances photoelectrocatalytic activity, providing an important strategy for developing a scalable solar fuels technology

Pathways Regulating Cytosolic Phospholipase a\u3csub\u3e2\u3c/sub\u3e Activation and Eicosanoid Production in Macrophages by Candida Albicans

Resident tissue macrophages are activated by the fungal pathogen Candida albicans to release eicosanoids, which are important modulators of inflammation and immune responses. Our objective was to identify the macrophage receptors engaged by C. albicans that mediate activation of group IVA cytosolic phospholipase A2 (cPLA2α), a regulatory enzyme that releases arachidonic acid (AA) for production of prostaglandins and leukotrienes. A comparison of peritoneal macrophages from wild type and knock-out mice demonstrates that the β-glucan receptor Dectin-1 and MyD88 regulate early release of AA and eicosanoids in response to C. albicans. However, cyclooxygenase 2 (COX2) expression and later phase eicosanoid production are defective in MyD88-/- but not Dectin-1-/- macrophages. Furthermore, C. albicans-stimulated activation of MAPK and phosphorylation of cPLA2α on Ser-505 are regulated by MyD88 and not Dectin-1. In contrast, Dectin-1 mediates MAPK activation, cPLA 2α phosphorylation, and COX2 expression in response to particulate β-glucan suggesting that other receptors engaged by C. albicans preferentially mediate these responses. Results also implicate the mannan-binding receptor Dectin-2 in regulating cPLA2α. C. albicans-stimulated MAPK activation and AA release are blocked by D-mannose and Dectin-2-specific antibody, and overexpression of Dectin-2 in RAW264.7 macrophages enhances C. albicans-stimulated MAPK activation, AA release, and COX2 expression. In addition, calcium mobilization is enhanced in RAW264.7 macrophages overexpressing Dectin-1 or -2. The results demonstrate that C. albicans engages both β-glucan and mannan-binding receptors on macrophages that act with MyD88 to regulate the activation of cPLA2α and eicosanoid production