An Exploration of Perovskite Materials for Thermochemical Water Splitting

Two-step thermochemical water splitting is a promising technology for the hydrogen production of solar energy. This process possesses the advantages of utilizing the full solar spectrum, producing flexible fuels, and requiring no precious metal catalysts. It furthermore temporally separates the oxygen release and hydrogen production steps, eliminating the possibility of O2 and H2 recombination. Ceria, which undergoes non-stoichiometric changes in oxygen content, has been demonstrated as an effective material for solar-driven thermochemical fuel production, but the process requires extremely high temperatures (~ 1600 degrees C), leading to efficiency penalties and challenges in reactor design and construction. Accordingly, the objective of this work is the development of new thermochemical reaction substrate materials which enable operation at lower temperatures and ideally increase fuel productivity and efficiency. Here we explore perovskite systems, specifically La1-xSrxMnO3-δ, La0.8Sr0.2Mn1-yFeyO3-δ, and La0.8Sr0.2Mn1-yAlyO3-δ. The link between the solid-state chemistry, redox properties, hydrogen production, and reaction kinetic limitations will be discussed. This study aims to learn how to design and tailor the good catalytic oxides for solar-driven thermochemical water splitting application

Thermodynamic and kinetic assessments of strontium-doped lanthanum manganite perovskites for two-step thermochemical water splitting

Solar-driven thermochemical water splitting using non-stoichiometric oxides has emerged as an attractive technology for solar fuel production. The most widely considered oxide for this purpose is ceria, but the extreme temperatures required to achieve suitable levels of reduction introduce challenges in reactor design and operation, leading to efficiency penalties. Here, we provide a quantitative assessment of the thermodynamic and kinetic properties of La_(1−x)Sr_xMnO_(3−δ) perovskites, targeted for a reduced temperature operation of thermochemical water splitting. Sr-doping into lanthanum manganite increases the thermodynamic fuel production capacity, which reaches 9 ml g^(−1) for 0.4 Sr for a thermochemical cycle operated between 1400 and 800 °C. The hydrogen yields are moreover in good agreement with expected values based on analysis and extrapolation of thermogravimetric data available in the literature. High levels of Sr doping, however, result in low steam-to-hydrogen conversion rates, implying high energy penalties in an operational reactor. Furthermore, the rate of fuel production decreases with increasing Sr content, suggesting that intermediate compositions may yield the most suitable combination of properties

Img2Logo:Generating Golden Ratio Logos from Images

Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc

Automatic Learning of A Supervised Classifier for Patent Prior Art Retrieval

Prior art retrieval is the process of determining a set of possibly relevant prior arts for a specific patent or patent application. Such process is essential for various patent practices, e.g. patentability search, validity search, and infringement search. To support the automatic retrieval of prior arts, existing studies generally adopt the traditional information retrieval (IR) approach or extend the IR approach by incorporating additional information such as citations, classes of patents. Those approaches only exploit partial information of patents and thus may limit the performance of prior art retrieval. In response, we propose a novel approach which employs comprehensive information of patents and performs a supervised approach for prior art retrieval. Unlike traditional supervised learning approach which requires manual preparation of a set of positive and negative training examples, the proposed supervised technique includes a simple but effective mechanism for automatic generation of training examples. Our empirical evaluation on a large dataset consisted of 52,311 semiconductor-related patents indicates that the proposed supervised technique significantly outperforms the traditional full-text-based IR approach

Tourniquet Use in Total Knee Arthroplasty

The use of an intraoperative tourniquet for total knee arthroplasty (TKA) is a common practice. Although it provides clear filed and ideal cementation during surgery, issues regarding the effectiveness, drawbacks and complications are still investigated. This review was conducted to evaluate the role of tourniquet in TKA through a comprehensive literature search was done in PubMed Medicine, Embase, and other internet database. Debating issues, including the blood loss, operation time, alignment, compromised wound healing, quadriceps weakness and timing of release were furtherly examined. Based on our prior work and the general consensus that the tourniquet should be set with the lowest pressure and for the least ischemic time possible, we recommend early tourniquet release right after the closure of extensor mechanism in the TKAs without drainage

Unusual decrease in conductivity upon hydration in acceptor doped, microcrystalline ceria

The impact of hydration on the transport properties of microcrystalline Sm_(0.15)Ce_(0.85)O_(1.925) has been examined. Dense, polycrystalline samples were obtained by conventional ceramic processing and the grain boundary regions were found, by high resolution transmission electron microscopy, to be free of impurity phases. Impedance spectroscopy measurements were performed over the temperature range 250 to 650 °C under dry, H_2O-saturated, and D_2O-saturated synthetic air; and over the temperature range 575 to 650 °C under H_2–H_2O atmospheres. Under oxidizing conditions humidification by either H_2O or D_2O caused a substantial increase in the grain boundary resistivity, while leaving the bulk (or grain interior) properties unchanged. This unusual behavior, which was found to be both reversible and reproducible, is interpreted in terms of the space-charge model, which adequately explains all the features of the measured data. It is found that the space-charge potential increases by 5–7 mV under humidification, in turn, exacerbating oxygen vacancy depletion in the space-charge regions and leading to the observed reduction in grain boundary conductivity. It is proposed that the heightened space-charge potential reflects a change in the relative energetics of vacancy creation in the bulk and at the grain boundary interfaces as a result of water uptake into the grain boundary core. Negligible bulk water uptake is detected under both oxidizing and reducing conditions