Control of interfacial reactions during liquid phase processing of aluminum matrix composites reinforced with INCONEL 601 fibers

A comprehensive investigation is made of the parameters affecting the extent of interface reactions during squeeze casting of composites consisting of a matrix of either pure Al or alloy AS13 reinforced with fibers of INCONEL 601. The process parameters are the preform thickness and temperature, the fiber volume fraction, the temperature and mass of the liquid metal, and the temperature of the die. Adjustment of these process parameters made possible the full control of reactions. It is found that reactions proceed mainly in the solid state after decomposition of the oxide barrier layer covering the fibers. A simple kinetic model is developed that enlightens the role of this barrier layer. No trace of reaction could be detected in composites processed using preoxidized preforms. Alloying Al with Si also induces a drastic reduction of reactivity. The high ductility of the composites attests to the processing quality. An original procedure is proposed for measuring the activation energy for initiation of reactions by differential thermal analysis

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press