Influence of processing on stability,microstructure and thermoelectric properties of Ca3Co4 − xO9 + δ

Due to high figure of merit, Ca₃Co_4 ? xO_9 + δ (CCO) has potential as p-type material for high-temperature thermoelectrics. Here, the influence of processing including solid state sintering, spark plasma sintering and post-calcination on stability, microstructure and thermoelectric properties is reported. By a new post-calcination approach, single-phase materials were obtained from precursors to final dense ceramics in one step. The highest zT of 0.11 was recorded at 800 °C for CCO with 98 and 72% relative densities. In situ high-temperature X-ray diffraction in air and oxygen revealed a higher stability of CCO in oxygen (～970 °C) than in air (～930 °C), with formation of Ca₃Co₂O₆ which also showed high stability in oxygen, even at 1125 °C. Since achievement of phase pure high density CCO by post-calcination method in air is challenging, the phase stability of CCO in oxygen is important for understanding and further improvement of the method.     

Crystalline Intermediate Phases in the Sol–Gel-Based Synthesis of La2NiO4+δ

X-ray diffraction and transmission electron microscopy were applied to investigate a sol–gel synthetic process for the mixed oxygen ion and electron conductor La₂NiO_4+δ with a K₂NiF₄ structure type. The development of the La₂NiO_4+δ is elucidated considering the influence of calcination temperatures and dwell times. Following the thermal decomposition of nitrate and organic precursors in an intermediate step, the lanthanum nickel oxide is obtained after a short dwell time above 750°C. This occurs by the transformation of an ultrafinely dispersed powder consisting of lanthanum oxycarbonate, lanthanum oxide, and nickel oxide. The pure La₂NiO_4+δ phase was obtained by similar solid-state reactions between nanocrystalline powder particles at just 950°C.     

OctoMap: an efficient probabilistic 3D mapping framework based on octrees

Three-dimensional models provide a volumetric representation of space which is important for a variety of robotic applications including flying robots and robots that are equipped with manipulators. In this paper, we present an open-source framework to generate volumetric 3D environment models. Our mapping approach is based on octrees and uses probabilistic occupancy estimation. It explicitly represents not only occupied space, but also free and unknown areas. Furthermore, we propose an octree map compression method that keeps the 3D models compact. Our framework is available as an open-source C++ library and has already been successfully applied in several robotics projects. We present a series of experimental results carried out with real robots and on publicly available real-world datasets. The results demonstrate that our approach is able to update the representation efficiently and models the data consistently while keeping the memory requirement at a minimum.     

Multifunctional Magnetic Optical Sensor Particles with Tunable Sizes for Monitoring Metabolic Parameters and as a Basis for Nanotherapeutics

Magnetic optical sensor particles with multifunctional cores and shells are synthesized via a facile nanoprecipitation method and the subsequent modification of the particle shell. The hydrophobic particle core includes optical oxygen indicators, a light harvesting system, photosensitizers, and magnetic nanoparticles. Further functionalities are introduced by modifying the shell with enzymes, antibodies, multiple layers of polyelectrolytes, stimuli‐responsive polymers, and luminescent indicator dyes. The hydrodynamic diameter is tunable by varying different precipitation parameters.     

Influence of Lubricant on the Nucleate Boiling Heat Transfer Performance of Refrigerant—A Review

This review provides an overview of the lubricant on the heat transfer performance pertaining to nucleate boiling. It appears that the effect of individual parameter on the heat transfer coefficient may be different from study to study. This is associated with the complex nature of lubricant and some compound effects accompanying the heat transport process. Some important effects such as oil concentration, heat flux, geometric configuration, saturation temperature, thermodynamic and transport properties, miscibility, foaming, and additional surface active agent are reported and discussed. In general, the heat transfer coefficient is impaired provided the oil concentration is sufficient high (e.g., >7%), and this is applicable to smooth and structured tubes. But normally structured tubes tend to suffer more from lubricant, yet this is especially conspicuous when the size of the reentrant channel is small. On the other hand, foaming and partial miscibility seem to benefit the heat transfer coefficient.     

Pessimistic cost-sensitive active learning of decision trees for profit maximizing targeting campaigns

In business applications such as direct marketing, decision-makers are required to choose the action which best maximizes a utility function. Cost-sensitive learning methods can help them achieve this goal. In this paper, we introduce Pessimistic Active Learning (PAL). PAL employs a novel pessimistic measure, which relies on confidence intervals and is used to balance the exploration/exploitation trade-off. In order to acquire an initial sample of labeled data, PAL applies orthogonal arrays of fractional factorial design. PAL was tested on ten datasets using a decision tree inducer. A comparison of these results to those of other methods indicates PAL’s superiority.