Perovskite oxides for oxygen transport: Chemistry and material horizons.

Oxygen permeable membrane, which has the advantages of high separation selectivity, low energy consumption and simple process in oxygen separation, can be used in the fields of environment and energy, such as pure oxygen preparation, fuel cell, oxygen-enriched combustion and chemical reactor for methane catalytic conversion (e.g. partial oxidation of methane, carbon dioxide reforming with methane). New materials and technological development are needed to achieve this target for GHG reformation. In this direction, mixed ionic-electronic conducting (MIEC) oxides based on perovskite oxides are one of the prominent materials for oxygen transport at high temperatures. These compounds were created into solid ceramic membranes with considerable electronic and oxygen ionic conductivity. As a result of the differential partial pressure of oxygen across the membrane, this process enables the ionic transfer of oxygen from the air, providing the driving force for oxygen ion transport. Notably, over the last 40 years, the defect theory has been applied to a wide range of MIEC materials, providing insight into electronic and ionic transport, widely applied to designing catalysts for wastewater treatment and gas purification. However, a critical review by in-depth analysis from the material side on perovskite oxides for oxygen transport is needed. This work evaluates the research community's significant and relevant contributions in the perovskite oxides for gas separation domain over the previous four decades in conjunction with theoretical concepts, which would give rise to the fundamental understanding of the impact of various transitional metal elements on oxygen transport performance and stability in a different atmosphere.

3D cost aggregation with multiple minimum spanning trees for stereo matching.

Cost aggregation is one of the key steps in the stereo matching problem. In order to improve aggregation accuracy, we propose a cost-aggregation method that can embed minimum spanning tree (MST)-based support region filtering into PatchMatch 3D label search rather than aggregating on fixed size patches. However, directly combining PatchMatch label search and MST filtering is not straightforward, due to the extremely high complexity. Thus, we develop multiple MST structures for cost aggregation on plenty of 3D labels, and design the tree-level random search strategy to find possible 3D labels of each pixel. Extensive experiments show that our method reaches higher accuracy than the other existing cost-aggregation and global-optimization methods such as the 1D MST, the PatchMatch and the PatchMatch Filter, and currently ranks first on the Middlebury 3.0 benchmark.