The high-temperature phase diagram of the UO2 – ThO2 system has been experimentally revisited in the present study for the first time since 1970, using a laser heating approach combined with fast pyrometry in a thermal arrest method. The melting / solidification temperature, which is of fundamental information for a reactor design was studied here. It was found that low addition of ThO2 to UO2 would result in a slight decrease of the solidification temperature. A minimum was found at 3098 K around a composition of 5 mol % ThO2. The solid / liquid transition temperature was then observed to increase again with increasing ThO2 fraction. The literature value of pure ThO2 (around 3630 K) was well reproduced here. Important experimental difficulties, stemming from the high temperatures reached during the measurements, as well as a completeinvestigation with electron microscopy, Raman spectroscopy and powder X-ray diffraction are extensively discussed. These results show the importance of the high-temperature oxygen chemistry also in this actinide oxide compound.JRC.E.3-Materials researc

The click-based interactive segmentation aims to extract the object of interest from an image with the guidance of user clicks. Recent work has achieved great overall performance by employing feedback from the output. However, in most state-of-the-art approaches, 1) the inference stage involves inflexible heuristic rules and requires a separate refinement model, and 2) the number of user clicks and model performance cannot be balanced. To address the challenges, we propose a click-based and mask-guided interactive image segmentation framework containing three novel components: Cascade-Forward Refinement (CFR), Iterative Click Loss (ICL), and SUEM image augmentation. The CFR offers a unified inference framework to generate segmentation results in a coarse-to-fine manner. The proposed ICL allows model training to improve segmentation and reduce user interactions simultaneously. The proposed SUEM augmentation is a comprehensive way to create large and diverse training sets for interactive image segmentation. Extensive experiments demonstrate the state-of-the-art performance of the proposed approach on five public datasets. Remarkably, our model reduces by 33.2%, and 15.5% the number of clicks required to surpass an IoU of 0.95 in the previous state-of-the-art approach on the Berkeley and DAVIS sets, respectively.