FeOOH-loaded MnO2 nano-composite: An efficient emergency material for thallium pollution incident.

A FeOOH-loaded MnO2 nano-composite was developed as an emergency material for Tl(I) pollution incident. Structural characterizations showed that FeOOH successfully loaded onto MnO2, the nanosheet-flower structure and high surface area (191 m2 g-1) of material contributed to the excellent performance for Tl(I) removal. FeOOH-loaded MnO2 with a Fe/Mn molar ratio of 1:2 exhibited a noticeable enhanced capacity for Tl(I) removal compared to that of pure MnO2. The outstanding performance for Tl(I) removal involves in extremely high efficiency (achieved equilibrium and drinking water standard within 4 min) and the large maximum adsorption capacity (450 mg g-1). Both the control-experiment and XPS characterization proved that the removal mechanism of Tl(I) on FeOOH-loaded MnO2 included adsorption and oxidation: the oxidation of MnO2 played an important role for Tl(I) removal, and the adsorption of FeOOH loaded on MnO2 enhanced Tl(I) purification at the same time. In-depth purification of Tl(I) had reach drinking water standards (0.1 µg L-1) at pH above 7, and there wasn't security risk produced from the dissolution of Mn2+ and Fe2+. Moreover, the as-prepared material could be utilized as a recyclable adsorbent regenerated by using NaOH-NaClO binary solution. Therefore, the synthesized FeOOH-loaded MnO2 in this study has the potential to be applied as an emergency material for thallium pollution incident.

HOSVD-Based 3D Active Appearance Model: Segmentation of Lung Fields in CT Images.

An Active Appearance Model (AAM) is a computer vision model which can be used to effectively segment lung fields in CT images. However, the fitting result is often inadequate when the lungs are affected by high-density pathologies. To overcome this problem, we propose a Higher-order Singular Value Decomposition (HOSVD)-based Three-dimensional (3D) AAM. An evaluation was performed on 310 diseased lungs form the Lung Image Database Consortium Image Collection. Other contemporary AAMs operate directly on patterns represented by vectors, i.e., before applying the AAM to a 3D lung volume,it has to be vectorized first into a vector pattern by some technique like concatenation. However, some implicit structural or local contextual information may be lost in this transformation. According to the nature of the 3D lung volume, HOSVD is introduced to represent and process the lung in tensor space. Our method can not only directly operate on the original 3D tensor patterns, but also efficiently reduce the computer memory usage. The evaluation resulted in an average Dice coefficient of 97.0 % ± 0.59 %, a mean absolute surface distance error of 1.0403 ± 0.5716 mm, a mean border positioning errors of 0.9187 ± 0.5381 pixel, and a Hausdorff Distance of 20.4064 ± 4.3855, respectively. Experimental results showed that our methods delivered significant and better segmentation results, compared with the three other model-based lung segmentation approaches, namely 3D Snake, 3D ASM and 3D AAM.

Ni clusters immobilized on oxygen-rich siloxene nanosheets for efficient electrocatalytic oxygen reduction toward H2O2 synthesis.

Hydrogen peroxide (H2O2) electrosynthesis via the two-electron oxygen reduction reaction (2e- ORR) represents a green alternative to the energy-intensive anthraquinone process. However, the practical application of this method is limited by the lack of cost-effective and high-performance electrocatalysts. Reported here is a hybrid catalyst composed of nickel (Ni) clusters immobilized onto the surface of two-dimensional siloxene nanosheets (Ni/siloxene), which exhibits excellent efficiency and selectivity in electrocatalytic oxygen reduction to H2O2 in an alkaline medium, demonstrating a standard 2e- pathway with >95% H2O2 selectivity across a wide potential range. Experimental results disclose that the high performance of Ni/siloxene can be traced to a synergy of the Ni clusters and the oxygen-rich surface of siloxene. Density functional theory (DFT) calculations further reveal a weakened interaction between Ni/siloxene and *OOH and the consequently reduced energy barrier for the *OOH protonation toward H2O2 desorption, thus leading to a high 2e- ORR reactivity and selectivity. This work provides a valuable and practical guidance for designing high-performance 2e- ORR electrocatalysts based on the rational engineering of the metal-support interaction.