Mesoporous Zn–Ti Mixed Oxide Nanostructure: A New Bifunctional Catalyst for Partial Oxidation and Bezylation Reactions

Here, we report a facile synthesis of porous zinc-titanium oxide based mixed oxide nanoparticles having Zn/Ti molar ratio 1:2 based on evaporation-induced sol–gel route using Pluronic triblock copolymer P123 as a template. Use of volatile ethanolic media during the evaporation-induced self-assembly (EISA) method facilitates the formation of Zn–Ti mixed oxide heterostructure. Powder XRD data reveals that the composite material displayed ZnTiO₃/TiO₂ phases. Morphology, composition, porosity, nanostructure and thermal stability have been systematically investigated using small angle powder XRD, FE SEM-EDS, TEM, N₂ sorption, FT IR and TG-DTA techniques. The observed BET surface area of Zn–Ti mixed oxide was 231 m² g^?1 with a typical mesopore diameter (~?5 nm) mostly arising from interparticle void space. The Zn–Ti mixed oxide catalyst showed bifunctional activity for Friedel–Craft benzylation of aromatics using benzyl chloride as well as partial oxidation of olefins under mild reaction conditions using dilute aqueous H₂O₂ as oxidant.

Graphical Abstract

Zn–Ti based porous nanoparticles synthesized using Pluronic P123 copolymer surfactant via EISA method has shown a very high surface area of 231 m² g^?1 and a significant bifunctional role for liquid phase oxidation and benzylation reaction.

     

Germanium Source Metal Drain Tunnel FET with Dual Dielectric Underlap

Silicon - In this paper, we propose, design and simulate a new double gate (DG) tunnel field effect transistor (TFET), using germanium (Ge) source, dual dielectric gate oxide, gate/drain underlap...     

Post-disaster damage classification based on deep multi-view image fusion

This study aims to facilitate a more reliable automated postdisaster assessment of damaged buildings based on the use of multiple view imagery. Toward this, a Multi-View Convolutional Neural Network (MV-CNN) architecture is proposed, which combines the information from different views of a damaged building, resulting in 3-D aggregation of the 2-D damage features from each view. This spatial 3-D context damage information will result in more accurate and reliable damage quantification in the affected buildings. For validation, the presented model is trained and tested on a real-world visual data set of expert-labeled buildings following Hurricane Harvey. The developed model demonstrates an accuracy of 65% in predicting the exact damage states of buildings, and around 81% considering ±1 class deviation from ground-truth, based on a five-level damage scale. Value of information (VOI) analysis reveals that the hybrid models, which consider at least one aerial and ground view, perform better.     

磁流变弹性体的性能研究

以天然橡胶为基体制备磁流变弹性体（MRE），研究MRE的Payne效应及磁感应强度和磁流变效应。电子显微镜分析得出，对于羰基铁粉质量分数最大（81.67%）的MRE，羰基铁粉分布密集，出现羰基铁粉团聚现象。流变仪测试结果表明：随着羰基铁粉质量分数的增大，MRE的Payne效应和磁流变效应增强；随着应变的增大，MRE的储能模量减小，损耗因子增大。