Thiol-Functionalized Covalent Organic Frameworks as Thermal History Indictor for Temperature and Time History Monitoring

Various products, including foods and pharmaceuticals, are sensitive to temperature fluctuations. Thus, temperature monitoring during production, transportation, and storage is critical. Facile indicators are required to monitor temperature conditions via color changes in real time. This study aimed to prepare and apply thiol-functionalized covalent organic frameworks (COFs) as a novel indicator for monitoring thermal history and temperature abuse. The COFs underwent obvious color changes from bright yellow to purple after exposure to different temperatures for varying durations. The reaction kinetics are analyzed under isothermal conditions, which reveal that the order of reaction rates is k_−20°C < k_4°C < k_20°C < k_35°C < k_55°C. The activation energy (E_a) of the COFs is calculated using the Arrhenius equation as 50.71 kJ moL⁻¹. The COFs are capable of sensitive color changes and offer a broad temperature tracking range, thereby demonstrating their application potential for the monitoring of temperature and time exposure history during production, transportation, and storage. This excellent performance thermal history indicator also shows promise for expanding the application field of COFs.     

Highly active sites of low spin FeⅡN4species:The identification and the ORR performance

Over recent years,catalytic materials of Fe-N-C species have been recognized being active for oxygen reduction reaction(ORR).However,the identification of active site remains challenging as it generally involves a pyrolysis process and mixed components being obtained.Herein Fe₃C/C and Fe₂N/C samples were synthesized by temperature programmed reduction of Fe precursors in 15%CH₄/H₂and pure NH₃,respectively.By acid leaching of Fe₂N/C sample,only single sites of FeN₄species were presented,providing an ideal model for identification of catalytic functions of the single sites of FeN₄in ORR.A correlation was conducted between the concentration of Fe^ⅡN₄in low spin state by Mossbauer spectra and the kinetic current density at 0.8 V in alkaline media,and such a structure-performance correlation assures the catalytic roles of low spin Fe^ⅡN₄ species as highly active sites for the ORR.     

可见光引发剂研究进展

光固化技术的应用非常广泛，常用于光固化涂料、油墨、牙科固化、胶粘剂以及 3D打印材料等领域。与紫外光固化相比，可见光固化具备辐射安全、固化深度高、设备价格低廉等优势。作为光固化体系的重要组成部分，光引发剂的研究一直备受关注。本文对近 2~3 a可见光引发剂的研究进展进行了综述，主要从 TPO类、萘酰亚胺类、蒽醌类、咔唑类、硅酮类、肟酯类、共轭染料类、光生酸剂类和金属配合物类光引发剂 9个方面进行了综述，并对可见光引发剂的发展方向做了简单的概述。     

Flotation Behavior,Collector Adsorption Mechanism of Quartz and Feldspar-Quartz Systems Using PEA as a Novel Green Collector

Silicon - A novel green cationic surfactant Poly (propylene glycol) bis (2-aminopropyl ether) (PEA) with multiple amine groups was utilized as a collector for flotation separation of quartz from...     

Enhanced photo-electrochemical activity of ZnO/Cu2S nanotube arrays photocathodes

ZnO/Cu₂S nanotube arrays are fabricated firstly by a facile and capping-agent-free method, and the photo-electrochemical performance has been studied systematically. The results show that ZnO/Cu₂S nanotube arrays achieve enhanced photo-electrochemical water splitting performance and the photocurrent densities of ZnO/Cu₂S are 7.9 times than that of ZnO at 0 V versus Ag/AgCl. The performance of the ZnO/Cu₂S nanotube arrays can be adjusted by changing the amount of Cu₂S microcrystals. The results confirm that the enhanced photo-electrochemical performance of ZnO/Cu₂S is due to the significantly improved visible light absorption, effective separation of photo-induced carriers due to the well band energy match and the formed p-n junction between ZnO and Cu₂S.     

Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology

This work intends to develop an online experimental system for screening of deoxynivalenol (DON) contamination in whole wheat meals by visible/near-infrared (Vis/NIR) spectroscopy and computer vision coupling technology. Spectral and image information of samples with various DON levels was collected at speed of 0.15 m s⁻¹ on a conveyor belt. The two-type data were then integrated and subjected to chemometric analysis. Discriminant analysis showed that samples could be classified by setting 1000 μg kg⁻¹ as the cut-off value. The best correct classified rate obtained in prediction was 93.55% based on fusion of spectral and image features, with reduced prediction uncertainty as compared to single feature. However, quantification of DON by quantitative analysis was not successful due to poor model performance. These results indicate that, although not accurate enough to provide conclusive result, this coupling technology could be adopted for rapid screening of DON contamination in cereals and feeds during processing.