Facile preparation of biomimetic mineralized COFs based on magnetic silk fibroin and its effective extraction of sulforaphane from cruciferous vegetables
文献类型: 外文期刊
第一作者: Liu, Guangyang
作者: Liu, Guangyang;Zhang, Xuan;Li, Lingyun;Chen, Ge;Lv, Jun;Xu, Xiaomin;Huang, Xiaodong;Xu, Donghui;Liu, Guangyang;Zhang, Xuan;Wang, Jian;Cao, Jiayong;Yin, Chen;Liu, Yuan;Zhang, Xuan;Xu, Donghui;Wang, Jing
作者机构:
关键词: Sulforaphane; Biomimetic mineralization; Silk fibroin; Covalent organic framework; Magnetic solid-phase extraction
期刊名称:FOOD CHEMISTRY ( 影响因子:8.8; 五年影响因子:8.6 )
ISSN: 0308-8146
年卷期: 2024 年 434 卷
页码:
收录情况: SCI
摘要: A novel biomimetic mineralized covalent organic framework (BM-COF) was prepared based on magnetic silk fibroin and a new sulforaphane pretreatment technology was constructed. First, metal coordination was performed on the surface of silk fibroin, and nanoparticles were deposited by in-situ mineralization after coprecipitation. Then, biomineralized COFs were prepared by in-situ self-assembly of a COF layer on Fe3O4@silk fibroin surface guided by interfacial directional growth technology. The BM-COFs had a multilayer structure, large specific surface area and pore volume, and superparamagnetic properties, which make them an ideal adsorbent. The adsorption of sulforaphane by BM-COFs is mainly multi-molecular layer adsorption and chemisorption, there might be electrostatic action, pi-stacking and hydrogen bonding in the adsorption process. The composite material was successfully used for the pretreatment of sulforaphane in cruciferous vegetables. An extraction time of 30 min gave extraction efficiencies as high as 92%, and the recovery could reach more than 73%.
分类号:
- 相关文献
作者其他论文 更多>>
-
An improved 3D-SwinT-CNN network to evaluate the fermentation degree of black tea
作者:Zhu, Fengle;Wang, Jian;Zhang, Yuqian;Zhao, Zhangfeng;Shi, Jiang;He, Mengzhu
关键词:Black tea fermentation; Hyperspectral imaging; 3D-SwinT-CNN; 3D convolutional neural networks; Swin transformer
-
TMT-based quantitative proteomic analysis reveals eggshell matrix protein changes correlated with eggshell quality in Jing Tint 6 laying hens of different ages
作者:Zhao, Dan-rong;Gong, Fei;Min, Yu-na;Zhao, Dan-rong;Gao, Li-bing;Feng, Jia;Zhang, Hai-jun;Wu, Shu-geng;Wang, Jing;Min, Yu-na
关键词:eggshell quality; ultrastructure; matrix proteins; proteomics
-
A survey of efficient fine-tuning methods for Vision-Language Models - Prompt and Adapter
作者:Xing, Jialu;Liu, Jianping;Sun, Lulu;Chen, Xi;Gu, Xunxun;Wang, Yingfei;Liu, Jianping;Wang, Jian;Liu, Jianping
关键词:Vision-language; Computer vision; Efficient fine-tuning; Pre-training model; Prompt; Adapter
-
Complete genome sequence of a novel dsRNA virus from the phytopathogenic fungus Fusarium oxysporum
作者:Wang, Jing;Ni, Yunxia;Zhao, Hui;Liu, Xintao;Liu, Hongyan;Qiu, Rui;Li, Shujun
关键词:
-
The Function of SD1 on Shoot Length and its Pyramiding Effect on Shoot Length and Plant Height in Rice (Oryza sativa L.)
作者:Dong, Jingfang;Ma, Yamei;Hu, Haifei;Wang, Jian;Yang, Wu;Fu, Hua;Zhang, Longting;Chen, Jiansong;Zhou, Lian;Li, Wenhui;Nie, Shuai;Zhao, Junliang;Liu, Bin;Yang, Tifeng;Zhang, Shaohong;Zhang, Longting;Liu, Ziqiang
关键词:Shoot Length; Plant Height; Causal gene; Allele Mining; Pyramiding Effect; Rice
-
Carbon nanospheres bridging in perovskite quantum dots/BiOBr: An efficient heterojunction for high-performance photoelectrochemical sensing of deoxynivalenol
作者:Chen, Miao-Miao;Liu, Yuan;Jiang, Jun;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Chen, Miao-Miao;Liu, Yuan;Jiang, Jun;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Chen, Miao-Miao;Liu, Yuan;Jiang, Jun;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Chen, Miao-Miao;Liu, Yuan;Jiang, Jun;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Jiang, Jun;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Zhang, Qi;Li, Peiwu;Tang, Xiaoqian;Zhao, Shuaiqi;Tang, Xiaoqian
关键词:Carbon nanospheres; Perovskite; Heterojunctions; Photoelectrochemical immunosensors; Deoxynivalenol
-
Mapping Maize Planting Densities Using Unmanned Aerial Vehicles, Multispectral Remote Sensing, and Deep Learning Technology
作者:Shen, Jianing;Hu, Jingyu;Wang, Jian;Shu, Meiyan;Guo, Wei;Qiao, Hongbo;Yue, Jibo;Wang, Qilei;Zhao, Meng;Liu, Yang;Niu, Qinglin;Niu, Qinglin
关键词:maize planting density; object detection; machine learning; vegetation index; YOLO; GLCM