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徐琴琴

副教授博士生导师硕士生导师
性别：女
毕业院校：大连理工大学
学位：博士
所在单位：化工学院
学科：化工过程机械. 流体机械及工程. 安全科学与工程
办公地点：西部校区H315
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[11]徐琴琴.银建中.Direct Growth of Higly Dispersed MnCl24H2O Nanostructures with Different Morphologies on Grapheme in Supercritical CO2[A],The 4th China-France Workshops on Supercritical Fluids,2022
[12]ligen.zhoudan,徐琴琴,Qiao, Guo-Yue,银建中.Effect of different co-solvents on solubility of ILs [Emim]Ac, [Bmim][NTf2] in scCO(2)[J],JOURNAL OF MOLECULAR LIQUIDS,2022,284:102-109
[13]Liu, Yi-Fan.徐琴琴,Cai, Pei,Zhen, Meng-Yuan,Wang, Xin-Yao,银建中.Effects of operating parameters and ionic liquid properties on fabrication of supported ionic liquid membranes based on mesoporous gamma-Al2O3 supports[J],JOURNAL OF MEMBRANE SCIENCE,2022,545:176-184
[14]Qiao, Guoyue.徐琴琴,Wang, Aiqin,zhoudan,银建中.Efficient synthesis of sub-5 nm Ag nanoparticles by the desorption effect of supercritical CO(2)in SBA-15[J],NANOTECHNOLOGY,2022,31(37)
[15]Xiang, Hao-Ming.Sun, Jian-Fei,ligen,徐琴琴,Li, Zhuo-Jian,Quo, Guo-Yue,银建中.Enhancement of a Double Cosolvent on Solubility of [Bmim][Ac] and [Bmim][NTf2] in Supercritical CO2[J],JOURNAL OF CHEMICAL AND ENGINEERING DATA,2022,65(4):1655-1662
[16]Zhang, Qiaozhi.Zhao, Mengjiao,徐琴琴,Ren, Hongrui,银建中.Enhanced Enzymatic Hydrolysis of Sorghum Stalk by Supercritical Carbon Dioxide and Ultrasonic Pretreatment[J],APPLIED BIOCHEMISTRY AND BIOTECHNOLOGY,2022,188(1):101-111
[17]徐琴琴.Zhao, Meng-Jiao,Yu, Zhen-Zi,银建中,Li, Guo-Min,Zhen, Meng-Yuan,Zhang, Qiao-Zhi.Enhancing enzymatic hydrolysis of corn cob, corn stover and sorghum stalk by dilute aqueous ammonia combined with ultrasonic pretreatment[J],INDUSTRIAL CROPS AND PRODUCTS,2022,109:220-226
[18]Zhao, Meng-Jiao.徐琴琴,Zhen, Meng-Yuan,Li, Guo-Min,xugang,银建中.Enhancing enzyme hydrolysis of Sorghum stalk by CO2-pressurized liquid hot water pretreatment[J],Environmental Progress Sustainable Energy,2022,36(1):208-213
[19]徐琴琴.Zhao, Wei,Zhi, Jia-Tao,银建中.Exfoliation of graphite in CO2 expanded organic solvents combined with low speed shear mixing[J],炭素,2022,135:180-186
[20]银建中.徐琴琴,魏炜,Wanw, AQ.Experiments and numerical simulations of supercritical fluid extraction for Hippophae rhamnoides L seed oil based on artificial neural networks[J],INDUSTRIAL ENGINEERING CHEMISTRY RESEARCH,2022,44(19):7420-7427

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