Synthesis of monolithic zirconia aerogel via a nitric acid assisted epoxide addition method

RSC Advances ◽  
2014 ◽  
Vol 4 (60) ◽  
pp. 31666 ◽  
Author(s):  
Liang Zhong ◽  
Xiaohong Chen ◽  
Huaihe Song ◽  
Kang Guo ◽  
Zijun Hu
RSC Advances ◽  
2018 ◽  
Vol 8 (72) ◽  
pp. 41603-41611 ◽  
Author(s):  
Benxue Liu ◽  
Min Gao ◽  
Xiaochan Liu ◽  
Yongshuai Xie ◽  
Xibin Yi ◽  
...  

Large-sized, high-transparent and monolithic ZrO2 aerogel was prepared by a synthetic zirconium precursor.


RSC Advances ◽  
2015 ◽  
Vol 5 (102) ◽  
pp. 84280-84283 ◽  
Author(s):  
Zhiyi Zhang ◽  
Qiuyue Gao ◽  
Yi Liu ◽  
Chunmei Zhou ◽  
Mingjia Zhi ◽  
...  

Citric acid was used as the cheap and environmental friendly gelation accelerator for preparation of monolithic zirconia aerogel.


Author(s):  
N.C. Lyon ◽  
W. C. Mueller

Schumacher and Halbsguth first demonstrated ectodesmata as pores or channels in the epidermal cell walls in haustoria of Cuscuta odorata L. by light microscopy in tissues fixed in a sublimate fixative (30% ethyl alcohol, 30 ml:glacial acetic acid, 10 ml: 65% nitric acid, 1 ml: 40% formaldehyde, 5 ml: oxalic acid, 2 g: mecuric chloride to saturation 2-3 g). Other workers have published electron micrographs of structures transversing the outer epidermal cell in thin sections of plant leaves that have been interpreted as ectodesmata. Such structures are evident following treatment with Hg++ or Ag+ salts and are only rarely observed by electron microscopy. If ectodesmata exist without such treatment, and are not artefacts, they would afford natural pathways of entry for applied foliar solutions and plant viruses.


1916 ◽  
Vol 82 (2122supp) ◽  
pp. 150-150
Author(s):  
R. Seligman ◽  
P. Williams
Keyword(s):  

Author(s):  
Agung Eddy Suryo Saputro ◽  
Khairil Anwar Notodiputro ◽  
Indahwati A

In 2018, Indonesia implemented a Governor's Election which included 17 provinces. For several months before the Election, news and opinions regarding the Governor's Election were often trending topics on Twitter. This study aims to describe the results of sentiment mining and determine the best method for predicting sentiment classes. Sentiment mining is based on Lexicon. While the methods used for sentiment analysis are Naive Bayes and C5.0. The results showed that the percentage of positive sentiment in 17 provinces was greater than the negative and neutral sentiments. In addition, method C5.0 produces a better prediction than Naive Bayes.


2015 ◽  
Vol 53 (6) ◽  
pp. 426-431 ◽  
Author(s):  
Jae-Woo Ahn ◽  
Seong-Hyung Ryu ◽  
Tae-Young Kim
Keyword(s):  

2015 ◽  
Vol 19 (0) ◽  
pp. 55-58
Author(s):  
Zhen-xue Liu ◽  
◽  
Zhong-xue Gan ◽  
Jun-jie Gu ◽  
Qing-feng Song

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