Hydrogen production by the anaerobic fermentation from acid hydrolyzed rice straw hydrolysate

2011 ◽  
Vol 36 (21) ◽  
pp. 14280-14288 ◽  
Author(s):  
Alex C.C. Chang ◽  
Ying-Hsuan Tu ◽  
Ming-Hsiang Huang ◽  
Chyi-How Lay ◽  
Chiu-Yue Lin
RSC Advances ◽  
2018 ◽  
Vol 8 (41) ◽  
pp. 22924-22930 ◽  
Author(s):  
Tao Sheng ◽  
Lei Zhao ◽  
Lingfang Gao ◽  
Wenzong Liu ◽  
Guofeng Wu ◽  
...  

An edible fungal pretreatment of rice straw was proposed for enhanced hydrogen production while reducing the chemical cost for traditional biological hydrogen production from lignocellulose.


2014 ◽  
Vol 171 ◽  
pp. 145-151 ◽  
Author(s):  
Leilei He ◽  
He Huang ◽  
Zhongfang Lei ◽  
Chunguang Liu ◽  
Zhenya Zhang

2010 ◽  
Vol 35 (2) ◽  
pp. 459-468 ◽  
Author(s):  
Yi-Ping Guo ◽  
Shao-Qun Fan ◽  
Yao-Ting Fan ◽  
Chun-Mei Pan ◽  
Hong-Wei Hou

2012 ◽  
Vol 65 (7) ◽  
pp. 1281-1289 ◽  
Author(s):  
Cesar-Arturo Aceves-Lara ◽  
Eric Latrille ◽  
T. Conte ◽  
Jean-Philippe Steyer

This paper describes the use of electrical conductivity for measurement of volatile fatty acids (VFA), alkalinity and bicarbonate concentrations, during the anaerobic fermentation process. Two anaerobic continuous processes were studied: the first was a laboratory reactor for hydrogen production from molasses and the second was a pilot process for anaerobic digestion (AD) of vinasses producing methane. In the hydrogen production process, the total VFA concentration, but not bicarbonate concentration, was well estimated from the on-line electrical conductivity measurements with a simple linear regression model. In the methane production process, the bicarbonate concentration and the VFA concentration were well estimated from the simultaneous on-line measurements of pH and electrical conductivity by means of non-linear regression with neural network models. Moreover, the total alkalinity concentration was well estimated from electrical conductivity measurements with a simple linear regression model. This demonstrates the use of electrical conductivity for monitoring the AD processes.


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