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Comprehensive modeling of photo-fermentation process for prediction of hydrogen production

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논문

Comprehensive modeling of photo-fermentation process for prediction of hydrogen production

학술지

International journal of hydrogen energy

저자명

Akbari, Leila; Mahmoodzadeh Vaziri, Behrooz

초록

<P><B>Abstract</B></P> <P>Hydrogen production via modern technologies and without using fossil fuels has been found considerably important recently. Photo-fermentation is introduced as one of the most effective methods without high risk for bio-hydrogen production. In this study, comprehensive modeling and simulation of bio-hydrogen production is carried out through photo-fermentation process. In this way, different applicable models are considered to predict the kinetics of microbial growth. Also, new modified mathematical models are particularly proposed for photo-fermentation to forecast the specific growth rate of microorganisms, substrate consumption and hydrogen production rates. Various combinations of the models are applied and predictions of the models are validated by experimental data related to the growth of <I>Rhodobacter Sphaeroides</I> on malate as the substrate. The combination, entitled as <I>MVA1,</I> is introduced as the best one to predict kinetic factors in photo-fermentation. The presented models can be used as an excellent starting point to accomplish experimental and industrial works.</P> <P><B>Highlights</B></P> <P> <UL> <LI> New modified models are presented in accordance with photo fermentation. </LI> <LI> Inhibitory effects of biomass, light, malate and H<SUB>2</SUB> amount assessed simultaneously. </LI> <LI> The combination models are able to express the effect of vital factors properly. </LI> <LI> Model predictions are highly in accordance with experimental data. </LI> </UL> </P>

발행연도

2017

발행기관

Elsevier

ISSN

0360-3199

ISSN

1879-3487

42

21

페이지

pp.14449-14457

주제어

Bio-hydrogen; Photo-fermentation; Modeling; Specific growth rate; Substrate consumption rate; Hydrogen production rate

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1 2023-12-11

논문; 2017-05-01

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