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Microbial fuel cell performance improvement by optimizing parameters - Soumya Pandit,Debarata Das,Makarand Madhao Ghangrekar

englanti
2017-06-07
71,34 € 109,75 €

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Toimitus 12-18 arkipäivässä

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With ever increasing populations, the global demand of energy is expected to increase significantly in the near future. In recent years, one of the promising approaches to this quest is the Microbial fuel cell (MFC) technology. MFCs are unique in their ability to use microbes to convert the energy stored in the feedstock directly into electricity without the need for combustion. The present research work fo ... Täydellinen kuvaus

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With ever increasing populations, the global demand of energy is expected to increase significantly in the near future. In recent years, one of the promising approaches to this quest is the Microbial fuel cell (MFC) technology. MFCs are unique in their ability to use microbes to convert the energy stored in the feedstock directly into electricity without the need for combustion. The present research work focuses mainly on improving the performance of different components in the MFC. A detailed description on microbial fuel cell technology and their applications have been discussed. From the present studies, it may be inferred that the power density of the MFCs can be improved significantly by finding out the suitable operational parameters. This book is an endeavour towards showcasing that power generation in MFCs can be systematically incremented by identifying and optimizing the various process parameters. This book with its easy to follow instructions will provide the readers a direction towards an effective design and operation of MFCs with its widespread applications which can be prescribed to students and professionals interested in entering the field.

Lisätietoja

Kirjoittaja Soumya Pandit, Debarata Das, Makarand Madhao Ghangrekar
Julkaisija LAP LAMBERT Academic Publishing
Julkaisuvuosi 2017
Kannen tyyppi Pehmeäkantinen
EAN 9783330088160
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Arvostelet: Microbial fuel cell performance improvement by optimizing parameters
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71,34 € 109,75 €