Mathematical Modelling and Optimisation of Hydrogen Production from Photo-Fermentation in Microbial Electrolysis Cell using Sago Waste with Neural Network Algorithm
Development of renewable energy is necessary as fossil fuels are bound to run out and hydrogen is an attractive alternative to replace fossil fuels because it is renewable and pollution-free. Microbial electrolysis cell (MEC) is a good method for hydrogen production from biomass. As a consequence of...
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| 格式: | Final Year Project Report |
| 語言: | English |
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Universiti Malaysia Sarawak (UNIMAS)
2020
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| 主題: | |
| 在線閱讀: | http://ir.unimas.my/id/eprint/34673/2/THEN%20MUN%20YIP.pdf http://ir.unimas.my/id/eprint/34673/ |
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| 總結: | Development of renewable energy is necessary as fossil fuels are bound to run out and hydrogen is an attractive alternative to replace fossil fuels because it is renewable and pollution-free. Microbial electrolysis cell (MEC) is a good method for hydrogen production from biomass. As a consequence of increased production of sago in Sarawak, sago waste has been rising over the years and cause negative environmental impact if sago waste is not properly treated. Thus, MEC is good where it can produce biohydrogen as a source of energy and at the same time, minimising the disposal problem of sago waste. For this project, mathematical modelling will be done to study the hydrogen production in MEC in-depth as the reaction in MEC is highly complex and non-linear making it hard to predict. |
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