@book{
 title = {Sustainable design and synthesis of algal biorefinery for biofuel production},
 type = {book},
 year = {2014},
 source = {Computer Aided Chemical Engineering},
 identifiers = {[object Object]},
 keywords = {[Algal biorefinery, Biological carbon sequestratio},
 volume = {33},
 id = {f78a0984-0a72-3a83-bdf3-d4cd978432ec},
 created = {2016-08-19T13:20:23.000Z},
 file_attached = {false},
 profile_id = {f27171f8-b200-3870-9028-dcb6a084733d},
 last_modified = {2017-03-25T02:01:24.507Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We develop a new process superstructure of algal biorefinery for biological carbon sequestration and hydrocarbon biofuel production that encompasses off-gas purification, algae cultivation, harvesting and dewatering, lipid extraction, remnant treatment, biogas utilization and algal oil upgrading stages. Multiple technology alternatives are considered in the process superstructure, including direct off-gas and purified carbon dioxide by monoethanolamine process; open pond and three types of photobioreactors for algae culture; flotation thickening, filtration and centrifugation to dehydrate algal slurry; hexane and n-butane as lipid extractant; anaerobic digestion and catalytic gasification to exploit algal remnant; two catalysts, Co-Mo and Ni-Mo in the hydroprocessing reactor. This process reuses all the produced CO2 from the processing units that leads to zero direct greenhouse gas emission of the entire process. Based on the superstructure, we propose a mixed-integer nonlinear programming model to minimize the unit carbon sequestration and utilization cost. We further apply a tailored branch-and-refine algorithm based on successive piecewise linear approximation to globally optimize problem efficiently. The optimization results indicate clear economic and environmental advantage when the feed gas is limited only during the day. ? 2014 Elsevier B.V.},
 bibtype = {book},
 author = {Gong, J. and You, F.}
}

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