| 1. |
- Chen, Xu, et al.
(författare)
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Catalytic fast pyrolysis of biomass to produce furfural using heterogeneous catalysts
- 2017
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Ingår i: Journal of Analytical and Applied Pyrolysis. - : Elsevier BV. - 0165-2370 .- 1873-250X. ; 127, s. 292-298
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Tidskriftsartikel (refereegranskat)abstract
- Furfural is a valuable chemical, the production of furfural from renewable biomass resources becomes more attractive in recent years. In this study, biomass fast pyrolysis with heterogeneous catalysts (titanium compounds (TiN, TiO2 and TiOSO4) and metal nitrides (MoN, GaN and VN)) for furfural production was investigated experimentally by means of pyrolysis-gas chromatography/mass-spectrometry (Py-GC/MS). The measurement results indicated that TiN and GaN promoted the furfural compounds production notably mainly through direct decomposition of oligosaccharides. The formation of furfural was promoted when the amount of TiN was increased, and the yield of furfural formed was about 5.5 times the size of that from non-catalytic pyrolysis when TiN/cellulose mass ratio was 4. The furfural yield decreased when the pyrolysis residence time increased from 10 to 30 s, which suggests competitive reactions (formation of 1, 6-anhydro-beta.-D-glucopyranose) against the formation of furfural. TiN, as a catalyst for fast pyrolysis towards furfural production, can be well applied to agriculture biomass residues. Comparing three biomass residues: corncob, wheat straw and cotton stalk, corncob showed higher furfural yield due to the higher holocellulose content, while wheat straw showed higher furfural selectivity.
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| 2. |
- Qi, Tian, et al.
(författare)
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Biomass steam gasification in bubbling fluidized bed for higher-H 2 syngas : CFD simulation with coarse grain model
- 2019
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Ingår i: International Journal of Hydrogen Energy. - : Elsevier BV. - 0360-3199. ; 44:13, s. 6448-6460
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Tidskriftsartikel (refereegranskat)abstract
- A comprehensive coarse grain model (CGM) is applied to simulation of biomass steam gasification in bubbling fluidized bed reactor. The CGM was evaluated by comparing the hydrodynamic behavior and heat transfer prediction with the results predicted using the discrete element method (DEM) and experimental data in a lab-scale fluidized bed furnace. CGM shows good performance and the computational time is significantly shorter than the DEM approach. The CGM is used to study the effects of different operating temperature and steam/biomass (S/B) ratio on the gasification process and product gas composition. The results show that higher temperature enhances the production of CO, and higher S/B ratio improves the production of H 2 , while it suppresses the production of CO. For the main product H 2 , the minimum relative error of CGM in comparison with experiment is 1%, the maximum relative error is less than 4%. For the total gas yield and H 2 gas yield, the maximum relative errors are less than 7%. The predicted concentration of different product gases is in good agreement with experimental data. CGM is shown to provide reliable prediction of the gasification process in fluidized bed furnace with considerably reduced computational time.
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