| 1. |
- Jin, Yanghao, et al.
(författare)
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A novel three-stage ex-situ catalytic pyrolysis process for improved bio-oil yield and quality from lignocellulosic biomass
- 2024
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Ingår i: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 295
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Tidskriftsartikel (refereegranskat)abstract
- This study aims to improve the quality and yield of bio-oil produced from ex-situ catalytic pyrolysis of lignocellulosic biomass (sawdust) using a combination of stage catalysts with Al-MCM-41, HZSM-5, and ZrO2. The research employed various methods, including thermogravimetric analysis (TGA), differential scanning calorimetry, bench-scale experiments, and process simulations to analyze the kinetics, thermodynamics, products, and energy flows of the catalytic upgrading process. The introduction of ZrO2 enhances the yield of monoaromatic hydrocarbons (MAHs) in heavy organics. Compared with the dual-catalyst case, the MAHs yield escalates by approximately 344% at a catalyst ratio of 1:3:0.25. Additionally, GC-MS data indicate that the incorporation of ZrO2 promotes the deoxygenation reaction of the guaiacol compound and the oligomerization reactions of PAHs. The integration of ZrO2 as the third catalyst enhances the yield of heavy organics significantly, achieving 16.85% at a catalyst ratio of 1:3:1, which increases by nearly 35.6% compared to the dual-catalyst case. Also, the addition of ZrO2 as the third catalyst enhanced the energy distribution in heavy organics. These findings suggest that the combination of these catalysts improves the fuel properties and yields of the bio-oil.
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| 2. |
- Wang, Shule, 1994-, et al.
(författare)
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A machine learning model to predict the pyrolytic kinetics of different types of feedstocks
- 2022
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Ingår i: Energy Conversion and Management. - : Elsevier BV. - 0196-8904 .- 1879-2227. ; 260, s. 115613-
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Tidskriftsartikel (refereegranskat)abstract
- An in-depth knowledge of pyrolytic kinetics is vital for understanding the thermal decomposition process. Numerous experimental studies have investigated the kinetic performance of the pyrolysis of different raw materials. An accurate prediction of pyrolysis kinetics could substantially reduce the efforts of researchers and decrease the cost of experiments. In this work, a model to predict the mean values of model-free activation energies of pyrolysis for five types of feedstocks was successfully constructed using the random forest machine learning method. The coefficient of determination of the fitting result reached a value as high as 0.9964, which indicates significant potential for making a quick initial pyrolytic kinetic estimation using machine learning methods. Specifically, from the results of a partial dependence analysis of the lignocellulose-type feedstock, the atomic ratios of H/C and O/C were found to have negative correlations with the pyrolytic activation energies. However, the effect of the ash content on the activation energy strongly depended on the organic component species present in the lignocellulose feedstocks. This work confirms the possibility of predicting model-free pyrolytic activation energies by utilizing machine learning methods, which can improve the efficiency and understanding of the kinetic analysis of pyrolysis for biomass and fossil investigations.
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| 3. |
- Wang, Shule, et al.
(författare)
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Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes
- 2023
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Ingår i: Communications Chemistry. - : Springer Nature. - 2399-3669. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Feedstock properties play a crucial role in thermal conversion processes, where understanding the influence of these properties on treatment performance is essential for optimizing both feedstock selection and the overall process. In this study, a series of van Krevelen diagrams were generated to illustrate the impact of H/C and O/C ratios of feedstock on the products obtained from six commonly used thermal conversion techniques: torrefaction, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, pyrolysis, and gasification. Machine learning methods were employed, utilizing data, methods, and results from corresponding studies in this field. Furthermore, the reliability of the constructed van Krevelen diagrams was analyzed to assess their dependability. The van Krevelen diagrams developed in this work systematically provide visual representations of the relationships between feedstock and products in thermal conversion processes, thereby aiding in optimizing the selection of feedstock and the choice of thermal conversion technique.
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| 4. |
- Wen, Yuming, et al.
(författare)
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H2-rich syngas production from pyrolysis of agricultural waste digestate coupled with the hydrothermal carbonization process
- 2022
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Ingår i: Energy Conversion and Management. - : Elsevier BV. - 0196-8904 .- 1879-2227. ; 269, s. 116101-116101
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Tidskriftsartikel (refereegranskat)abstract
- A novel process to produce a H2-rich syngas from a high moisture-containing agricultural waste digestate is proposed. This process combines the use of hydrothermal carbonization (HTC), dewatering, pyrolysis, and catalytic reforming. Due to the feature of the high moisture content in the digestate, the effect of the HTC and dewatering on the process performance is of interest, and four scenarios were considered. Furthermore, three pyrolytic temperatures were chosen to understand the effect of pyrolysis conditions on the produced H2-rich syngas. A life cycle assessment was conducted to investigate the environmental impact of the proposed process. Results show that the application of HTC technology, increases the process efficiency, produces less syngas from one ton of digestate, lowers the cumulative energy demand and the negative carbon emissions. When the dewatering technology is used, the syngas yield is promoted but the H2 concentration in the syngas is reduced. The H2 to CO molar ratio reaches the maximum value of 9.2 when using a 450 ˚C pyrolysis temperature, by only using HTC. When the combining process of HTC and dewatering is used, it results in the highest process efficiency, but the smallest relative negative CO2 equivalent emissions by treating one ton of dry digestate.
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| 5. |
- Wen, Yuming, et al.
(författare)
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Pyrolysis of engineered beach-cast seaweed : Performances and life cycle assessment
- 2022
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Ingår i: Water Research. - : Elsevier BV. - 0043-1354 .- 1879-2448. ; 222
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Tidskriftsartikel (refereegranskat)abstract
- The blooming of beach-cast seaweed has caused environmental degradation in some coastal regions. Therefore, a proper treating and utilizing method of beach-cast seaweed is demanded. This study investigated the potential of producing power or biofuel from pyrolysis of beach-cast seaweed and the effect of the ash-washing process. First, the raw and washed beach-cast seaweeds (RS and WS) were prepared. Thereafter, thermogravimetric analysis (TG), bench-scale pyrolysis experiment, process simulation, and life cycle assessment (LCA) were conducted. The TG results showed that the activation energies of thermal decomposition of the main organic contents of RS and WS were 44.23 and 58.45 kJ/mol, respectively. Three peak temperatures of 400, 500, and 600 degrees C were used in the bench-scale pyrolysis experiments of WS. The 600 degrees C case yielded the most desirable gas and liquid products. The bench-scale pyrolysis experiment of RS was conducted at 600 degrees C as well. Also, an LCA was conducted based on the simulation result of 600 degrees C pyrolysis of WS. The further process simulation and LCA results show that compare to producing liquid biofuel and syngas, a process designed for electricity production is most favored. It was estimated that treating 1 ton of dry WS can result in a negative cumulative energy demand of -2.98 GJ and carbon emissions of -790.89 kg CO2 equivalence.
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