Abstract
Hydrothermal liquefaction of woody biomass with catalysts was commonly applied in bio-energy research, but the effects of catalyst and solvent on yield and properties of bio-energy are not clear. In this work, the influences of catalyst and solvent on bio-energy production were studied, during which four solvents and three catalysts were used, and the liquefaction parameters were optimized by experimental and Machine learning (ML) method. Results show that the maximum yields of bio-oil and biochar are 65.0% and 32.0%, respectively, and the caloric values of bio-oil and biochar are 31.2 MJ/kg and 26.5 MJ/kg, respectively. Alkaline catalysts and 1,4-butanediol-triethanolamine mix solvent can benefit the bio-energy generation. In addition, a Random Forest (RF) was developed to forecast the yields, and the method performed well with experimental results.
| Original language | English |
|---|---|
| Article number | 126354 |
| Number of pages | 8 |
| Journal | Bioresource Technology |
| Volume | 346 |
| DOIs | |
| Publication status | Published - Feb 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
User-Defined Keywords
- Bio-energy
- Catalyst
- Hydrothermal liquefaction mechanism
- Machine learning
- Woody biomass
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