Functionalized Biochar from the Amazonian Residual Biomass Murici Seed: An Effective and Low-Cost Basic Heterogeneous Catalyst for Biodiesel Synthesis.
Thaissa Saraiva RibeiroMatheus Arrais GonçalvesGeraldo Narciso da Rocha FilhoLeyvison Rafael Vieira da ConceiçãoPublished in: Molecules (Basel, Switzerland) (2023)
This study presents the synthesis of a basic heterogeneous catalyst based on sodium functionalized biochar. The murici biochar (BCAM) support used in the process was obtained through the pyrolysis of the murici seed ( Byrsonimia crassifolia ), followed by impregnation of the active phase in amounts that made it possible to obtain concentrations of 6, 9, 12, 15 and 18% of sodium in the final composition of the catalyst. The best-performing 15Na/BCAM catalyst was characterized by Elemental Composition (CHNS), Thermogravimetric Analysis (TG/DTG), X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FT-IR), Scanning Electron Microscopy (SEM), and Energy Dispersion X-ray Spectroscopy (EDS). The catalyst 15Na/BCAM was applied under optimal reaction conditions: temperature of 75 °C, reaction time of 1.5 h, catalyst concentration of 5% ( w / w ) and MeOH:oil molar ratio of 20:1, resulting in a biodiesel with ester content of 97.20% ± 0.31 in the first reaction cycle, and maintenance of catalytic activity for five reaction cycles with ester content above 65%. Furthermore, the study demonstrated an effective catalyst regeneration process, with the synthesized biodiesels maintaining ester content above 75% for another five reaction cycles. Thus, the data indicate a promising alternative to low-cost residual raw materials for the synthesis of basic heterogeneous catalysts.
Keyphrases
- highly efficient
- room temperature
- electron microscopy
- low cost
- ionic liquid
- reduced graphene oxide
- metal organic framework
- carbon dioxide
- visible light
- high resolution
- sewage sludge
- anaerobic digestion
- stem cells
- gold nanoparticles
- electron transfer
- risk assessment
- quantum dots
- magnetic resonance
- machine learning
- dual energy
- solid state
- data analysis