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Biomass is an organic substance widely available in nature as a fresh or a waste material considered renewable energy that aligns with the zero-carbon scheme to reduce the dependency on fossil fuels. However, after conversion, biomass's physical or chemical properties highly affect biofuel characteristics. A variety of instruments can be used to figure out biofuel reactivity. Considering commonly adopted instruments, thermogravimetric analysis (TGA) is a simple, fast, and efficient way to determine biofuel properties and reactivity. The TGA method has the capability to analyze the biofuel properties (proximate analysis: moisture, volatile matter, fixed carbon, and ash) and combustion features of biomass (such as ignition, reactivity, etc). Most importantly, the TG curvatures (TGA and DTG) reveal the behavior of the biofuel during the thermodegradation process. As a consequence, the quality and quantity analyses on the biofuel properties and reactivity can be investigated comprehensively. Moreover, some TGA integration with artificial intelligence (AI) has been studied to better understand biofuel management and technology for future development. The outcome for the TGA-AI integration may obtain an excellent result with the fit quality value R2 >95 %. This study aims to comprehensively review relevant research using TGA to analyze the lignocellulosic biofuel properties and reactivity. Moreover, the discussion in this study is extended to perspective, challenges, and future work. |
