This research goal is to develop a predictive model for the pyrolysis of lignocellulosic biomass. Modeling of pyrolysis of biomass is complex and challenging because of short reaction times, temperatures as high as a thousand degrees Celsius, and biomass of varying or unknown chemical compositions. As such a deterministic model is not capable of representing the pyrolysis reaction system, we have developed our model to overcome these problems. In this research, we use our model to predict the pyrolysis of Pongmia in nitrogen. There are plenty of chemical species in lignocellulosic biomass. However, there are three main chemical species in lignocellulosic biomass, namely cellulose, hemicellulose and lignin. The compositions of these three species vary among the different types of biomass. In the case of plant biomass, the compositions of the three species also depend on where the plant is grown and which part of the plant the species reside; for example the chemical compositions in the leaf can be different from the trunk. This paper is a significant extension of our previous paper (see Nuttapol and Achenie, 2013). Simulation results show that the model can predict 91.82% of pyrolysis of Pongmia in nitrogen correctly. The model holds promise that it can be used to predict the yields in the pyrolysis of other lignocellulosic biomass.

Predictive model for pyrolysis of biomass

248th National Meeting (2014)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.