Fast pyrolysis of biomass for energy and fuels

Bioenergy is now accepted as having the potential to provide the major part of the projected renewable energy provisions of the future as biofuels in the form of gas, liquid or solid fuels or electricity and heat. There are three main routes to providing these biofuels — thermal conversion, biological conversion and physical conversion — all of which employ a range of chemical reactor configurations and process designs. This paper focuses on fast pyrolysis from which the liquid, often referred to as bio-oil, can be used on-site or stored or transported to centralised and/or remote user facilities for utilisation for example as a fuel, or further processing to biofuels and/or chemicals. This offers the potential for system optimisation, much greater economies of scale and exploitation of the concepts of biorefineries. The technology of fast pyrolysis is described, particularly the reactors that have been developed to provide the necessary conditions to optimise performance. The primary liquid product is characterised, as well as the secondary products of electricity and/or heat, liquid fuels and a considerable number of chemicals. The main technical and non-technical barriers to the market deployment of the various technologies are identified and briefly discussed.

Source localization of reaction-diffusion models for brain tumors

We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.