Abstract
The biomass to biofuel process requires both initial conversion or densification of raw biomass followed by an upgrading step which can address high oxygen content, low hydrogen content, and stability prior to being considered petroleum compatible in a traditional refinery for processing into gasoline or diesel. Processing strategies exist with the goal of developing biofuels independently of petroleum product, though co-processing or refining is considered as the most viable path to commercialization. Upgrading processes are intensive, thus addressing issues to commercialization of biomass based biofuel can be accomplished through optimization of existing conversion i.e., CFP, and altering are development of new methods to treat bio-oil for aforementioned issues.
The paper herein presents methods for addressing CFP optimization in various ways:via cyber physical modeling and application of AI methodology to solve complex issues and chemical reactions, in additional to outlining existing bio-oil treatments and experimenting with catalytic transfer hydrogenation and blending as a means for upgrading, or in the case of blending, skipping the upgrading process altogether. Both biomass to bio-oil conversion, and post conversion upgrading processes represent a major stumbling block to commercialization and success of 2nd generation biofuels as a whole, thus addressing both steps in the supply chain represents a significant gain in advancing the state of technology of the biofuel production process. The research presented herein aims to outline the existing state of technology, and provides several mechanisms for addressing the deficiencies both qualitatively and analytically. In addition to innovative advancements in biofuel production, Appendix B and C outline potential ways to optimize biomass to bio-oil conversion using AI and integrated system design.