Lignin is a high-volume byproduct from the pulp and paper industry and is currently burned to generate electricity and process heat. The industry has been searching for high value-added uses of lignin to improve the process economics. In addition, battery manufacturers are seeking nonfossil sources of graphitic carbon for environmental sustainability. In this work, lignin (which is a cross-linked polymer of phenols, a component of biomass) is converted into graphitic porous carbon using a two-step conversion. Lignin is first carbonized in water at 300 °C and 1500 psi to produce biochar, which is then graphitized using a metal nitrate catalyst at 900–1100 °C in an inert gas at 15 psi. Graphitization effectiveness of three different catalystsiron, cobalt, and manganese nitratesis examined. The product is analyzed for morphology, thermal stability, surface properties, and electrical conductivity. Both temperature and catalyst type influenced the degree of graphitization. A good quality graphitic carbon was obtained using catalysis by Mn­(NO3)2 at 900 °C and Co­(NO3)2 at 1100 °C.

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The predictive capability of the Vignes equation is limited, with considerable deviations encountered in a number of systems. A modification of this expression is developed accounting for solution viscosity. Comparison with data for a large number of known systems shows that this modified version improves the over-all predictability. The concept of segmental diffusion is used to explain the results for mixtures of n-alkanes.

The integrated biorefinery has the opportunity to provide a strong, self‐dependent, sustainable alternative for the production of bulk and fine chemicals, e.g., polymers, fiber composites and pharmaceuticals as well as energy, liquid fuels, and hydrogen. Although most of the fundamental processing steps involved in biorefining are well‐known, there is a need for a methodology capable of evaluating the integrated processes in order to identify the optimal set of products and the best route for producing them. The complexity of the product allocation problem for such processing facilities demands a process systems engineering approach utilizing process integration and mathematical optimization techniques to ensure a targeted approach and serve as an interface between simulation work and experimental efforts. The objective of this work is to assist the bioprocessing industries in evaluating the profitability of different possible production routes and product portfolios while maximizing stakeholder value through global optimization of the supply chain. To meet these ends, a mathematical optimization based framework is being developed, which enables the inclusion of profitability measures and other technoeconomic metrics along with process insights obtained from experimental as well as modeling and simulation studies. © 2007 American Institute of Chemical Engineers Environ Prog, 2007