Abstract
Because of the growing demand for renewable fuels, the production of butanol through acetone-butanol-ethanol (ABE) fermentation of lignocellulosic biomasses is attracting more and more research interest.
The major limit for an industrial-scale production of bio-butanol is the high separation cost, due to the presence of other fermentation products and to its low final concentration in the broth. In fact, microorganisms used in ABE fermentation suffer from product inhibition giving a low ABE final concentration in a batch process. The application of an in-situ recovery technique able to remove butanol during fermentation is a viable solution to solve the problem and improve the profitability of ABE fermentation.
In this context, gas stripping appears to be the most promising and cost-effective separation technique. However, gas stripping usually also removes a large amount of water with butanol and requires a higher energy input because of its lower butanol selectivity if compared to other separation techniques. To improve the performance of the integrated fermentation-gas stripping process for butanol production, optimization of gas stripping conditions, and a better understanding of its effects on the ABE fermentation are needed. Several experimental studies on lab-scale gas stripping units are available in literature, but no process simulation studies are present.
This study regards the synthesis of the optimal process configuration for the in-situ recovery of butanol from a batch fermentation unit, in which the product is recovered from the fermentation broth by means of nitrogen gas stripping. A sensitivity analysis has been performed to study the effect of the gas flowrate on the separation performances. For the studied configuration a detailed simulation using Aspen Hysys® has demonstrated that it is possible to obtain a high selectivity to butanol that leads to a phase separation in the condensate, reducing the cost of the downstream process and indicating the potential and the profitability of the proposed process solution.
