Manufacturing butanol, ethanol, and acetone through grain fermentation has been attracting increasing research interest. In the production of these chemicals from fermentation, the cost of product recovery constitutes the major portion of the total production cost. Developing cost-effective flowsheets for the downstream processing is, therefore, crucial to enhancing the economic viability of this manufacturing method. The present work is concerned with the synthesis of such a process that minimizes the cost of the downstream processing. At the outset, a wide variety of processing equipment and unit operations, i.e., operating units, is selected for possible inclusion in the process. Subsequently, the exactly defined superstructure with minimal complexity, termed maximal structure, is constructed from these operating units with the rigorous and highly efficient graph-theoretic method for process synthesis based on process graphs (P-graphs). Finally, the optimal and near-optimal flowsheets in terms of cost are identified.

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A novel holistic approach is proposed for process retrofitting. Unlike conventional approaches, the proposed approach totally resynthesizes the entire process by incorporating the operating units with enhanced performances. As such, it can take into account all possible outcomes, including the inevitable restructuring of the flowsheet's network structure. Naturally, the proposed approach can be executed by resorting to the efficient graph-theoretic method based on P-graphs that have been originally devised for synthesizing virgin processes; nevertheless, the approach does not require the enormous effort involved in exhaustively identifying plausible operating units in synthesizing virgin processes. With the combinatorial feasibility of most operating units largely predetermined, the approach detects, with extraordinary speed, any changes in the flowsheet's network structure incurred by retrofitting. The efficacy of the approach is demonstrated by applying it to the retrofitting of a conventional downstream process for the biochemical production of butanol through the incorporation of newly identified adsorbing units.

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A highly effective algorithmic method is proposed for optimally synthesizing an azeotropic-distillation system from an extensive set of candidate operating units, i.e., functional units. The method has been derived by resorting to the graph-theoretic approach to process-network synthesis based on process graphs (P-graphs); it also resorts to the methodology established in our previous contribution for dividing the residue curve map (RCM) of a material system, i.e., mixture, to be separated into partitioned materials. This allows the entire space of the RCM to be taken into account in composing networks of candidate operating units, thereby preventing the localization of search. Moreover, the RCM is transformed into the flow-rate map, where any material is quantitatively defined by the molar flow rates of its components instead of the concentrations as in the RCM. This renders it possible to eliminate the nonlinearity in the governing equations of the candidate operating units. The efficacy of the method is amply demonstrated through the well-known example of separating ethanol from its aqueous solution with toluene as the entrainer. The method is applicable to other complex processes with phase transition, and/or phase separation, e.g., crystallization, extraction, reactive distillation, and their combinations.

The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by utilizing the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the creators of the P-graph framework at the University of Pannonia. The integration of supply chain design and sustainability is the main focus of this collaboration. The P-graph framework provides a mathematically rigorous procedure for synthesizing optimal and alternative suboptimal networks subject to multiple objectives and constraints, which include profitability and sustainability in the proposed methodology. Specifically, to evaluate the sustainability of a given process under construction including its supply chain, sustainability metrics are incorporated into the design procedure. The proposed methodology is demonstrated with the optimal design of a supply chain for providing heat and electric power to an agricultural region with relatively limited land area where agricultural wastes can potentially be recovered as renewable resources. The objective functions for optimization comprise the profit and the ecological footprint. The results of the study indicate that, compared to using electricity from the grid and/or natural gas, using renewable energy resources can yield substantial cost reductions of up to 5%, as well as significant ecological footprint reductions of up to 77%. It may, therefore, be possible to design more sustainable supply chains that are both cost-effective and less environmentally damaging.