Integrating reaction pathways and downstream separation network for optimal sustainable process route selection

Reducing the environmental impact of chemical production has become a critical objective due to carbon emission regulations and the challenges the carbon market poses. Downstream separation network optimization, which can improve process sustainability by using complex heat exchanger networks, applying advanced separation techniques, optimizing the design/operating parameters, etc., has been researched for many years. However, most optimization work focuses solely on downstream separation sections without considering the selection of raw materials and different reaction pathways. This work aims to develop a mixed integer nonlinear programming (MINLP) optimization model, which integrates reaction pathway selection and downstream separation optimization, to select the optimal sustainable process route for utilizing raw materials or producing products. The objective is to maximize/minimize the process profit/cost. Decision variables such as binary variables, which represent the selection of separation task, key component, heating utility, and continuous variables, which influence the separation mass/energy balance, are considered. By giving parameters like reaction conversion rate, selectivity, and raw material/product price, this optimization model can identify the optimal process route for producing a target product or utilizing a raw material. The optimization model was applied to two case studies: one-step isobutylene and methanol utilization and two-step 1,4-butanediol (BDO) production. The process routes, using isobutylene for pivalic acid production and methanol for gasoline production, have the highest process profit per carbon emission. And the process route, which uses acetylene for BDO production, leads to minimum process cost.