The overall purpose of this work is to develop systematic methodology for the simultaneous design and selection of processes and molecules (materials). A propertybased approach is used to develop an interface between process and molecular design/selection. In particular, we focus on the problem of designing/selecting materials that are used in the context of a recycle/reuse system of process streams and for energy applications. Fresh and recycled resources (e.g., process streams, biomass, solvents, etc.) are integrated with the process to satisfy property-based constraints for the process units and to optimize the usage of the resources and the design of the process. For molecular design, property operators for mixing streams and group contribution methods (GCM) are used to consistently represent process sources, sinks, and different functional groups on the same property-base. For material selection, property based criteria (e.g., heat rate, high heating value, etc.) are used to bridge the process with material. This consistent representation enables the definition of the optimization problem formulation for product design while taking into consideration the recycle/reuse of process streams. In particular, this dissertation addresses four integrated topics. First, a new graphical approach for material targeting and substitution is presented. This graphical approach offers initial solutions and valuable insights that can be effectively used for conceptual design and for initializing mathematical programming techniques. Second, a mathematical optimization approach is developed along with a decomposition-based global solution procedure for material targeting and substitution using property integration. Third, an implementation approach is developed to synthesize the details of a recycle/reuse process network design based on the targets identified through the graphical and/or the mathematical approaches. Finally, property integration techniques are extended to a broader scope which deals with the lifecycle analysis of biomass utilization for energy generation. A generic model is developed to optimize the types and quantities of the feedstocks used to optimize power generation with biomass-fossil fuel co-fed system. Important issues of biomass growth, harvesting, transportation, processing, and disposal are included. Property-based tracking and constraints are included in the analysis. Also, the issues associated with greenhouse gas (GHG) emissions are incorporated in the analysis. Case studies are solved throughout the dissertation to demonstrate the applicability of the developed procedures.

The process industries are characterized by the significant consumption of fresh resources. This is a critical issue, which calls for an effective strategy towards more sustainable operations. One approach that favors sustainability and resource conservation is material recycle and/or reuse. In this regard, an integrated framework is an essential element in sustainable development. An effective reuse strategy must consider the process as a whole and develop plant-wide strategies. While the role of mass and energy integration has been acknowledged as a holistic basis for sustainable design, it is worth noting that there are many design problems that are driven by properties or functionalities of the streams and not by their chemical constituency. In this dissertation, the notion of componentless design, which was introduced by Shelley and El-Halwagi in 2000, was employed to identify optimal strategies for resource conservation, material substitution, and overall process integration. First, the focus was given on the problem of identifying rigorous targets for material reuse in property-based applications by introducing a new property-based pinch analysis and visualization technique. Next, a non-iterative, property-based algebraic technique, which aims at determining rigorous targets of the process performance in materialrecycle networks, was developed. Further, a new property-based procedure for determining optimal process modifications on a property cluster diagram to optimize the allocation of process resources and minimize waste discharge was also discussed. In addition, material substitution strategies were considered for optimizing both the process and the fresh properties. In this direction, a new process design and molecular synthesis methodology was evolved by using the componentless property-cluster domain and Group Contribution Methods (GCM) as key tools in developing a generic framework and systematic approach to the problem of simultaneous process and molecular design.

The process industries such as petrochemicals, chemicals and pharmaceuticals, among others, consume large amounts of material and energy resources. These industries are also characterized by generating enormous amounts of waste that significantly contribute to the pollution of the environment. Integrated process design is a very effective technique in conserving process resources and preventing pollution. The design and environmental constraints may involve a variety of component- and property-based restrictions. To date, most techniques have been developed to handle process constraints which is either composition-based (via mass integration) or property-based. No work has been reported to handle the synthesis of resource conservation network that is governed by both constraints. The objective of this work is to develop a systematic and cost-effective design technique that is aimed at minimizing the consumption of fresh resources and the discharge of pollutants simultaneously. Because of the nature of the component- and property-based constraints, this approach is based on mass and property integration and takes into account the process constraints and also environmental regulations. In this research work, a new approach has been developed to simultaneously address component-based recycle constraints as well as property-based discharge constraints. The proposed optimization technique is intended to minimize the consumption of fresh resources, the pollutant content in the waste streams, and the operational and waste treatment costs. Additionally, a mixed-integer nonlinear programming (MINLP) formulation is solved for a case study of phenol production from cumene hydroperoxyde to illustrate the new problem and devised solution algorithm.