460678 General Bio-Separation Superstructure Optimization Framework

Wednesday, November 16, 2016: 4:43 PM
Carmel I (Hotel Nikko San Francisco)
Wenzhao (Tony) Wu1, Christos T. Maravelias2 and Kirti Yenkie1, (1)Department of Chemical and Biological Engineering, University of Wisconsin – Madison, Madison, WI, (2)Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI

General Bio-Separation Superstructure Optimization Framework

Wenzhao Wu, Kirti Yenkie, Christos T. Maravelias*

Dept. of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706

Recent advances in synthetic biology and metabolic engineering have enabled the production of a range of chemicals using engineered microorganisms1,2. However, despite the intriguing potential, the biological production of high-value chemicals is challenging because it is likely to have low titer and substantial amounts of excreted byproducts, and the purity specifications for high-value chemicals, as opposed to fuels, are rather strict, which means that separation costs are likely to represent a large fraction of the total production cost (more than 70% of total cost3). Thus, the efficient synthesis of bio-separation processes becomes a critical task. Although this synthesis problem has been studied for various chemicals in the past, these studies were mostly performed on a case-by-case basis. There has been limited research towards the development of systematic methods for bio-separations, applicable to all chemical targets. Accordingly, the goal of the present work is to develop a general bio-separation superstructure optimization framework, aiming to provide guidance on the preliminary synthesis of separation networks.

Based on general bio-separation principles and insights obtained from industrial separation processes for specific products, we first identify four separation stages: (1) cell treatment, (2) product phase isolation, (3) concentration and purification, and (4) final refinement. Specifically, cell treatment starts with the harvesting of cells (if the product is intracellular), which can be performed using solid-liquid separation technologies. Cell harvesting is followed by cell disruption to release the intracellular products. The first stage is skipped if the product is extracellular, and the separation starts from the second stage - product phase isolation, where the product-rich phase is isolated. In the concentration and purification stage, we remove large amount of water along with other impurities, by utilizing the differences between the product and the other components on volatility, molecular size, diffusivity, solubility in solvents, etc. In the final refinement stage, we further remove trace impurities and perform refined operations to satisfy special product specifications, such as colorlessness, complete dryness, and crystal form.

Figure 1. Stage-wise analysis of bio-separation processes, including key product properties, attributes, and units for each stage.

Next, we identify key product properties and key attributes that affect the separation processes in each stage, as shown in Figure 1. For example, in Stage 2, the different attributes imply different locations of the product (e.g., “NSL LT” indicates that the product is located at the top, while “SOL” indicates that the product is dissolved in water and evenly distributed in the system), and hence different separation processes. Major units in each stage are also identified.

Then for each stage, we systematically implement a set of connectivity rules4 to develop attribute-specific superstructures. They are subsequently combined to generate a stage-specific superstructure. Finally, all the four stage-specific superstructures are integrated into a general superstructure (shown in Figure 2) that accounts for all types of bio-chemical products.

We further develop a superstructure reduction method to solve product-specific instances, based on product type, unit availability and suitability, case-specific considerations, and final product specifications. The reduced superstructure for an example case is shown in Figure 2, where an EX NSL LT NVL LQD CMD product (see abbreviations in Figure 1) is required to be completely colorless in its final product form, and all units in the general superstructure are available except for filtration.

Figure 2. The general bio-separation superstructure (including the “dimmed” parts), and the reduced superstructure (excluding the dimmed parts) for an example case, where an EX NSL LT NVL LQD CMD product is required to be completely colorless in its final product form, and all units in the general superstructure are available except for filtration.

Finally, a general MINLP optimization model, including short-cut unit models (e.g., Fenske-Underwood equations for distillation unit models) for all types of separation units considered in the framework, is formulated. In the modeling of a specific reduced superstructure, only models of relevant units (which exist in the reduced superstructure) are included.

The proposed framework is applied to three case studies. Each case considers different set of product types, unit availability and suitability, case-specific considerations, and final product specifications. The common objective is to minimize total cost of purifying a dilute product stream (5 wt% concentration) to a product stream with at least 90 wt% purity.

References

[1] Gavrilescu, M. & Chisti, Y., 2005. Biotechnology- a sustainable alternative for chemical industry. Biotechnology advances, Volume 23, pp. 471-499.

[2] Bornscheuer, U. T. & Nielsen, A. T., 2015. Editorial overview: chemical biotechnology: interdisciplinary concepts for modern biotechnological production of biochemicals and biofuels. Current Opinion in Biotechnology, Volume 35, pp. 133-134.

[3] Kiss, A. A., Grievink, J. & Rito-Palomares, M., 2015. A systems engineering perspective on process integration in industrial biotechnology. J Chem Technol Biotechnol, Volume 90, pp. 349-355.

[4] Wu, W., Henao, C. & Maravelias, C., 2016. A Superstructure Representation, Generation and Modeling Framework for Chemical Process Synthesis. AIChE J.


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