We are aware of an issue with certificate availability and are working diligently with the vendor to resolve. The vendor has indicated that, while users are unable to directly access their certificates, results are still being stored. Certificates will be available once the issue is resolved. Thank you for your patience.

(580e) General Bio-Separation Superstructure Optimization Framework

Wu, W., University of Wisconsin – Madison
Maravelias, C. T., University of Wisconsin-Madison
Yenkie, K., Vishwamitra Research Institute

General Bio-Separation Superstructure
Optimization Framework

, Kirti Yenkie, Christos T.

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.

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

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.


[1] Gavrilescu, M. & Chisti, Y.,
2005. Biotechnology- a sustainable alternative for chemical industry. Biotechnology
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.