(228dg) Assessment of Bioseparation Technology Options for Bio-Based Chemicals Generated from Microbial Cultures | AIChE

(228dg) Assessment of Bioseparation Technology Options for Bio-Based Chemicals Generated from Microbial Cultures


Yenkie, K. M. - Presenter, University of Illinois, Chicago
Wu, W., University of Wisconsin – Madison
Maravelias, C., Princeton University
Assessment of bioseparation technology options for bio-based chemicals
generated from microbial cultures

Kirti M. Yenkie, WenZhao Wu,
Christos T. Maravelias*

Department of Chemical and
Biological Engineering,

University of Wisconsin-Madison.

  Abstract Background

The alarming climatic changes
like global warming and constantly declining fossil reserves have established
the need for alternative sources which are environmentally benign and
sustainable. Production of chemicals from microbial sources is one such
alternative that has potential to generate carbon neutral cycle (Fresewinkel et al., 2014). However, along with satisfaction of these crucial requirements their production must also be commercially viable. The separation of bio-based chemicals contained in process streams from microbial cultivations prove to be most challenging and can contribute to more than 70% of the total production costs. Thus, the economic feasibility is dependent upon the efficient synthesis of separation systems.

Separation synthesis requires
evaluation of several alternative technologies performing similar tasks, since
their suitability is affected by variations in parameters like separation unit efficiency,
input stream characteristics and desired product specifications. A sensitivity
study involving potential variations in these parameters can provide a general
guideline for technology selection while synthesizing separation systems. Previous
work in this area has focused on the performance of individual technologies and
has provided some general guidelines regarding their applicability to
microalgae harvesting (Molina Grima et al., 2003) and biofuels (Brennan and Owende, 2010). However, a simultaneous and detailed quantitative analysis for synthesis and evaluation of bioseparation systems is not available. Methodology

We develop a bioseparation
superstructure framework involving four stages: (i) cell treatment, (ii)
product phase isolation, (iii) concentration and purification and (iv)
refinement. Each stage comprises of technology alternatives for tasks like
biomass harvesting, cell disruption and product recovery based on their
separation principles. Then, we generate reduced superstructures for specific
product categories based on their physicochemical properties (solubility,
density and volatility), physical state (solid or liquid), localization
(extracellular or intracellular) and intended use (commodity or specialty). We
generate a base case by assuming nominal values for parameters like plant
capacity, product titer, desired purity, technology parameters, cost of raw
materials, chemicals and separating agents from relevant literature (Choi and Lee, 1999; Mooibroek et al., 2007) and process simulation packages (SuperPro Designer) for economic assessment. We have a combinatorial optimization problem with an objective to minimize the overall bioseparation costs. The solution provides the cost distribution in each bioseparation stage and identifies the technologies selected.

However, technologies
performing intended tasks and their suitability for a specific product can vary
depending on stream characteristics (biomass titer, product concentration), technology
performance indices (efficiencies) or matching parameters (like mass separating
agents contributing to raw material costs or energy separating agents
contributing towards utility requirements) and final specifications (product
purity and recovery). Hence, we perform an optimization based sensitivity
analysis by varying these critical parameters and study the effects on technology
selection as well as process economics. Results

To illustrate, we present some results for
the product category of intracellular(IN)-insoluble (NSL)-heavy(HV)-solid(SLD)-commodity(CMD)
chemical. The stage-wise cost contribution analysis predicts (Fig 1A) that
stage I-cell treatment is the key cost driver, followed by stage II-product
phase isolation and stage IV-refinement while stage III-concentration and
purification is absent for the base case. We select the task of biomass
harvesting in stage I, which can be performed by sedimentation, centrifugation
and filtration, for sensitivity analysis. The results for variation in
performance indices of centrifugation (efficiency) and filtration (retention
factor) on total separation cost ($/kg product) can be seen in Figure 1B. The
contour lines are horizontal in the region where filtration is selected and
vertical where centrifuge is selected. Threshold values when there is a shift
in technology selection is denoted by the white lines. We observe that total
separation cost can vary from 3.12 to 8.44 $/kg. Thus, maximum improvement that
can be achieved by selecting a suitable biomass harvesting operation is ~32%
when compared to the base case (shown by the black point in Figure 1B).

Figure 1
Results for the product category of intracellular (IN)-insoluble (NSL)-heavy
(HV)-solid (SLD)-commodity (CMD) chemical.

(A) Stage-wise
cost contribution analysis for the base case.

Sensitivity analysis for biomass harvesting task in stage I by varying
performance index of centrifuge (efficiency) and filtration (retention factor). Conclusions

We studied separation systems
for the recovery of chemicals produced via a range of bio-conversions. We
believe that such an analysis will prove valuable in (1) selecting the
chemicals that can be produced economically using bioconversions, and (2) designing
separation processes for bio-based chemicals. The threshold values determined by
our analysis will help in deciding which technology shall be more promising for
a particular task when the information about relevant parameters are known
apriori. Sometimes, a particular technology selected in a previous stage also
influences the technology selection in the following stages. Thus, we can make
an informed decision regarding which technologies should be placed in
conjunction. Most importantly, the proposed framework help us identify some
promising research directions in the area of separations, a topic that has
received limited attention despite its high impact on the economics of
biomass-to-fuels/chemicals strategies.



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