Evidence map›Paper›PMID 28503196›Full record

ArticleBiotechnology for biofuels2017

Synthesis and analysis of separation networks for the recovery of intracellular chemicals generated from microbial-based conversions.

Kirti M Yenkie, Wenzhao Wu, Christos T Maravelias

Abstract read
In one paragraph

Article in Biotechnology for biofuels, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kirti M YenkieDepartment of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691 USA.
Wenzhao WuDepartment of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691 USA.
Christos T MaraveliasDepartment of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBioseparations can contribute to more than 70% in the total production cost of a bio-based chemical, and if the desired chemical is localized intracellularly, there can be additional challenges associated with its recovery. Based on the properties of the desired chemical and other components in the stream, there can be multiple feasible options for product recovery. These options are composed of several alternative technologies, performing similar tasks. The suitability of a technology for a particular chemical depends on (1) its performance parameters, such as separation efficiency; (2) cost or amount of added separating agent; (3) properties of the bioreactor effluent (e.g., biomass titer, product content); and (4) final product specifications. Our goal is to first synthesize alternative separation options and then analyze how technology selection affects the overall process economics. To achieve this, we propose an optimization-based framework that helps in identifying the critical technologies and parameters.

resultsWe study the separation networks for two representative classes of chemicals based on their properties. The separation network is divided into three stages: cell and product isolation (stage I), product concentration (II), and product purification and refining (III). Each stage exploits differences in specific product properties for achieving the desired product quality. The cost contribution analysis for the two cases (intracellular insoluble and intracellular soluble) reveals that stage I is the key cost contributor (>70% of the overall cost). Further analysis suggests that changes in input conditions and technology performance parameters lead to new designs primarily in stage I.

conclusionsThe proposed framework provides significant insights for technology selection and assists in making informed decisions regarding technologies that should be used in combination for a given set of stream/product properties and final output specifications. Additionally, the parametric sensitivity provides an opportunity to make crucial design and selection decisions in a comprehensive and rational manner. This will prove valuable in the selection of chemicals to be produced using bioconversions (bioproducts) as well as in creating better bioseparation flow sheets for detailed economic assessment and process implementation on the commercial scale.

Indexed as

Cost contributionDownstream separationOptimizationPhysical propertyTechnology selectionThreshold value

Identifiers

PMID28503196
PMCPMC5422901

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.