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Simultaneous Extraction, Fractionation and Enrichment of Microalgal Triacylglyerides by Exploiting the Tunability of Neat Supercritical Carbon Dioxide Thomas Alan Kwan, Qingshi Tu, and Julie Zimmerman ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.6b02214 • Publication Date (Web): 12 Oct 2016 Downloaded from http://pubs.acs.org on October 20, 2016
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ACS Sustainable Chemistry & Engineering
Simultaneous Extraction, Fractionation and Enrichment of Microalgal Triacylglyerides by Exploiting the Tunability of Neat Supercritical Carbon Dioxide
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Thomas A. Kwan a, Qingshi Tu a and Julie B. Zimmerman a,b
a
5 6 7 8 9 10
Department of Chemical and Environmental Engineering, Yale University, 9 Hillhouse Avenue, New Haven, CT, USA.
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Keywords: solubility separation, biorefinery, energy analysis
12 13
Abstract: Continuous flow supercritical carbon dioxide (scCO2) was used to simultaneously
14
extract, fractionate, and enrich triacylglycerides (TAGs) of different carbon chain lengths and
15
degrees of unsaturation from a 6-component mixture of analytical standards and from Chlorella
16
sp., a common microalgae used as biodiesel feedstock. Evidence is presented that solubility for a
17
given TAG can be enhanced or diminished in the presence of other, dissimilar TAGs due to
18
solute to solute interactions and scCO2 densities.
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Chlorella sp. extracts suggests that TAG mixtures and biomass matrices influence extraction
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behavior with the same TAG behaving differently depending on the starting material. This was
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validated by fitting Chrastil’s solubility parameters to indicate which TAGs were most
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susceptible to solute to solute interactions and neat CO2 density.
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comparing the energy requirements for the downstream purification of TAGs trimyristin (C14:0),
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tripalmitin (C16:0), and trierucin (C22:1) from mixtures extracted with the scCO2 method
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developed here. The model outputs suggest trade-offs for over- or under-enriching certain TAGs
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using neat scCO2. Both the experimental and modeling results demonstrate the potential of
b
School of Forestry and Environmental Studies, Yale University, 195 Prospect St, New Haven, CT, USA. E-mail:
[email protected], Tel: +1-203-432-9703
Comparison of analytical standard and
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A model was developed
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scCO2 to be used as an initial fractionation and enrichment tool whereby the associated energy
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and economic costs of downstream processing, such as distillation, can be reduced.
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1. Introduction Increasing awareness of the adverse environmental, economic, social, and political impacts
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resulting from our dependence on fossil fuels is driving the need to develop greener products and
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processes in support of a bioeconomy.1-3 Development of these clean technologies presents
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significant opportunities for environmental and societal benefit as well as economic growth
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through advancing a renewable chemicals industry.4 However, supplanting petroleum-derived
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fuels and chemicals is challenging as modern refineries efficiently produce a multitude of
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valuable products by utilizing every fraction of crude oil.5 Recent research has aimed to develop
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analogous biorefinery technologies to fully transform biomass into biofuels and useful chemicals
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while realizing returns on energy investments.6 A number of challenges remain in the
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development of biorefineries; chief among them is the efficient and cost-effective separation and
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purification of the targeted compounds.7
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Lipids are one group of compounds that has been targeted for biorefining as they can be used for
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the production of biofuels, renewable chemicals, and dietary supplements.8-9 Due in part to their
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variety of triacylglyceride (TAG) lipid content, including saturated and unsaturated fatty acids
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with medium-chain (C10-C14), long-chain (C16-C18), and very-long-chain (C≥20) lengths,9-10
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microalgae have gained attention as a sustainable feedstock for a multitude of uses. Of particular
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interest is Chlorella sp., a microalgae, that produces reasonable quantities of polyunsaturated
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fatty acids (PUFAs) (e.g., octadecadienoic (C18:2); octadecatrienoic (C18:3)), monounsaturated
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fatty acids (MUFAs) (e.g., hexadecenoic (C16:1); octadecenoic (C18:1)), and saturated fatty 2 ACS Paragon Plus Environment
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acids (e.g., tetradecanoic (C14:0); eicosanoic (C20:0)).11 Depending on chain length and degree
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of unsaturation, lipid preservation or transformation may be desirable. For example, the PUFA,
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octadecatrienoic acid (C18:3) is used directly as a nutritional supplement in infant formulas12 and
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MUFAs, octadecenoic (C18:1) and hexadecenoic (C16:1), can be transformed to alkyl esters via
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transesterification to produce an optimal biodiesel because of their ignition and cold-flow
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properties.13 Saturated medium-chain and long-chain fatty acids are utilized in pharmaceutical,
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chemical, and food applications while upgrading stearic acid (C18:0) and palmitic acid (C16:0)
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to iso-alkanes for transportation fuels is actively being investigated.14-15
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Enhancing the efficient and cost-effective extraction, fractionation, and purification of TAGs
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will facilitate their exploitation, a significant step towards a viable biorefinery and ultimately a
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biobased economy.16 However, cost-effective and sustainable methods are still needed as
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traditional organic solvents are non-selective for TAG, necessitate further downstream separation
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processes, are toxic, and are costly to recycle.17 Despite high capital cost and potentially high
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energy requirements, supercritical carbon dioxide (scCO2) has been heralded as a scalable,
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tunable, and green technology for the extraction of microalgae lipids.18 Unlike organic solvents,
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scCO2 is non-toxic, produces solvent-free lipids, has a high selectivity for TAG, and is suitable
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to produce extracts for human consumption.19 The efficacy of scCO2 as a solvent primarily
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depends on its density, which can be controlled by varying pressure and/or temperature.20 This
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tunability has been leveraged to optimize total TAG yield, but not necessarily fractionation and
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enrichment, for various microalgae and extraction conditions.7
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A number of models have been developed to explain the extraction kinetics of a biomass/scCO2
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system describing an initial, rapid extraction phase limited by solute solubility followed by a
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slower extraction phase limited by internal mass transfer.21 Controlling extraction kinetics is
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essential for scaling biomass/scCO2 technologies, optimizing fractionation, and evaluating
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industrial scale economics.19, 22 Consequently, understanding TAG solubility behavior in scCO2,
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particularly from microalgal biomass, is key as it regulates kinetics during the first phase of
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extraction (Figure 1; inset). Previous studies using binary and tertiary mixtures of analytical
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standard TAGs have shown the solubility of a given TAG is affected by solute-solute
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interactions with other TAGs of various chain lengths and degrees of saturation.23-24 This effect
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can diminish or enhance relative solubility such that a TAG of lesser solubility in scCO2 at a
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given density can demonstrate enhanced solubility in the presence of another, more soluble
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TAG. Conversely, more soluble TAGs can exhibit diminished solubility in the presence of a less
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soluble TAG.24 These results have implications toward separation efficiency and fractionation
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using scCO2. Extraction systems can potentially be designed and operated to favor or disfavor
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solubilizing certain TAGs based on chain length and degree of saturation to minimize or negate
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downstream separation processes. However, this requires greater understanding of the behavior
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of complex TAG mixtures extracted from actual biomass as well as biomass matrix effects.
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This study evaluated the tunability of neat scCO2 to extract and fractionate TAGs from Chlorella
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sp. in a continuous flow system with a high resolution of temporal information. These results are
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then compared to the behavior of mixtures of TAG analytical standards. Combinations of
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pressures and temperatures were used to achieve different scCO2 densities. Results were
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assessed by solubility separation factors and solvato complex behavior (the necessary molecular
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association between solvent and solute to transition the TAG into scCO2) as well as the heats of
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solvation and vaporization. The potential of scCO2 to be used as an initial fractionation and
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enrichment tool is demonstrated whereby the associated energy and economic costs of
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downstream processing, such as distillation, can be reduced.
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2. Experimental materials and methods
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solvents with HPLC or better grade were purchased from Sigma-Aldrich. TAG standards were
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obtained from Nu-Chek Prep, Inc.; bone dry (≥99.8%) liquid carbon dioxide and ultra-high
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purity (99.999%) nitrogen gas was purchased from Airgas, Inc. Microalgae Chlorella sp. was
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grown in the University of Arizona’s Aquaculture Raceway Integrated Design (ARID),25
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lyophilized, ground with a pestle and mortar, and sieved to a particle size between 250 and 355
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microns.
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2.2 Extraction apparatus
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through a stainless steel tube, heated with a CAL ETC1311 controller and insulated heating tape,
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to a 25 mL SFT-100 extractor vessel from Supercritical Fluid Technologies, Inc. In addition to
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the two SFT-100 temperature probes, three additional probes monitored temperature at the inlet
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of the SFT-100, the extraction cylinder, and outlet line after the restrictor valve.
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temperatures were held constant, never exceeding 3⁰C deviation from the extraction vessel inlet,
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extraction vessel, and outlet line. Constant temperature from the point of biomass extraction to
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collection was setup to prevent reflux. It should be noted the temperature set point for the fluid
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delivery and restrictor/outlet lines were higher than the targeted value to heat the incoming flow
2.1 Standards, reagents, and biomass Fatty acid methyl ester (FAME) analytical standards, boron trifluoride (BF3), and organic
Two ISCO 100DX pumps setup for continuous constant pressure delivered carbon dioxide
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from room temperature and prevent freezing of the outlet due to the Joule-Thompson effect. All
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samples were collected in 5mL glass vial sample traps placed in an ice bath, excavated with N2
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gas and sealed with Teflon lined caps and stored at -20 ⁰C until derivatization (Chlorella sp.
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extracts) or analysis (analytical standard extracts).
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2.3 Supercritical carbon dioxide
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temperature and pressure extraction conditions using the National Institute of Standards and
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Technology (NIST) Reference Fluid Thermodynamic and Transport Properties Database
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(REFPROP).27 Analytical standards or microalgae biomass were loaded in the extraction vessel
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and the system was heated to the specified temperature. Pressurized CO2 was then introduced
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and equilibrated for 15 minutes after which the restrictor and outlet valves were opened and
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sample collection of the continuous flow began. CO2 flowrate was monitored from the ISCO
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pump controller and a flowmeter connected to the sample trap.
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2.4 Experimental conditions
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component mixture of trimyristin, tripalmitin, tripalmitolein, tristearin, triolein, and trierucin.
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300 mg of each TAG was loaded in the extraction vessel and each extraction was triplicated. For
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biomass extractions, 5 grams of Chlorella sp. were loaded and the extractions triplicated for each
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system condition evaluated. Extractions of analytical standards were all set to 40 ⁰C with
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pressures of 8.31, 9.3, 13.4, and 17.2 MPa for system condition referred to as very low, medium,
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high, and very high density respectively. Extractions of Chlorella sp. were run at 37 ⁰C and
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8.3MPa, 60 ⁰C and 13.8 MPa, and 40 ⁰C and 13.4 MPa for system conditions referred to with
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low, medium, and high density respectively. scCO2 density was thus 384 (very low), 550-556
Span and Wagner’s carbon dioxide equation of state26 was used to calculate densities based on
Extractions of TAG standards used a binary mixture of tripalmitin and triolein and a six
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(medium), 750 (high), and 812 (very high) mg/ml. The flowrate for all extractions was 2.8 ± 0.3
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mg/min.
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Samples were collected in ~5 minute intervals for the first 30 minutes, then ~10 minute intervals
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for the next 30 minutes. After the initial hour of collection, samples were collected in ~15
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minute intervals. The initial, rapid sample collection was necessary to characterize the solubility
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during the first phase of Chlorella sp. extractions.
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2.5 Analysis
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6890 gas chromatography (GC) unit equipped with an Agilent Select Biodiesel (15 m, 0.32 mm,
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0.10 µm) column and a flame ionization detector (FID) set to 400⁰C. The inlet temperature was
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set to 250⁰C with an 80:1 split, helium carrier gas at 4ml/min, the initial oven temperature was
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set to 40⁰C and held for 5 minutes, ramped up to 180⁰C at 15⁰C per minute, then to 280⁰C at 5⁰C
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per minute, then to 380⁰C at 15⁰C per minute and held for 10 minutes. Lipid extracts of
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Chlorella sp. were reconstituted in chloroform and transesterified to FAME for analysis using
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14% boron trifluoride (BF3) in methanol for 1 hour at 95 ⁰C.28-29 The FAME was collected in
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hexane and analyzed via the GC-FID equipped with an SP-2560 Capillary Column (100 m ×
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0.25 mm, df 0.20 µm). The inlet temperature was set to 250⁰C with an 80:1 split, helium carrier
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gas at 4ml/min, the initial oven temperature was set to 140⁰C and held for 5 minutes, ramped to
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180⁰C at 8⁰C per minute, then to 210⁰C at 8⁰C per minute, then to 250⁰C at 20⁰C per minute and
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held for 10 minutes. FID temperature was 250⁰C. TAG extracts and FAME were identified and
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quantified by comparing retention times and responses to known analytical standards.
TAG standard extracts were reconstituted in a 1:1 chloroform/hexane and analyzed with an HP
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The obtained FAME profile of Chlorella sp. was used as a proxy for the TAG content; intact
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TAG tend to have the same or similar fatty acid groups, particularly ones that predominate the
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lipid profile such as the profiles presented in this study.30 Chlorella sp. extracts were calculated
170
assuming a TAG composed of identical fatty acid chains. In this way, the transesterification
171
served only to identify chain length and degree of saturation of the solutes and enabled a
172
comparison to the extractions of TAG standards where each fatty acid chain was known to be
173
identical.
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2.6 Solubility data
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extraction results described by (Eq. 1):
Continuous flow solubility for each compound was calculated using the linear first phase
∗ =
178
(Eq. 1)
179
where yi* is the apparent solubility of solute i in scCO2 at a given density. Additionally, a
180
solubility separation factor, αij, was calculated as a ratio of apparent solubility of solutes i and j,
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yi* and yj*, respectively (Eq. 2). ∗
182
= ∗
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First phase extraction results were also used to fit Chrastil’s equation for compound solubility.
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Chrastil’s equation (Eq. 5) is valid for TAG in scCO2 with solubilities less than 100-200 g/L
185
where good fits with experimental data may indicate no solute to solute interaction and poor fits
186
suggesting that solute-solute interactions affect solubility. The formation of a solvato complex in
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equilibrium with no solute to solute interaction is defined by (Eq. 3.):
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∆ !"#$%&"' ()
+ + , + -./ + 0-1/ = -.12 /
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(Eq. 2)
(Eq. 3)
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where Y is the solute, Z is the dense gas, k is the number of molecules of gas to form a solvato
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complex, R is the gas constant, T is temperature, qs is a constant, and YZk is the solute
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concentration in the dense gas. Chrastil approximated solute concentration in the supercritical
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fluid by the Clapeyron-Clausius equation: -./ =
193 194
∆ $%3"45%&"' ()
+ +
(Eq. 4)
where qv is a constant. By combining Eq. 3 and Eq. 4, Chrastil’s equation31 is:
∗ = 6 2 exp ( + ;) )
195
(Eq. 5)
196
where d is the density of the gas and k is a density dependent association number between solute
197
and solvent. a accounts for the enthalpy of solute vaporization and enthalpy of a single solute to
198
form a solvato complex in a neat, dense gas and is equivalent to: ==
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∆ !"#$%&"' >∆ $%3"45%&"' (
(Eq. 6)
200
An association parameter, k, describes the number of molecules required to form a solvato
201
complex with a single solute. The b parameter characterizes the effect of molecular weights and
202
includes constants from the Clapeyron-Clausius equation and the equilibrium heat of solvation as
203
described by: ; = ln(AB + 0AC ) + + + + − 0ln (AC )
204 205
(Eq. 7)
where MY and MZ are the solute and solvent molecular weights.
206 207
Additionally, Stahl32-33 showed that at constant temperature, Equation 6 is linear for single
208
substances:
209
ln(∗ ) = 0 E ln 6 + ; E
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(Eq. 8)
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Experimental data from analytical standard TAG was used to fit parameter k’ using the slope of
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the solubility isotherm, ln(y*) vs. ln(d), and the b’ parameter is reported as the intercept of the y*
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axis.
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Experimental data from Chlorella sp. was used to initially fit k using the slope of the solubility
215
isotherm, ln(y*) vs. ln(d) while a was fit using the slope of ln(y*) plotted against 1/T according
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to Chrastil’s equation.31,
217
(GRG) algorithm was used to estimate b with the freedom to adjust a and k. Convergence was
218
achieved for all b parameters such that a and k did not deviate from the initial experimental data
219
values.
33
With initial values for k and a, the Generalized Reduced Gradient
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2.7 Downstream energy consumption
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was modeled in Aspen Plus V9. The process flow diagram is in supporting information S.1.
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Process energy consumption of four initial TAG mixtures were based on the first phase
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extraction results from this study using three different scCO2 densities and a traditional Bligh and
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Dyer solvent extraction.34 The objective modeled was to separate trimyristin (C14:0), tripalmitin
227
(C16:0) and Trierucin (C22:1) into high purity (>99%) streams from the rest of the TAGs. The
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process flow diagram (PFD) and initial composition of the TAG mixture for each scenario is
229
available in supporting information.
Energy consumption for the downstream separation of TAG mixtures by molecular distillation
230 231
The Peng-Robinson equation of state35 was used for TAG property estimation; due to the missing
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parameters in the Aspen component database, the concentration of tripalmitolein (C16:1) was
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combined with trimyristin (C14:0) based on the Equivalent Carbon Number (ECN)36 and the 10 ACS Paragon Plus Environment
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concentration of triarachidin (C:20:0) and tribehenin (C:22:0) were combined with trierucin
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(C22:1). Three distillation columns were assumed to have 20 trays and a pressure of 1.3e-6 MPa.
236
Reflux ratios were varied to minimize the energy consumption while maintaining the targeted
237
purity for the trimyristin and tripalmitin streams.
238
239 240 241 242 243
3. Results and Discussion
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analytical standards at a mass ratio of 1:1:1:1:1:1 were loaded into the vessel and extracted at
245
three different CO2 densities, 550, 750, and 812 mg/ml CO2. These densities were chosen to
246
represent the tunability of scCO2 and are referred to as medium, high, and very high density
247
respectively. Previous studies have shown that the solubility of analytical standards will be
248
unchanged for initial mass loading differences of up to 20%.37 The apparent solubility of each
249
TAGs using 2.8 mg/min of CO2 is shown in Figure 2 and supports that the solubility of various
250
TAGs changes with CO2 density. This is determined by the slope of the linear portion of the
251
initial extraction phase (Figure 1).
3.1 Impact of CO2 density on solubility of analytical standard mixtures To more readily approximate the complex mixtures that result from biomass, a mix of six
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Extract (mg)
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Figure 1: First phase extraction behavior of a mixture of six analytical standard triacylglycerides at high CO2 density (750 mg/ml) with a flow rate of 2.8 mg/min over 107 minutes as an example. Linear first phase behavior was measured for each triacylglyceride extracted from a mix of analytical standards and from the microalgae Chlorella sp. in this study. Insert: A representation of the first phase linear relationship between the amount of TAG extracted and the amount of solvent delivered, which is characterized by being solubility limited, whereas the second phase is mass transfer limited.
259 260
While trierucin (C20:1), the longest chain TAG evaluated in the analytical standards mixture,
261
demonstrates the highest solubility at both densities, the solubility of the other TAGs changes in
262
relation to each other at the various densities (Figure 2; analytical standards). It is interesting to
263
note, that the shortest TAG chain, trimyristin (C14:0), consistently demonstrates an apparent
264
solubility that is in the middle of the group. Further, tripalmitolein (C16:1), a mid-chain length
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TAG in this mixture, has its apparent solubility reduced from 0.11 at medium CO2 density to the
266
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respectively. (The tabulated y* data is available in supporting information S.2.) This indicates a
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potential strategy to fractionate complex TAG mixtures by changing the density of CO2 during a
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dynamic extraction. In this way, the density of the CO2 can be tuned to increase the separation of
270
certain MUFAs (i.e., enriching for C20:1 and deselecting for C16:1 at very high CO2 densities)
271
before altering the density of the CO2 (i.e., lowering the density to 550 mg/ml CO2) to then
272
selectively remove other TAGs (i.e., C16:1) from the remaining mixture (i.e., depleted of C20:1).
273
Solubilities at very high density were close to or exceeded the recommended valid range for
274
Chrastil’s equation of 100-200 g/L (y* values greater than 0.12-0.25 at this density). For this
275
reason, the very high density condition was not evaluated for Chlorella sp. extraction
276
experiments.
0.3
Analytical Standards
Chlorella sp. Saturated TAG C14:0 C16:0 C18:0 C20:0
0.2
C22:0 C24:0 MUFA TAG C16:1 C18:1
0.1
C20:1 C22:1 PUFA TAG C18:2 C18:3
0.0 Medium
High
Low
Medium
High
Supercritical Carbon Dioxide Density 277 278 279
Figure 2: Measured solubility, y*, and scCO2 densities for multi-component analytical standard TAG mixtures and TAGs extracted from the microalgae Chlorella sp. (Note: extracts from Chlorella sp. were
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modeled to be a triacylglyceride with identical fatty acids and reported as the modeled chain length and saturation.)
282 283 284 285 286
3.2 Solubility separation
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traditionally assumed to exhibit similar properties as a solute38. The separation factors for
288
tripalmitin and triolein from the binary, six analytical standards mixture, and Chlorella sp.
289
extractions are presented in Figure 3. For all conditions, scCO2 density had an effect on the
290
separation factor. At lower density conditions, the extract was enriched for C18:1 while the at
291
higher densities the extract was enriched for C16:0 in all of the analytical standard mixtures.
292
Interestingly, at a CO2 density of 750 mg/ml, the separation factor, αC16:0 / C18:0, was similar at 1.3
293
and 1.4 for the binary and multi component mixture respectively, but was 0.65 (enriching for
294
C18:1) when extracting from Chlorella sp.. The enrichment trend was different for the
295
microalgae extracts such that at lower densities C16:0 was favored and at higher densities C18:1
296
was favored. Solubility separation factors for each TAG pair at all of the conditions evaluated in
297
this study are available in the supporting information S.3.
Tripalmitin (C16:0) and triolein (C18:1) have an equivalent carbon number (ECN) and are
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Figure 3: Relative amounts of tripalmitin (C16:0) and triolein (C18:1) extracted depend on the state of CO2 as well as the matrix from which it is being extracted from. Densities of scCO2 evaluated were 384, 463, 550, 750, and 812 mg/ml labeled as very low, low, medium, high, and very high respectively.
302 303
Total yield during the first phase extraction for all system conditions increased with increasing
304
density. However, the lipid composition of the extract differed for each density condition. The
305
analytical standards mixture saw an increase in trimystirin (C14:0), tripalmitin (C16:0), tristearin
306
(C18:0), and trierucin (C20:1) from medium to high density while tripalmitolein (C16:1)
307
decreased and triolein (C18:1) was unchanged. Similar compounds extracted from Chlorella sp.
308
with medium and high CO2 densities showed that C16:1 and C18:1 increased, C18:0 decreased,
309
and C16:0 was unchanged.
310 311
The dissimilar solubility trends of analytical standards and Chlorella sp. extracts at different
312
density conditions suggest that the mixture (and matrix) from which TAG are extracted has an
313
impact on solubility behavior. Because the number of unique TAGs in the microalgae was
314
greater than that of the analytical standards, more solute/solute interactions may be modifying
315
their solubility. Additionally, at a high scCO2 density the apparent solubility of C16:1 and C18:1
316
(MUFAs) are higher from the microalgae extraction compared to the analytical standards. While
317
the TAG extracts from the analytical standard mixture showed no clear MUFA behavior trend,
318
both MUFA and PUFA compounds all increased in yield and solubility with increasing density
319
when extracted from Chlorella sp.
320 321
Interestingly, at medium and high scCO2 densities, the apparent solubility for similar compounds
322
extracted from microalgae compared to the analytical standards mixtures are dissimilar. The
323
apparent solubility of C16:0 extracted from the analytical standards mixture increased with
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324
increasing density while a slight depression was observed for extractions from Chlorella sp..
325
Note that in the analytical standards mixture, C16:0 was approximately 17% of the total mass but
326
accounted for almost 50% of the microalgae lipids. Because of the differences in initial mass
327
loadings, as well as the absence or presence of a complex biomass matrix, the different behaviors
328
and trends of the C16:0 TAG suggest that the matrix has an effect on the apparent solubility of
329
this TAG in scCO2 regardless of density.
330 331 332
3.3 Solvato complex and solute to solute interactions
333
solute to solute interactions. The parameters described in Eqs. 5 and 8 are listed in Table 1,
334
ordered from poorest fit to best fit, and were derived from the results presented in Figure 2
335
(complete data set available in supporting information S.2). Results from Chrastil’s original
336
investigation31 and Güclu-Üstundag and Temelli’s review33 for select individual TAGs where
337
solute to solute interactions do not exist are also presented for comparison.
Chrastil’s solubility parameters are derived from equilibrium thermodynamics and assume no
338 339 340 341 342 343 344
Table 1: Solubility parameters and their respective coefficient of determination from this study (indicated by *) and from other studies for select individual TAG to compare values derived from a mixture versus single component extractions where no solute-solute interactions exist. Results are ordered from poorest to best fit. †the authors cite a low R2 value as a result of combining data sets from different
studies
C16:1 (Tripalmitolein)* C18:1 (Triolein)* C20:1 (Trierucin)* C16:0 (Tripalmitin)* C18:0 (Tristearin)* C14:0 (Trimyristin)* C14:0 (Trimyristin)33 C16:0 (Tripalmitin)33
Class MUFA MUFA MUFA Saturated Saturated Saturated Saturated Saturated
Analytical standards k' b' 0.4 1.7 2.9 -14.7 4.2 -22.4 6.3 -36.5 6.0 -35.0 3.7 -20.1 9.27 -61.0 5.50 -32.1
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R2 0.036 0.635 0.749 0.776 0.960 0.984 0.991 0.601†
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C20:0* C18:0* C14:0* C22:0* C18:2* C18:1* C24:0* C16:0* C18:3* C20:1* C16:1* C16:031 C18:131
Class Saturated Saturated Saturated Saturated PUFA MUFA Saturated Saturated PUFA MUFA MUFA Saturated MUFA
b -10.6 0.7 -3.0 4.3 -2.9 -2.5 -8.8 4.6 -0.7 -0.9 0.7 -12.15 2.42
Chlorella sp. k a 1.5 808.4 0.7 -694.5 -1.7 4801.5 2.1 -5157.9 6.3 -10717.2 6.5 -11207.3 17.3 -32297.2 0.8 -1634.0 9.4 -18029.9 5.0 -9607.7 7.8 -15273.6 2.98 -2387.8 5.22 -11386.5
R2 (k) 0.042 0.208 0.287 0.478 0.807 0.824 0.971 0.985 0.994 0.997 0.999 -
R2 (a) 0.003 0.045 0.539 0.729 0.571 0.592 0.826 0.981 0.891 0.903 0.923 -
345 346
The coefficient of determination (R2), which indicates limited solute to solute interaction as it
347
approaches 1, ranged from 0.036 to 0.984 (Eq. 8) for extracts from the analytical standards
348
mixture. The k and a parameter values ranged from 0.042 to 0.999 and 0.003 to 0.923 (Eq. 6),
349
respectively, for Chlorella sp. extracts. MUFA in the analytical standards mixture generally had
350
poor fits to Eq. 8 while saturated TAGs had better fits. In contrast, MUFA and PUFA TAG
351
extracted from the biomass tended to have better fits for k and saturated TAG tended not to fit
352
Eq. 6 with the exception of C24:0 and C16:0 with k fits of 0.9712 and 0.9852 and a fits of 0.8262
353
and 0.9812 respectively. The a parameter suggests which TAGs are likely to be affected by
354
temperature and solutes with poor fits, such as C20:0 and C18:0, are more difficult to predict in
355
terms of first phase solubility behavior. This variability may be due to the affect mixtures have
356
on the heat of solvation and vaporization needed to transition into the scCO2 solvent. R2 values
357
for k and a parameters trended together as expected given that TAGs susceptible to solubility
358
effects stemming from mixture impacts would also be susceptible to enthalpy effects.
359
Intermolecular interactions between dissimilar TAG can change their solubility behavior in
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360
scCO237 and may be explained mechanistically by the energy needed to form a solvato complex,
361
or the condensation of the solvent around a solute molecule.39 Evidence presented here shows
362
that dissimilar TAG can modify the formation of the solvato complex and consequently alter the
363
apparent solubility behavior in scCO2. R2 values for k and a parameters trended together as
364
expected given that TAGs susceptible to solubility effects stemming from mixture impacts would
365
also be susceptible to enthalpy effects.
366 367
These results suggest that MUFA and PUFA TAG extracted from microalgae may be less
368
affected by potential solute to solute interactions in the solvato complex and mixture impacts due
369
to the enthalpy of vaporization. However, saturated TAG tend to be more affected by solute to
370
solute interactions which may be acting as entrainers, potentially due to hydrogen bonding.40
371
Additionally, CO2 can form a weak, cooperative, hydrogen bond with carbonyl groups as shown
372
by a longer C-O bond of CO2 involved with a C-H•••O hydrogen bond.41 The absence of a
373
double bond in a saturated TAG provides more opportunities for hydrogen bonding. Saturated
374
TAG tend to be straighter and longer than unsaturated TAG, providing more surface area for
375
hydrogen bonding when compared to a fatty acid chain with the same carbon chain length. TAG
376
interaction with CO2 and TAG entrainer effects would corroborate the observed different
377
apparent solubilites of the same TAG extracted from Chlorella sp. compared to analytical
378
standards mixtures for similar operating conditions and scCO2 density.
379 380
MUFAs C16:1 and C20:1 extracted from Chlorella sp. yielded relatively high a (0.923 and
381
0.903, respectively) and k (0.999 and 0.997, respectively) fits indicating their extraction behavior
382
is effected by their physical properties and less susceptible to solute to solute interactions.
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383
Because the solvation power of scCO2 is attributed to density, and consequently its polarity, logP
384
values for MUFAs C16:1, C18:1, and C20:1 may provide additional insight to their apparent
385
solubility (Figure 4).
386 387
Figure 4: Apparent solubility of MUFA extracts from Chlorella sp. and relationship with their polarity.
388 389
The trend appears to show an optimal value of logP, between 19 and 21, which is responsive to
390
CO2 density. Though the apparent solubility of C20:1 was relatively low regardless of CO2
391
density, it fit Chrastil’s model well, implying that extracting other TAG at lower densities first,
392
then switching conditions to enrich for the long chain MUFA may offer another handle for TAG
393
extraction enrichment. Additionally, the logP and y* relationships indicate a very high density
394
will be required for optimal extraction of compounds with relatively high logP values. Lastly,
395
C16:1 demonstrated similar solubility at low and medium density conditions, but at high density
396
its solubility is increased seven-fold. This indicates that C16:1 can withstand a range of low to
397
medium densities if operators seek to enrich the extract for other TAGs at lower density
398
conditions.
399
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400 401
3.4 Downstream energy impacts and trade-offs
402
potential reductions of energy and economic costs associated with downstream processing, such
403
as distillation, were modeled. Both organic and scCO2 extraction systems can use wet or dry
404
biomass but the organic system will have ~18% less overall extraction efficiency.42
405
upstream energy required to dry microalgae was not considered in the analysis but has been
406
shown to be ~2.6 MJ/kg of water dried in both cases.43-44 However, even “wet” biomass is still
407
dewatered and can be considered a biomass slurry of 10-20% water.45 Because of this, dry
408
biomass was used to maximize the lipid yield from the organic solvent system and the energy
409
required for drying was assumed to be the same for both technologies. This results in the most
410
conservative estimate of energy comparisons for the two systems.
411
compositions were used in the analysis including those resulting from the low, medium, and high
412
scCO2 density extractions of Chlorella sp. as determined in this study as well as one resulting
413
from conventional organic solvent extraction using dried algae (Table 2).
414
Table 2: Initial composition of the TAG mixture prior to the modeled distillation purification.
Given the possible use of scCO2 as an initial fractionation and enrichment tool, an analysis of the
The
Four initial TAG
C14:0
C16:0
C16:1
C18:0
C18:1
C18:2
C18:3
C20:0
C22:0
C22:1
C24:0
Solvent extraction
7.09%
57.26%
3.14%
17.78%
4.76%
1.52%
2.69%
0.00%
0.00%
0.03%
5.73%
scCO2 low density
2.26%
67.97%
1.98%
13.67%
5.32%
3.68%
1.04%
0.96%
2.60%
0.50%
0.00%
scCO2 medium density
1.98%
26.55%
3.20%
10.55%
24.49%
16.66%
2.89%
12.39%
0.51%
0.50%
0.27%
scCO2 high density
0.19%
16.07%
14.37%
3.46%
24.61%
15.26%
16.68%
0.53%
0.99%
0.92%
6.93%
415 416
In all cases, the first distillation column purified C14:0 to at least 99.4%, the second column
417
purified C16:0 to at least 98.8%, and the third column purified C22:1 to at least 99.2%. Results
418
from the energy analysis showed that altering the TAG composition in the extraction step by
419
scCO2 can provide energy savings for downstream processing. Table 3 summarizes the reflux
420
ratio of each column as well as the energy consumption to purify the selected TAG reported as 20 ACS Paragon Plus Environment
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421
total and normalized to 1kg of purified TAG. Tripalmitin (C16:0) and trierucin (C22:1) were
422
relatively more concentrated after the low density scCO2 extraction; accordingly, the energy
423
consumption for the distillation process was lower compared to the other starting TAG
424
composition scenarios. On the other hand, when the relative tripalmitin concentration in the
425
initial TAG mixture was significantly reduced, as is the case for the initial composition of the
426
medium and high density scCO2 extracts, the energy consumption for separation was increased.
427 428 429
Table 3: Summary of normalized results for each TAG analyzed and starting with the four relative mixtures of TAG from the three different densities in this study and an organic extraction. Reflux ratio
Organic solvent scCO2 low density scCO2 medium density scCO2 high density
MJ/kg TAG purified
MJ/hr
Column 1
Column 2
Column 3
Column 1
Column 2
Column 3
Energy consumption
0.7
2.5
0.5
5.422
6.536
0.988
1.29
0.7
2.0
0.5
5.083
6.103
0.847
1.20
0.5
7.0
0.5
5.140
7.177
1.918
1.42
0.5
20
0.5
5.507
12.656
2.213
2.04
Energy consumption normalized to mass of TAG separated
Organic solvent
scCO2 low density
scCO2 medium density
scCO2 high density
kg/hr
MJ/kg
kg/hr
MJ/kg
kg/hr
MJ/kg
kg/hr
MJ/kg
C14:0
1.070
5.065
0.418
12.175
0.512
10.036
1.545
3.565
C16:0
5.976
1.094
6.694
0.912
2.619
2.740
1.682
7.523
C22:1
0.003
339.179
0.399
2.121
1.321
1.452
0.257
8.610
430 431 432
Energy consumption per mass of purified TAG did not always follow a linear relationship; that
433
is, higher initial enrichment did not necessarily mean a lower energy requirement to complete the
434
purification downstream. Non-linear trends may be attributed to the different lipid profiles being
435
distilled. For example, C22:1 accounts for 0.50% of the extract in both the low and medium
436
scCO2 density lipid profile but the relative amount of C18:1, C18:2, and C20:0 is higher and
437
C16:0 is lower in the medium density extract. Subsequently, the energy per mass of C22:1 21 ACS Paragon Plus Environment
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438
purified is 2.121 and 1.452 MJ/kg for the low and medium density conditions respectively. The
439
trends are presented in Figure 5 on a log-log plot. C16:0 showed a linear trend meaning higher
440
extraction enrichments would reduce the energy needed for downstream purification. However,
441
for C14:0 and C22:1, a non-linear trend indicates an optimal amount of enrichment can be
442
targeted to reduce downstream energy consumption for purification. Because the analysis used
443
relative amounts of TAG mixtures from this study, extractions from other biomass and/or with
444
non-TAG fractions may make separation more or less energy intensive. These results, based on
445
extraction profiles from Chlorella sp., however do provide insight to the complex nature of
446
enriching for certain TAG in an extraction. Additional, more robust investigations to the
447
extraction and purification energy impacts and trade-offs in a biorefinery setting will be essential
448
to guide development of methods and technologies supporting a sustainable bioeconomy.
449
450 451 452 453
Figure 5: Downstream energy required to purify select TAG in relation to the relative amount of the TAG in the starting mixture extracted from microalgae. The trends indicate energy trade-offs may exist for over or under enriching various TAGs with scCO2 as a pre-treatment for distillation.
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457 458
Acknowledgements: This work was partially supported by the National Science Foundation
459
under Grant #152432 and Graduate Research Fellowship, Grant #DGE-1122492. Any opinions,
460
findings, and conclusions or recommendations expressed in this material are those of the
461
author(s) and do not necessarily reflect the views of the Nation Science Foundation.
462 463
Supporting Information: Process flow diagram of downstream distillation process and the
464
unabridged solubility separation factors.
465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492
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30. MacDougall, K. M.; McNichol, J.; McGinn, P. J.; O'Leary, S. J.; Melanson, J. E., Triacylglycerol profiling of microalgae strains for biofuel feedstock by liquid chromatographyhigh-resolution mass spectrometry. Anal Bioanal Chem 2011, 401 (8), 2609-2616. 31. Chrastil, J., Solubility of solids and liquids in supercritical gases. J. Phys. Chem. 1982, 86 (15), 3016-3021. 32. Stahl, E.; Schilz, W.; Schütz, E.; Willing, E., A quick method for the microanalytical evaluation of the dissolving power of supercritical gases. Angew. Chem. Int. Ed. (English) 1978, 17 (10), 731-738. 33. Güçlü, Ü.; Temelli, F., Correlating the Solubility Behavior of Fatty Acids, Mono-, Di-, and Triglycerides, and Fatty Acid Esters in Supercritical Carbon Dioxide. Ind. Eng. Chem. Res. 2000, 39 (12), 4756-4766. 34. Bligh, E.; Dyer, W., A rapid method of total lipid extraction and purification. Can J Biochem Physiol 1959, 37 (8), 911-917. 35. Peng, D.-Y.; Robinson, D. B., A new two-constant equation of state. Ind. Eng. Chem. Fundam. 1976, 15 (1), 59-64. 36. Podlaha, O.; Töregård, B., Some new observations on the equivalent carbon numbers of triglycerides and relationship between changes in equivalent carbon number and molecular structure. J. Chromatogr. A 1989, 482 (1), 215-226. 37. Bamberger, T.; Erickson, J. C.; Cooney, C. L.; Kumar, S. K., Measurement and model prediction of solubilities of pure fatty acids, pure triglycerides, and mixtures of triglycerides in supercritical carbon dioxide. J. Chem. Eng. Data 1988, 33 (3), 327-333. 38. Hamdy, A. H. E.-.; Perkins, E. G., High Performance reversed phase chromatography of Natural triglyceride mixtures: Critical pair separation. J. Am. Oil Chem. Soc. 1981, 58 (9), 867872. 39. Debenedetti, P. G.; Kumar, S. K., The molecular basis of temperature effects in supercritical extraction. AlChE J. 1988, 34 (4), 645-657. 40. Nilsson, W. B.; Gauglitz, E. J.; Hudson, J. K., Solubilities of methyl oleate, oleic acid, oleyl glycerols, and oleyl glycerol mixtures in supercritical carbon dioxide. J. Am. Oil Chem. Soc. 1991, 68 (2), 87-91. 41. Raveendran, P.; Wallen, S. L., Cooperative C−H···O Hydrogen Bonding in CO2−Lewis Base Complexes: Implications for Solvation in Supercritical CO2. J. Am. Chem. Soc. 2002, 124 (42), 12590-12599. 42. Yuan, J.; Kendall, A.; Zhang, Y., Mass balance and life cycle assessment of biodiesel from microalgae incorporated with nutrient recycling options and technology uncertainties. GCB Bioenergy 2015, 7 (6), 1245-1259. 43. Delrue, F.; Setier, P. A.; Sahut, C.; Cournac, L.; Roubaud, A.; Peltier, G.; Froment, A. K., An economic, sustainability, and energetic model of biodiesel production from microalgae. Bioresour. Technol. 2012, 111, 191-200. 44. Tu, Q.; McDonnell, B. E., Monte Carlo analysis of life cycle energy consumption and greenhouse gas (GHG) emission for biodiesel production from trap grease. Journal of Cleaner Production 2016, 112, 2674-2683. 45. Sills, D. L.; Paramita, V.; Franke, M. J.; Johnson, M. C.; Akabas, T. M.; Greene, C. H.; Tester, J. W., Quantitative uncertainty analysis of Life Cycle Assessment for algal biofuel production. Environ. Sci. Technol. 2013, 47 (2), 687-694.
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Title: Simultaneous Extraction, Fractionation and Enrichment of Microalgal Triacylglyerides by Exploiting the Tunability of Neat Supercritical Carbon Dioxide Authors: Thomas A. Kwan, Qingshi Tu, and Julie B. Zimmerman Brief synopsis: Supercritical carbon dioxide is shown to have potential as an initial fractionation and enrichment approach reducing the energy consumption and costs in an integrated biorefinery model.
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