Multivariate approach to on-line supercritical fluid extraction – supercritical fluid chromatography –mass spectrometry method development

A. Paige Wicker1,2, Kenichiro Tanaka3, Masayuki Nishimura4, Vivian Chen4, Tairo Ogura4, William

Hedgepeth4, Kevin A. Schug1,2

1) Department of Chemistry and Biochemistry, UT Arlington, Arlington, TX, USA

2) Affiliate of Collaborative Laboratories for Environmental Analysis and Remediation, UT Arlington, Arlington, TX, USA

3) Shimadzu Corporation, Nakagyo-ku, Kyoto, Japan

4) Shimadzu Scientific Instrument, Inc., Innovation Center, Columbia, MD, USA

10/16/2018

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Forensics

Bioanalysis

Natural Products

Environmental Food Science

Applications forOn-line SFE-SFC-MS

1. Supercritical fluids – properties and uses in analytical chemistry

2. Supercritical fluid extraction (SFE)

3. Supercritical fluid chromatography (SFC)

4. Overview of Shimadzu Nexera UC system (SFE-SFC-MS)

5. Polycyclic Hydrocarbons in Soil

6. Multivariate approach to method development

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Phase Diagram for CO2 Properties

• Hybrid of liquid and gas properties

• High diffusivity and low viscosity, like a gas

• High solute diffusion coefficients (DM) in mobile phase

• Density* and solvating power, like a liquid

*varies with T and P – attention!

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Phase Diagram for CO2 Practical Use in SFE and SFC

• CO2 has most reasonable critical point for instrumentation

• Solvating power like hexane

• Add polar modifier (MeOH, ACN) to increase solvating power (~ 2 – 40% v/v)

• Operate more in subcritical region with modifiers• High diffusivity and low viscosity

maintained

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▪Analytical technique since 1980s

▪Supercritical CO2 + modifiers

▪Stepwise process:1. Extraction of soluble substances from matrix by SF

2. Separation/recovery of the extracted compounds

▪On-line and Off-line

▪Dynamic and static modes

▪Green extraction technique▪Reduced solvents, reagents, energy usage, waste, time, and cost

▪CO2 is a gas at room T; depressurize and vent after use

COMMON APPLICATIONS• Bioactive natural products• Pesticide residues in food and soil• Lipids

INSTRUMENT COMPONENTS• CO2 supply• Cooling heat exchanger• Flow meter• CO2 pump• Co-solvent pump• Extraction cell (heated)• Restrictor• Sample collector (heated)

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Key Parameters to be Optimized:

Raw Material – particle size & porosity (mass transfer), water content

P and T – density of solvent (solvating strength)◦ Increase P, increased density, better solvating power◦ Increase T, decreases density, but increases volatility of solutes

Use of modifiers – usually < 10%; increased solubility

Flow rate – maximize extraction (high flow); maximize contact (low flow)

Extraction time – maximize extraction (higher); throughput (lower)◦ Flow rate and extraction time co-dependent variables – kinetics of extraction process

Analyte considerations: volatility, polarity, and thermal stability

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Binary mobile phase (SC CO2 + modifier) gives benefit of GC and LC

•Low viscosity and high diffusion constants• High speed (increased linear velocity)• High efficiency (longer columns)• Less backpressure issues than HPLC

•Addition of organic modifier allows analysis of polar compounds

•Lower solvent consumption compared to HPLC• Decreased waste generation and disposal costs

•A green separation technique, especially at larger scales

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SFE API-MS

ShimadzuNexera UC

Sample Preparation

Separation DetectionTrapping & High

Efficiency Separation48-vessel Autosampler

High Specificity & High Sensitivity on Triple Quadrupole MS

SFC

Sample in vessel

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•Good for samples with:• Trace level analytes

• Light or air sensitive analytes

• Restricted sample quantity

•Increased throughput

•On-line sorbent trap

•Nexera UC – trap on analytical column• Extraction solvent strength vs. chromatographic

retentivity

SFE COUPLED ON-LINE WITH:

• Gas chromatography – stationary

phase and film thickness

• Liquid chromatography/LC-MS –

solid phase trapping to remove gas

• Supercritical fluid chromatography –

packed or capillary trap

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Blocks highlighted in red are new hardware for the Nexera UC system.

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Loading & Static Extraction

P: 10-40 MPa

P: 10-40 MPa

Flow Rate: 0.25-5 mL/min%B: 0 – 10%

T: Ambient – 90 °CLoading Time: Flow rate & vessel volume dependentStatic Extraction Time: 0-10 min

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P: 10-40 MPa

P: 10-40 MPa

Flow Rate: 0.25-5 mL/min%B: 0 – 10%

T: Ambient – 90 °CDynamic Extraction Time: 0-10 min

Split Flow

To Waste

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P: 40 MPa (dynamic)

P: 10-40 MPa (static)

Flow Rate: 0.25-5 mL/min%B: 0 – 60%

T: Ambient – 80 °C

Achiral (Si, BEH, 2-EP, 2-PIC, diol, NH2, CN, DEA, C18, C8, biphenyl, PFP, Cholester) Chiral (amylose, cellulose, Pirkle type, cyclodextrins)

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Mix sample + IS +dehydrate kit

Add sample to vessel and seal

Place vessel inSFE rack changer

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www.whoi.edu

EPA designates as probable carcinogens:

benz(a)anthracene

benzo(a)pyrene

benzo(b)fluoranthene

benzo(k)fluoranthene

chrysene

dibenz(a,h)anthracene

indeno(1,2,3-c,d)pyrene

Natural and anthropogenic sources → soil → bioavailable Lundstedt Anal. Chem. 2006, 78, 2993-3000

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U.S. EPA method 8310 (HPLC-UV; HPLC-Fluor) (ca. 1986)

Sample prep (Kuderna-Danish)40 min. HPLC run0.45 – 18 ppm

Standby Analytical AnalysisDynamic ExtractionStatic ExtractionFrom Pumps

Valve Valve

Extraction Vessel

SFE UnitSFE-30A and Rack Changer

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Modifier 10% Acetonitrile (LCMS grade)

Flow Rate 3 mL/min

Extraction0-2 min Loading2-7 min Static Extraction7-12 min Dynamic Extraction

BPR A: 15 MPa; B: 15 MPa

Vessel Type 5.0 mL vessel

Soil Mass 1.00 g

Vessel Temp. 40 °C

12 minutes total for SFE

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Column COSMOSIL Cholester 250 mm x 4.6 mm, 5 µm

Modifier Acetonitrile (LCMS grade) 10 – 50%

Flow Rate 3.00 mL/min

ModifierGradient

10% (12-17 min)→ 20% (21 min)→ 40% (25-26 min)→ 50% (32 min)

BPR A: 15 MPa (50°C) B: 40 MPa (50°C)

Column Temp.

50°C

20 minutes total for SFC

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COSMOSIL Cholester phase250 x 4.6 mm, 5 µmGradient: 10 – 50% MeOH

Significant performance differences with sediment, clay, and sand matrices

32 min.total

analysis time

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Significant performance differences with sediment, clay, and sand matrices

Multivariate approach to on-line SFE-SFC-MS method development

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• Matrix composition• Analyte – matrix interactions

• Analyte retention; capacity

Validate method

SourcePost-column modifier

Nebulizing gas flow rateHeating gas flow rateDrying gas flow rate

Interface temperatureDesolvation line temperature

Heating block temperatureProbe position

Optimize MRM transitions

Optimize SFC parameters

SFC column selection

Optimize SFE parameters

Column temperatureModifier type

Modifier GradientPressureFlow rate

Make-up flow

Extraction temperatureModifier concentrationStatic extraction time

Dynamic extraction timePressureFlow rateSplit ratio

Optimize MS parameters

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Sam

ple

Ret

enti

tivi

ty

polar non-polar

high

low

PAH in soil

Quinones in soil

Drugs of abuse in

DBS

C18

C18 + protein

Miyazaki dehydrate

filter paper

silica gel

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Silica gel to mimic

carbohydrate

Amino-bonded silica to mimic

protein

C8-bonded silica to mimic fat

molecular weight

Log

P

Analyte Property Hypercube, at least

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Step 1. 2-Level Half Factorial Design

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WE ARE HERE

CotinineMatrineNicotineHydrocodoneHydromorphoneDiclofenacDiazepamWarfarinFentanyl

PhenobarbitalReserpineBentazonMethamphetamineAcetaminophenHistidineEstrone sulfateVanillinCannabidiol

18 model analytes, Optimized SFC-MS

Restek HILIC-Si (150 x 4.6 mm; 2.7 µm)Methanol + 5 mM ammonium formate2 – 60% modifier gradientColumn T: 50 oCDUIS ionization source

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Amino-bonded silica sample

26x

÷4

Extraction Pressure15 MPa 30 MPa

Peak Area: 864108

Peak Width: 0.199

Peak Area: 22547500

Peak Width: 0.055

Extraction Pressure15 MPa 30 MPa

Peak Area: 3145372

Peak Width: 0.239

Peak Area: 15388934

Peak Width: 0.060

Silica gel sample

Flow Rate 1 mL/min4 mL/min

Modifier Concentration 15% 5%

5x

÷4

Peak Area: 5354200

Peak Width: 0.255

Peak Area: 8430910

Peak Width: 0.033

Spinach mimic sample (9A:7S:1C8)

Extraction Pressure30 MPa 15 MPa

1.5x

15% 5%Modifier Concentration

÷8

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Extraction

Pressure

Extraction

Temperature

Static

Time

Dynamic

Time

Modifier

Concentration

Flow Rate

Protein √ √ √ √

Carbohydrate √ √ √ √

Fat √ √ √ √

Mixture √ √ √ √

• Assumes linear response (does not see maxima/minima)• Determines significance of variables and interactions, but does not provide optimal settings• Appropriate reduction of variables for Step 2. Response Surface Methodology experiments

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This Photo by Unknown Author is licensed under CC BY-NC-ND

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USER INPUT OUTPUT

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Proposed Intuitive Database – User Input

User selects ‘Matrix’ from dropdown menu.

% fat, carb, protein propagated by user selection of matrix. If user selects ‘other’ as matrix, then will manually enter % composition.*New data will be incorporated into database.

The initial step will entail the user selecting:• Sample matrix• Analyte(s)• Single run vs. Batch

Matrix Selection

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Proposed Intuitive Database – User Input

User selects ‘analyte’ from dropdown menu.

Physicochemical properties propagated by user selection of analyte.

Enter number of analytes.

If user selects ‘other’ as analyte, then will manually enter properties. Additionally, the name of ‘other’ analyte should be entered.*New data will be incorporated into database.

Analyte Selection

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Proposed Intuitive Database – User Input

User may select to either generate a single run or batch for optimization.

Select ‘single run’ → software directs user to a set of ‘starting parameters’.

Select ‘batch’ → software directs user to ‘key variables’.

Single Run vs. Batch

While the Database will feed into User Input to generate the starting parameters and key variables for analytes and matrices that we have optimized under the Central Composite Design, the unique User Input added will be utilized to update the Database.

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Proposed Intuitive Database - Database

Blackbox Database

AnalyteMonoisotopic

Mass Log P pKaMode m/z Precursor m/z Product Q1 CE Q2

(-)-cotinine 176.095 0.07 4.79 + 177.2 80.2 -30 -30 -32

98.25 -14 -22 -26

matrine 248.189 1.6 7.8 + 249.2 148.25 -46 -30 -44

247.3 -12 -26 -26

(-)-nicotine 162.116 1.17 3.1 + 163.15 117.15 -30 -26 -30

130.2 -30 -20 -30

hydrocodone 299.152 1.2 8.23 + 300.15 199.25 -24 -29 -32

128.25 -22 -62 -12

hydromorphone 285.136 0.9 8.59, 10.11 + 286.15 185.2 -30 -31 -34

128.2 -20 -59 -34

oxymorphone 301.131 0.83 8.17 + 302.15 284.25 -30 -21 -30

227.2 -30 -28 -24

Matrix % fat % carb % protein

Protein Powder 0 0 100

Corn Starch 100 100 0

MCT Oil 0 0 0

Spinach 6 53 41

Database could include analyte properties, suggestions for MRMs, and matrix compositions. Additionally, specific analyte/matrix optimized extraction parameters will be central to the database. Parameters will be developed through Central Composite Design experiments and response surface method data analysis with the assistance of UTA Department of IMSE.

Analyte/matrix Pressure (MPa)Static Ext Time

(min)Dynamic Ext Time (min)

%ModifierFlow rate (mL/min)

diazepam/protein powder 15 8 8 5 4

hydrocodone/spinach 30 8 8 15 1

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Proposed Intuitive Database – Starting Parameters

Based on what is entered in the User Input and parameters built into the Database, a set of starting parameters will auto-fill into the time program template for a single method file.

User defined SFC parameters optional.The user should be able to manually change

parameters in this window.

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Proposed Intuitive Database – Key Variables

The user may select to run a batch file to refine extraction parameters from those suggested for a single run.

Replace source parameters with extraction parameters. Enter potential values for parameters. Generate batch file.

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Design-Expert® Software

Factor Coding: Actual

Original Scale

early efficiency

6806.53 1.46604E+06

X1 = C: Static Time

X2 = E: Concentration

Actual Factors

A: Pressure = 15

B: Temperature = 45

D: Dynamic Time = 8

F: Flow rate = 2.5

5 7

9 11

13 15

2 3

4 5

6 7

8

0

200000

400000

600000

800000

1E+06

1.2E+06

1.4E+06

1.6E+06

chro

mato

gra

ph

ic e

ffic

ien

cy

Static Extraction Time (minutes)Modifier Concentration (%)

12.0 13.0 14.0 15.0

0

1000000

2000000

3000000

4000000

5000000

6000000

285.10>193.20(+)285.10>193.20(+)

5.0 10.0 15.0

0

250000

500000

750000

1000000

1250000

1500000

1750000

2000000

2250000 9:150.15>91.10(+)9:150.15>91.10(+)

0

0.5

1

1.5

2

2.5

3

3.5

1

1.5 2

2.5 3

3.5 4

4.5 5

5.5 6

6.5 7

7.5 8

8.5 9

9.5 10

Freq

uen

cy

pKa

0

1

2

3

4

5

-3.2

5

-2.2

5

-1.2

5

-0.2

5

0.7

5

1.7

5

2.7

5

3.7

5

4.7

5

5.7

5

6.7

5

Freq

uen

cy

Log P

0

2

4

6

8

75

12

5

17

5

22

5

27

5

32

5

37

5

42

5

47

5

52

5

57

5

62

5

67

5

Freq

uen

cy

Molecular Weight

Methamphetamine

Diazepam

Output for VisualizingKey Variables

3D Surface Map – Select 2 of 4 key variables to evaluate; click on map to see example chromatograms of each analyte in mixed sample corresponding to parameter combinations

Histograms– physicochemical properties highlighted for each analyte in the mixed sample.

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❖ Shimadzu Scientific Instruments and Shimadzu Corporation❖ Greg Vandiver❖ Sarah Olive❖ Kevin Marin

❖ Restek Corporation❖ Ty Kahler

❖ Inform Environmental❖ UTA IMSE

❖ Dr. Tory Chen❖ Dr. Shouyi Wang❖ Dr. Jay Rosenberg❖ Srividya Sekar

❖ Schug group

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