Chromatography: Feedstock Characterization and Fermentation Monitoring of Biofuels Part 1

1 The world leader in serving science

Paul Voelker November 14, 2012

Feedstock Characterization and Fermentation Monitoring of Biofuels Part 1

2

Operation • Measures current or charge

resulting from the oxidation or reduction of analyte on a specific electrode surface.

• Oxidation—electrons go from the analyte to the electrode.

• Reduction—electrons go from the electrode to the analyte.

Amperometry

Electron Transfer

e-

e-

Analyte

Amperometry

3

Oxidation of Glucose During Pulsed Amperometric (PAD) Detection

4

Summary of Thermo Scientific™ Dionex™ CarboPac™ Column Application Areas

• Dionex CarboPac PA10/PA20/SA10 • Mono- and disaccharides • Samples with few alditols • Linear polysaccharides • Sialic acids • Small sample amounts

• Dionex CarboPac PA1 • Oligosaccharides (better on

Dionex CarboPac PA100) • Official methods based on PA1 • Colominic acid, inulin, and

amylopectins

• Dionex CarboPac MA1 • Alditols • Separation of rhamnose and

GalN • Methylated carbohydrates • Separation of GalNAc and

GlcNAc

• Dionex CarboPac PA100/PA200 • Branched oligosaccharides • Sialylated oligosaccharides • Mono- and disaccharides • Lysaccharides polysaccharides

5

Thermo Scientific Dionex ICS-5000 Capillary HPIC System

High Pressure Ion Chromatography • High pressure capable with capillary

systems • Continuous operation up to 5000 psi

when configured as a Reagent-Free™ (RFIC™) system

HPIC—High Resolution, Fast Analyses

Feedstock Analysis of Mono- and Disaccharides Using HPAE-PAD with On-Line Eluent Generation

Page 1 Archana Pandey 10/29/2012

Archana Pandey, Senior Research Associate Analytics and R&D, LS9 Inc.

Part 2, Feedstock Characterization and Fermentation Monitoring of Biofuels Webinar

November 14, 2012

Objective Resolution of eight sugars

Sucrose, arabinose, galactose, glucose, xylose, mannose, fructose and cellobiose

Establish dynamic range (Thermo Scientific™ Dionex™ CarboPac™ PA20 and SA10 columns) to meet our application needs

Determine accuracy and reproducibility over desired dynamic range

Analysis

Cellulosic feedstock

Monitoring sugars in fermentation broth

2 Archana Pandey 10/29/2012

Xylose, mannose, and galactose

Fructose and arabinose

Separation of Four Sugars: sucrose, glucose, xylose, & fructose in 20 min

Peak coelution with other sugars


Traditional LC Method (RI)

Traditional LC Method (RI)

Refractive Index (RI) Detector

Glucose, galactose, xylose, and mannose

Tandem 45-Min LC Method RI

Method Development—Conversion from Transitional to Tandem LC

Arabinose & mannose coleute

Tandem 45-Min LC Method RI


Thermo Scientific Dionex ICS-5000 System with Pulsed Amperometric Detection (PAD) & the Dionex CarboPac PA 20 Column

Arabinose, glucose, galactose, xylose, mannose, and fructose


Cellobiose

Calibration—Quadratic Fit/R2/Range on Dionex CarboPac PA20

Range: 2.5–80 ppm


Accuracy: 93–103% RSD ≤ 3.0%


QC: Glucose at 50 ppm


Oligomers Real Sample Profile: 10,000-Fold Dilution


Feedstock Analysis: Lot X Analysis on Dionex Carbo Pac PA 20 Column

Sugars mg/L % Composition LS9 (w/w)

% Composition Lot X (w/w)

Arabinose 0.7 0.7 0.8

Galactose 2.1 2.0 2.2

Glucose 48.0 45.7 43.7

Xylose 4.8 4.5 6.0

Mannose 14.5 13.8 13.6

Fructose 4.84 4.6 6.1

TOTAL 74.9 71.3 72.4

100/120 mg/L

100/120 mg/L

Injected on Dionex CarboPac PA 20 Column

Concn Solution of Feedstock/Sugar (w/v)

Archana Pandey 10/29/2012

Comparison (Volumetric and Electronic)

10


Comparison Volumetric Pipette (VP) and Electronic Pipette (EP)

Feedstock % Composition Lot X

% Composition LS9 (VP)

% Composition LS9 (EP)

Arabinose 1.50 1.15 1.19

Galactose 2.81 2.79 2.77

Glucose 47.82 42.68 43.23

Xylose 6.22 4.55 4.68

Mannose 22.59 18.87 19.31

Fructose 0.09 NA NA


Analysis of Unknown Mix of Sugar from External Source

Sample 1 Carb 36-CVS

Dionex System

g/L

External Source

g/L

Arabinose 9.70 10.01

Glucose 9.82 10.01

Xylose 9.93 10.01

Galactose 9.77 10.01

Mannose 9.87 10.01

Sugars Sample Analyzed by Dilution with Electronic Pipette Not Based on Weight

Concn Dionex System

Sample 1 Carb 36-CVS ~ 10 g/L each 1000-Fold Dilution with Electronic Pipette for Dionex System

Sample 2 Carb 36-Level X ~ 36 g/L each 2000-Fold Dilution with Electronic Pipette for Dionex System

Sample 1 Carb 36-Level X

Dionex System

g/L

External Source

g/L

Arabinose 35.57 36.01

Glucose 37.00 36.01

Xylose 35.07 36.01

Galactose 35.60 36.01

Mannose 34.78 36.01

Reduce method run time—transition to Dionex CarboPac SA10 column

Increased dynamic range using:

0.4 nL internal loop (4-port pod)

Thicker, 15-ml gasket

Linear fit instead of quadratic fit

Good reproducibility and accuracy over desired dynamic range

Introduce internal standard (ISTD) ‘fucose’ to address injection variability

Further Optimization of Method


10/29/2012 Archana Pandey 14

Dionex CarboPac SA10 Column—Separation of Nine Sugars in 10 min Fucose, sucrose, arabinose, galactos, glucose, xylose, mannose, fructose,

and cellobiose

Linear Fit: R2 – 0.998-0.999 (5–300 ppm)


Accuracy on Standards ≥ 98%


QC at 50 ppm for Better Accuracy

Accuracy 98–102% RSD ≤ 1.0 %


Presenter

Presentation Notes

Same QC which on PA20 column with quadratic fit gave accuracy +/- 5-7 % when run on SA10 column with linear fit gave much more tighter within variability of +/- 1-2 %


RSQC at 100 ppm Sugars with ISTD Fucose


Feedstock Sample Profile

Fermentation Sample Profile Broth: 50-fold dilution

1000–2000-fold dilution

Feedstock Analysis: Lot X Analysis on Dionex CarboPac SA 10 Column


% Composition

Sugars

% Composition

Lot X

% Composition

Day 1

% Composition

Day 2

% Composition

Day 3

Arabinose 0.79 0.71 0.68 0.70

Galactose 2.22 2.05 1.97 2.03

Glucose 43.73 44.00 43.73 44.29

Xylose 6.02 5.38 5.26 5.29

Mannose 13.55 12.98 12.72 12.89

Fructose 6.08 4.61 4.53 4.49


Conclusion

Optimization of method suitable for analytical purposes

Established good accuracy and precision over the desired dynamic range

Routine analysis of feedstock and fermentation samples

Rapid and Selective HPAEC-PAD Determination of Carbohydrates in Biomass Samples

Dr. Kevin Chambliss

Department of Chemistry and Biochemistry

Biomass-to-Bioproduct Production Paradigm

Feedstock Chemical Pretreatment

Enzymatic Hydrolysis Fermentation

1. Total sugar (measured as monomers) after quantitative saccharification of potential feedstocks.

2. Free (monomers + sucrose) and total sugar in aqueous extracts of lignocellulosic feedstocks (total – monomeric = oligomeric).

3. Free and total sugar in pretreatment liquors.

4. Free and total sugar in enzymatic hydrolysates.

5. Free sugar in fermentation broths.

Routine Carbohydrate Analyses in Biofuels R&D:

Current Practice Relies Heavily on HPLC-RI Methods to Interrogate Carbohydrates

0

20000

40000

60000

80000

100000

120000

0 5 10 15 20 25

Resp

once

(RIu

)

Retention Time (min)

sucr

ose

arab

inos

e gala

ctos

e

gluc

ose

xylo

se

man

nose

fruc

tose

cello

bios

e

Shodex Sugar SP0810 (Pb2+-form); 30 cm × 3 mm Eluent: H2O at 0.6 mL/min Column Temperature: 85 °C

Run times approaching 60 min…

Benefits of RI include: (1) direct injection of samples due to wide linear dynamic range; and (2) simultaneous monitoring of additional compounds due to universal detection…

Significant Improvements in Run Time and Resolution Observed with HPAEC-PAD

0

5

10

15

20

0 4 2 6 10 8

mal

tose

cello

bios

e

gluc

ose

sucr

ose

arab

inos

e ga

lact

ose xy

lose

m

anno

se

fruc

tose

IS1

IS2 Re

spon

se (n

C)


CO32−/HCO3

−-modified Thermo Scientific™ Dionex™ CarboPac™ PA20

1.0 mM NaOH(aq) at 0.5 mL/min Column Temperature: 40 °C

Sevcik, R.A. et al. J. Chromatogr. A 2011, 1218, 1236–1243.

Inherent Sensitivity of PAD Required Sample Dilutions up to 1:2000 Prior to Analysis

Sevcik, R.A. et al. J. Chromatogr. A 2011, 1218, 1236–1243.

1 3 2 4 5

0

15

20

10

5 Inte

nsity

(nC)

IS =

1

1

3 2 4

5

1

3 2

4

5

0

Corn Stover

1:1000 1:600 1:400

1 3 2 4 5 0 1 3 2 4 5 0


Switchgrass Poplar Wood

arab

inos

e =

2 ga

lact

ose

= 3

gluc

ose

= 4

xylo

se =

5

Dionex CarboPac SA10 Stationary Phase Alleviates the Need for Column Modification

0

5

10

15

20

25

30

0 2 4 6 8 10 12

Resp

once

(nC)


sucr

ose

arab

inos

e ga

lact

ose

gluc

ose

xylo

se

man

nose

fr

ucto

se

cello

bios

e

Dionex CarboPac SA10; 25 cm × 4 mm 1.0 mM NaOH(aq) at 1.5 mL/min

Column Temperature: 45°C

Thermo Fisher Scientific Has Also Addressed Sample Dilution Requirements Affiliated with PAD

2 mil → 62 mil gasket

10 μL → 400 nL internal sample loop

Interlaboratory Comparison of Novel HPAEC-PAD Methodology

Richard Sevcik

Lipika Basumallick and Jeff Rohrer

Deb Hyman and Chris Scarlata

ACADEMIC

INDUSTRY

GOVERNMENT

Instrument Configuration: Thermo Scientific Dionex ICS-3000 equipped with an eluent generator, autosampler, low-volume injector, Dionex CarboPac SA10 column, large-volume PAD detection cell.

Objectives: (1) Verify the linear range of the PAD detector.

(2) Evaluate interlab reproducibility with ‘real’ samples.

(3) Compare concentrations determined via HPAEC-PAD with HPLC-RI.

http://www.dionex.com/en-us/index.html�

Linear Dynamic Range Spanned 1.0–1.5 Orders of Magnitude Independent of Analyte

10

11

12

13

14

0.0 1.0 2.0 3.0 4.0 5.0

Resp

onse

Fac

tor

Concentration (g/L)

Linear response region for glucose

0 2 4 6 8

10 12 14 16

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Resp

onse

Concentration (g/L)

± 5%

Glucose calibration curve (0.020–3.0 g/L) r2 = 0.9992

Comparable Calibration Sensitivities Were Observed at Each Test Site (n = 6)

glucose Site 1 Site 2 Site 3

galactose Site 1 Site 2 Site 3

xylose

arabinose

fructose

mannose

sucrose

cellobiose

4.85 4.79 5.54

5.61 5.48 5.64

5.11

4.63

2.88

4.34

2.64

3.66

Slope Intercept 0.080 0.370 0.444

0.114 0.365 0.311

0.192

0.139

0.198

0.262

0.165

-0.086

0.9992 0.9972 0.9943

0.9995 0.9976 0.9958

0.9979

0.9992

0.9983

0.9967

0.9985

0.9992

r2 LOQ (102 g/L) 1.7 0.46 1.4

1.7 0.46 1.4

1.8

2.0

1.7

2.1

3.3

3.0

LOQs in Sevcik et. al were reported in units of 101 μg/L

10 μL injection; 2 mil spacer

21 Opportunistic R&D Samples Were Analyzed to Support Reproducibility Comparisons

Feedstock Compositional Analysis (4): (2-stage hydrolysis w/ H2SO4…) 2 corn stover, miscanthus, NIST bagasse

Pretreatment Hydrolysates (8): (monomeric and total sugar…) 2 vertical reactor, steam gun, slurry

Saccharification/Fermentation Samples (8): (monomeric sugar…) 3 saccharification at T0 and 5 fermentation at Tf

Synthetic Sample (1): glucose, xylose, acetic acid, furfural, and 5-HMF in 0.7% H2SO4

Dilution Factor

No Dilution

1:50 or 1:10

1:10

1:50

Excellent to Good Reproducibility Observed Between Labs for More Abundant Sugars

y = 1.00x

0 5

10 15 20 25 30 35

0 5 10 15 20 25 30 35

Site

2

Site 1

y = 1.08x

0 5

10 15 20 25 30 35

0 5 10 15 20 25 30 35

Site

3

Site 1

Mean Glucose (g/L) Mean Xylose (g/L)

y = 0.95x

0

20

40

60

80

100

0 20 40 60 80 100

Site

2

Site 1

y = 0.98x

0

20

40

60

80

100

0 20 40 60 80 100

Site

3

Site 1

Similar Reproducibility Observed Between Labs for Quantitation of Minor Sugars

y = 1.02x

0

3

5

8

10

13

15

0 3 5 8 10 13 15

Site

3

Site 1

y = 0.99x

0

3

5

8

10

13

15

0 3 5 8 10 13 15

Site

3

Site 2

Mean Arabinose (g/L)

y = 1.04x

0

1

2

3

4

5

0 1 2 3 4 5

Site

3

Site 2

Mean Galactose (g/L)

y = 1.17x

0

1

2

3

4

5

0 1 2 3 4 5

Site

3

Site 1

Concentrations of Major Sugars Determined via HPAEC-PAD Generally Agreed with HPLC-RI Data

y = 0.94x

0 5

10 15 20 25 30 35

0 5 10 15 20 25 30 35

HPL

C-RI

HPAEC-PAD

y = 0.92x

0

20

40

60

80

100

0 20 40 60 80 100

HPL

C-RI

HPAEC-PAD

Mean Glucose (g/L) Mean Xylose (g/L)

As sugar concentrations increased in test samples, HPAEC-PAD data trended high relative to concentrations determined via HPLC-RI.

Correlations for minor sugars deviated even further from the expected trend in both positive and negative directions.

Co-eluting species can cause RI information to be erroneous in either direction…

Raw Data Strongly Support the Possibility of False Positives When HPLC-RI Is Used

Site 1 Site 2 Site 3 HPLC-RI Site 1 Site 2 Site 3 HPLC-RI Site 1 Site 2 Site 3 HPLC-RI

arabinose

ND ND ND

9.1(1)

5.41(8) 5.75(9) 5.65(1)

6.534(4)

11.3(5) 11.0(1)

10.81(1) 12.5(2)

galactose

ND ND ND

4.925(8)

2.250(3) 2.63(2) 2.65(1) 3.33(1)

ND ND ND

5.9(3)

glucose

9.5(2) 10.3(1) 10.7(2)

9.62(5)

12.28(2) 13.603(2)

14.18(7) 13.36(9)

24.8(5) 25.3(2) 27.3(1)

24.31(9)

xylose

83.2(4) 82.5(3) 83.4(7) 75.8(5)

40.9(4)* 37.1(3)*

36.94(5)* 43.06(1)

78.0(5) 80.5(5)

80.86(7) 74.2(4)

cellobiose

ND ND ND

1.66(2)

ND ND ND

1.26(2)

ND ND ND

2.55(2)

fructose

ND ND ND

1.3(2)

2.5(2) 2.42(2) 2.87(5) 2.22(2)

ND ND ND

4.2(2)

Frequency 9 12 4 0 2 7

PAD

PAD

PAD

Concluding Remarks

• HPAEC-PAD is a superior approach to HPLC-RI for determination of sugars in biomass samples.

• The Dionex CarboPac SA10 stationary phase offers significant improvements in run time and resolution, especially of sucrose, relative to the Shodex SP0810 column (Pb2+-form).

• A novel method, utilizing a Dionex CarboPac SA10 column in combination with a low-volume injection valve and high-volume detection cell, proved to be both robust and reproducible in an interlaboratory comparison.

• Hardware modifications engineered at Thermo Fisher Scientific reduced PAD sensitivity such that samples of interest could be analyzed at reasonable dilution levels.

• False positives are likely when HPLC-RI methods are used to interrogate sugars in samples derived from biomass, especially for sugars present at low levels.

Chromatography: Feedstock Characterization and Fermentation Monitoring of Biofuels Part 1

Technology

Transcript of Chromatography: Feedstock Characterization and Fermentation Monitoring of Biofuels Part 1