+ All Categories
Home > Documents > New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent...

New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent...

Date post: 21-Jun-2018
Category:
Upload: tranlien
View: 221 times
Download: 0 times
Share this document with a friend
37
New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample Characterization by GCxGC/FID/MSD, Crude Oil Biomarkers
Transcript
Page 1: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

New GCMS Applications

1

Malgorzata SierocinskaAgilent Technologies Waldbronn

Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample Characterization by GCxGC/FID/MSD, Crude Oil Biomarkers

Page 2: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Introduction

• Increasing quantities of biodiesel and jet are being co-transported in multi-product pipelines (MPP)

• In MPP transportation trace amounts of FAME can be found in jet parcels following biodiesel parcels due to FAME ‘trail back’.

• Following pipeline trials to establish the amount and profile of FAME ‘trail back’ into jet fuel

• JIG PQ committee work on the effect of various FAMEs (up to 400 ppm) on the specification properties of jet fuel the main engine

• Commercial aircraft OEMs gave approval of limit of 5 mg/kg total FAME in jet fuel

• New method developed using single column GC/MS to detect individual FAMEs from 0.5 mg/kg to 50 mg/kg– IP PM-DY/09 Method for Determination of FAME in Jet Fuel – GC/MS

with Selected Ion Monitoring

2

Page 3: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

IP PM-DY/09 Method for Determination of FAME in Jet Fuel – GC/MS with Selected Ion Monitoring

7890A GC Conditions:

Inlet:

• Temperature: 260 oC• Mode: splitless• Sample size: 1 uL

Column:

• HP-Innowax, 50m x 0.20 mm ID x 0.4 um• Flow: 0.6 mL/min helium constant flow mode

GC Oven:

• Initial temperature: 150 oC for 5 min.• Ramp 1: 20 oC/min to 200 oC for 17 min.• Ramp 2: 3 oC to 252 oC for 2 min.

5975C MSD Settings:

• Electron ionization (EI) at 70 eV• Source Temperature: 230 oC• Quad Temperature: 150 oC• Scan Range: m/z 33 to m/z 320• SIM Groups: see next slide

3

Page 4: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Mass Spec SIM Ions Used for FAME Quantification

FAME Species SIM Ions SIM Group Start Time

Methyl Palmitate (C16:0) 270 (mol. ion), 271, 239, 227 20 min.

Methyl Heptadecanoate (C17:0)* 284 (mol. ion) , 253, 241 28 min.

Methyl Stearate (C18:0) 298 (mol. Ion), 267, 255 32 min.

Methyl Oleate (C18:1) 296 (mol. ion), 265, 264 35.5 min.

Methyl Linoleate (C18:2) 294 (mol. ion), 295, 264, 263, 262 36.5 min.

Methyl Linolenate (C18:3) 292 (mol. ion) 293, 263, 236 39 min.

*C17:0 added to accommodate biodiesel made from animal fats

4

Page 5: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

SIM/SCAN of Calibration Standard0.5 mg/kg Each FAME in Dodecane

C16:0C17:0

C18:0 C18:1C18:2

C18:3Scan TIC

SIM TIC

5

Page 6: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

FAME Calibration – 0 to 5 mg/kg

6

C17:0 R² = 0.9998

C16:0 R² = 0.9998

C18:0 R² = 0.9999

C18:1 R² = 0.9999

C18:2 R² = 0.9997

C18:3 R² = 0.9997

0

20000

40000

60000

80000

100000

120000

140000

160000

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

C17:0

C16:0

C18:0

C18:1

C18:2

C18:3

Method uses this calibration for samples containing total FAME below 5 mg/kg

Page 7: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Matrix Induced Retention Time Shifts of FAME Peaks

26 28 30 32 34 36 38 40

C18:3+0.054 min.

C18:2+0.067 min.

C18:1+0.076 min.

C18:0+0.083 min.

C17:0+0.098 min.

C16:0+0.138 min.

50 mg/kg FAME Calibration Standard

50 mg/kg Each FAME Spiked in Jet Fuel

Sample matrix can shift FAME peaks outside of their detection windows

7

Page 8: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

5 mg/kg and 1 mg/kg Total FAME Spiked in Jet Fuel Sample 1

20 22 24 26 28 30 32 34 36 38 40 42 440

2000

6000

10000

14000

18000

22000

Abundance

Min.

Jet Fuel Blank

1 mg/kg Total FAME Spike

5 mg/kg TotalFAME Spike

C18:3

C18:2C18:1

C18:0C17:0C16:0

8

Page 9: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Qunatitative Results for 5 mg/kg and 1 mg/kg Total FAME Spiked in Jet Fuel Sample 1

5 mg/kg Total FAME Spike

FAME Run 1 Run 2 Run 3 Std Dev

C16:0 0.8 0.8 0.8 0.02

C17:0 0.9 0.8 0.8 0.01

C18:0 0.9 0.9 0.9 0.01

C18:1 0.8 0.8 0.8 0.01

C18:2 0.9 0.9 0.9 0.04

C18:3 0.9 0.9 0.9 0.02

Total 5.2 5.0 5.0 0.10

1 mg/kg Total FAME Spike

FAME Run 1 Run 2 Run 3 Std Dev

C16:0 0.3 0.5 0.5 0.09

C17:0 0.1 0.1 0.1 0.02

C18:0 0.1 0.1 0.1 0.02

C18:1 0.2 0.1 0.1 0.02

C18:2 0.2 0.2 0.2 0.01

C18:3 0.2 0.2 0.1 0.03

Total 1.0 1.2 1.2 0.12

9

Page 10: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Matrix Interference in Jet Fuel Sample 2

20 22 24 26 28 30 32 34 36 38 40 42 44 Min.

0.5 mg/kg Std of Each FAME

0.9 mg/kg Each FAME Spiked Second Jet Fuel Sample

Interferences change depending on type of jet fuel

10

Page 11: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Known Matrix Effects Raised C16:0 Detection Limit

22.90 23.00 23.10 23.20 23.30 23.40 23.50 23.60 23.70

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

22000

24000

26000

28000

30000

32000

34000

36000

38000

Time-->

Abundance

5 mg/kg

2 mg/kg

1 mg/kg

0.5 mg/kg

0.1 mg/kg

Data courtesy of Tom Lynch, BP

35.10 35.20 35.30 35.40 35.50 35.60 35.70 35.80 35.90 36.00 36.10 36.20 36.30 36.40 36.50

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

11000

Time-->

Abundance

Reference fuel

5 mg/kg

2 mg/kg

1 mg/kg

0.5 mg/kg

0.1 mg/kg

Reference fuel

C16:0 C18:1

11

Page 12: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Dean’s Heartcutting to Remove Matrix Interferences

FID

S/S Inlet

MSD

Restrictor

HP-Innowax

HP-5ms

Aux EPC

Capillary Flow TechnologyDeans Switch

12

Page 13: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

MDGC Method:GC/MS Instrument Conditions

Inlet:• Temperature: 260 oC• Mode: splitless• Sample size: 1 uL

Column 1:• HP-Innowax, 30m x 0.25 mm ID x 0.5 um• Flow: 1.0 mL/min He constant P (225 oC)

Column 2:• HP-5ms, 30m x 0.25mm ID x 0.25 um• Flow: 2.0 mL/min He constant P (225 oC)

Restrictor: 0.7m x 0.1 um ID deactivated fused silica

CC Oven:

• Initial temperature: 150 oC for 5 min.• Ramp 1: 20 oC/min to 200 oC for 17 min.• Ramp 2: 3 oC to 252 oC for 2 min.

MSD Settings:• Electron ionization (EI) at 70 eV• Source Temperature: 230 oC• Quad Temperature: 150 oC• Scan Range: m/z 33 to m/z 320• SIM Groups: see next slide

13

Page 14: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

FID Signal Used to Set Heart-Cut Times

50 mg/kg Total FAME Std

AVTURBlank

AVTUR 100 mg/kg Total

FAME Spike

22 24 26 28 30 32 34 36 38 40

FAMEPrimary Column Retention Time

(min.)

Heart-Cut Time (min.)

C16:0 24.080 23.7 – 24.6C17:0 29.151 28.9 – 29.5C18:0 33.798 33.5 – 34.1C18:1 34.841 34.5 – 35.1C18:2 36.825 36.6 – 37.2C18:3 39.570 39.3 – 39.9

Primary Column: HP-Innowax

Wider cut windows used to account for matrix induced retention time shifts

14

Page 15: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Improve SIM Ion Groups for FAME Peaks

40 60 80 100 120 140 160 180 200 220 240 260 280 300 320

167

115 1901417751 210 230 258 304

40 60 80 100 120 140 160 180 200 220 240 260 280 300 320

74

43143 227 270185 239

Jet Fuel BlankAverage Spectra25.5 – 25.8 min.

5 ppm C16:0 StandardAverage Spectra25.5 – 25.8 min.

Hydrocarbon mass peaks (mostly aromatics) in co-eluting jet fuel have little overlap with most FAME mass peaks

Prototype Software recommends SIM ions to reduce background interference and improve S/N in the target peak elution time

15

Page 16: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Expand SIM Ions Groups to Include FAME Base Peaks

FAME Species SIM Ions SIM Group Start Time

Methyl Palmitate (C16:0) 270(mol. ion), 271, 239, 227, 74(base) 20 min.

Methyl Heptadecanoate (C17:0) 284(mol. ion) , 253, 241, 74(base) 28 min.

Methyl Stearate (C18:0) 298(mol. Ion), 267, 255, 74(base) 32 min.

Methyl Oleate (C18:1) 296(mol. ion), 265, 264, 55(base) 35.5 min.

Methyl Linoleate (C18:2) 294(mol. ion), 295, 264, 263, 262, 67(base) 36.5 min.

Methyl Linolenate (C18:3) 292(mol. ion) 293, 263, 236, 79(base) 39 min.

16

Page 17: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

HP-5ms Secondary Column Elution of FAMES After Heart-Cut

C16:0 C17:0 C18:0 C18:1 C18:2 C18:3

HP-5ms ColumnMS Scan Data

HP-5ms ColumnMS SIM Data

Innowax ColumnFID Data

C16:0C17:0

C18:0 C18:1C18:2 C18:3

17

Page 18: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Combination of Heart-Cutting MDGC and Base Peak SIM Ions

• Improved detection of C16:0 FAME• Better(?) detection of C17:0 C18:0, C18:2 and C18:3• Added matrix interference with C18:1 FAME

26 28 30 32 34 36 38 40

C16:027.399 C17:0

32.133

C18:036.545

C18:137.336

C18:239.110

C18:341.558

Min.

1 mg/kg total FAME Spiked in Jet Fuel Sample 2(< 0.2 mg/kg each FAME)

18

Page 19: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Basic system layout for GCxGC FID/MSD

Auto-sampler

FID

Column 1

Flow modulator

s/s inletPCM

Switching valve

modulated

2nd column

1st column

Auto-sampler

FID

Column 1 Column 2Column 2

s/s inletPCM

Switching valve

modulated

2nd column

1st column

MSD

MS Tee

19

Page 20: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Flow Modulator Diagram for Operation with the 5975C MSD

Flow Modulation Interface for the MSD

MS Tee

Flow Modulation Interface for the MSD

MS Tee

171mm x 110um restrictor

Second column

Restrictor (0.4M x 0.25mm)FID

MOD

MSD

Second column

Restrictor (0.4M x 0.25mm)FID

MOD

MSD

20

Page 21: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

GC Image processing of MSD GCxGC dataTIC of heavy gasoline

Spectra are library searchable

21

Page 22: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Kerosene: GCxGC with MSD

22

Page 23: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

TIC: B20 Soy Biodiesel

23

Page 24: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

C18:2 Mass Spectrum

24

Page 25: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

25

5975C GCxGC

1. Naphthalene2. Methyl naphtalenes3. Dimethy naphthalenes4. 1 methyl 4- phenyl methyl benzene5. Anthracene6. Methly phenanthrene7. 9,10 dimethyl phenanthrene8. n-C23

Scan: 50 -375 amu

19 scans/sec. (2.3 scans)Scan range Scans/sec Scans/peak

50 - 200 28 3.350 - 300 22 2.6

Page 26: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Paraffins and Olefins Mix

12

3456

7 8 9 10 11 1213 1415

1. 1,8-Nonadiene2. 1-Nonene3. Nonane4. 1,9 Decadiene5. 1 Decene6. 4 Decene7. Decane

8. 3 Undecene9. Undecane10. 4 Decene11. Dodecane12. 2 Tridecene13. Tridecane

14. 5 Tetradecene15. Tetradecane

26

Page 27: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Paraffin and Aromatics Mix

1 2 34

5 6 7 8 9 10 11

1213

14 1516 1718

19

20

2122

1. Nonane2. 3-methyl nonane3. Decane4. 3-methyl decane5. Undecane6. 3-methyl 1-undecane7. Dodecane8. 4-methyl-dodecane9. 3-methyl-dodecane10. Tridecane11. Tetradecane

12. Butyl benzene13. 1-methyl 4 propyl benzene14. 1-methyl-4-(1-methylpropyl)-benzene15. Pentylbenzene16. 1-methyl butyl benzene17. Hexyl benzene18. 1,3 dimethyl butyl benzene19. 1-methyl hexyl benzene20. 1-methyl 2-n-hexyl benzene21. 1-butylhexyl-benzene22. 1-propyl heptyl-benzene

27

Page 28: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

MSD as a Standard GC Detector

1.Easy setup wit autotune

2. Possibility of using e-methods

3. Sensitivity and positive confinfirmation

4. Possibility of creating RTL methods with associated libraries

5. Possibility of column backflush to keep the ion source clean

6. High reliability

7. Compact and easy to service

28

Page 29: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Biomarkers are important in petroleum exploration for determining the age, biological source, and geological history of crude oils. They also allow characterization of crude oils in refineries and environmental monitoring.

The characterization of crude oils for biomarkers is commonly performed by capillary GC in combination with HRMS or SIM.

The application of SRM with a unique configuration of the GC allows for extended detection limits, higher throughput and higher analytical quality.

Biomarkers in Crude Oil

29

Page 30: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Experimental configuration

Pressure / Flow Controller

Column 1

Purged Ultimate Union

EI mode (70 eV)

SRM mode

Source 230°C

7890A GC

Injection Port

Pulsed Splitless

(300°C)

1.2 ml/min

1.22 ml/min

7000A

Column 2

30

Presenter
Presentation Notes
Essentially the purged Ultimate Union functions like a “Tee” in the middle of 2 columns. During acquisition, the flows in both columns are forward into the 7000A (blue arrows) and the system operates in constant flow mode. The second column gets a little extra makeup flow from the auxilliary EPC device (about 0.02mL/min)
Page 31: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Run times can be accelerated 30 minutes per cycle without loss in chromatographic resolution or substantial loss in signal by switching from a 60m column with He carrier gas to a 40m column with H2.

The speed of the 7000A Triple Quadrupole mass spectrometer in SRM mode required only a change in dwell time from 50 to 20 msec to record the required 17 transitions with the same number of scans over the peaks.

An experimental comparison with an uninterrupted 60m column (not shown) demonstrates that the use of the Pressure Controlled Tee configuration results in no degradation in chromatography.

Analysis Speed

↑40 min

↑70 min

40m column 60m column

31

Page 32: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Increased Throughput with BackflushingBackflush for faster turnaround, less carryover, and stable baselines

Targetcompounds High boiling compounds

seen in following solvent blank

No Backflush

With Backflush

Clean Solvent Blank

32

Presenter
Presentation Notes
Typical GCMS analysis of a series of hydrocarbon samples requires GC/MS methods with long cycle times and long GC oven hold times at high temperature to avoid compromising subsequent analysis with carryover of high-boiling components (top). In the absence of backflush- Even if often only a section (green) of the sample contains the biomarker series of interest (green box) – the Target compounds - the later eluting components must be removed by elevating the GC oven temperature and waiting for an extended period. However, if the Sample (H) is followed by a blank injection, high boiling compounds will appear in the following analysis as carryover which creates interferences and eventually degrades ion source performance. Note that Sample H contains a high percentage of very late eluting compounds. Utilizing backflush, the Target hydrocarbon compounds can be analyzed with significantly shorter method cycle times. After a series of samples using a Backflushing method including Sample H, a blank injection shows NO components and only the baseline rise associated with column bleed. In Backflushing methods, high boiling components are not retained and column degradation by “permanently” absorbed components and high temperature hold times decreases.
Page 33: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Analytical Precision of MS-MSReproducible biomarker concentrations in complex petroleum samples

33

Presenter
Presentation Notes
Routine biomarker analysis requires precise determination of the abundance of individual compounds which can vary over a very large range of concentrations in complex mixtures. This allows the distinction of differences between petroleum samples with subtly different source or post generation history. Results for ten sequential runs of a STANFORD-1 standard demonstrate that calculated concentrations of compounds using several different transitions with widely varying concentrations is precise.
Page 34: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Control Chart View

34

Presenter
Presentation Notes
Same data as previous slide
Page 35: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

A sophisticated understanding of petroleum systems requires the accurate deconvolution of oil mixtures derived from multiple source rocks. This problem is common where stacked source rocks exist in sedimentary basins.

Linearity and Dynamic Range: Deconvolving Oil Mixtures

35

Presenter
Presentation Notes
For next slide: A series of laboratory mixtures consisting of a marine petroleum endmember and a lacustrine endmember were analyzed for stigmastane, an ubiquitous component, and n-propylcholestane, a marine marker.
Page 36: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Linearity and Dynamic Range: Deconvolving Oil Mixtures

36

Presenter
Presentation Notes
A series of laboratory mixtures consisting of a marine petroleum endmember and a lacustrine endmember were analyzed for stigmastane, an ubiquitous component, and n-propylcholestane, a marine marker. As the ubiquitous component must be measured on a different MS/MS transition and is an order of magnitude more abundant in the marine oil, transition ratio stability and a large dynamic range are necessary to accurately identify marine petroleum inputs as as low as 0.2% by volume.
Page 37: New GCMS Applications - Agilent · New GCMS Applications 1 Malgorzata Sierocinska Agilent Technologies Waldbronn. Analysis of Trace Fatty Acid Methyl Esters (FAME) in Jet Fuel, Sample

Advantages of using SRM over SIM identified thus far include increased sensitivity, better selectivity and the potential to greatly reduce analysis time

Column backflush provided higher throughput with lower carry over

Hydrogen and narrower bore columns reduced the run time nearly two-fold

The scan speed, linearity, dynamic range and transition ratio stability of the triple quadrupole mass spectrometer allow the quantitative characterization and fingerprinting of petroleum samples and the deconvolution of petroleum mixtures.

Conclusions

37


Recommended