SlideShare une entreprise Scribd logo
1  sur  5
Télécharger pour lire hors ligne
a p p l i c at i o n N o t e

Atomic Absorption
Author
Stan Smith
PerkinElmer, Inc.
Shelton, CT 06484 USA

Analysis of Vanadium,
Nickel, Sodium, and Iron
in Fuel Oils using
Flame Atomic Absorption
Spectrophotometry

Introduction

Elemental analysis of fuel oil is an important
step in quantifying its quality. Combustion
of fuels containing metals can lead to the
formation of low melting-point compounds
that are corrosive to metal parts. The presence of certain metals, even at trace levels,
can deactivate or foul catalysts used during
the processing of the oil. ASTM® International
publishes numerous test methods for the
analysis of petroleum products, including
fuel oils. ASTM® D5863-00a (2005),
“Standard Test Methods for Determination of Nickel, Vanadium, Iron, and Sodium
in Crude Oils and Residual Fuels by Flame Atomic Absorption Spectrometry”, is
an industry-standard method for the analysis of fuel oils. Due to its multi-element
capabilities, inductively coupled plasma optical emission spectroscopy (ICP-OES)
may be the preferred technique for petroleum analyses requiring many elements,
however, flame atomic absorption spectrophotometry (FAAS) methods are still
quite effective and rapid for smaller numbers of elements such as those required
for fuel oil analyses. In addition, flame AA instrumentation is significantly more
compact than ICP-OES instruments, costs a fraction of the price, and requires less
operator training.
Experimental Conditions
Instrumentation
The analysis of a National Institute for Standards and
Technology® (NIST®) Standard Reference Material (SRM) fuel
oil was performed using a PerkinElmer® PinAAcle™ 900T
spectrometer (Figure 1) operated in the flame mode. A
stainless steel nebulizer (Part Nos. Nebulizer: N3160143;
End Cap: N3160102) was used along with a solvent-resistant
Kalrez® o-ring (Part No. N9300065) in the burner chamber and
a solvent-resistant drain assembly. Hollow cathode lamps
(Part Nos. V: N3050186, Ni: N3050152, Na: N3050148, Fe:
N3050126) were used for all analyses and an air-acetylene
flame was used for all elements except vanadium which was
analyzed with a nitrous oxide-acetylene flame (Burner Head
Part No. N0400100). Optimized parameters for each element
are listed in Table 1.

Table 1. Optimized experimental conditions for the analysis of
metals in fuel oil using the PinAAcle 900T spectrometer.
Analtye	
Wavelength (nm)	

Vanadium	 Nickel	Sodium	 Iron
318.40	

232.00	

589.00	

248.33

Slit Width (nm)	

0.7	

0.2	

0.2	

0.2

Read Time (sec)	

3.0	

3.0	

3.0	

3.0

Nitrous Oxide	

Air	

Air	

Air

Oxidant	
Oxidant Flow
(L/min)	

6.0	

10.0	 10.0	10.0

Acetylene Flow
(L/min)	

6.7	

2.5	 2.5	2.5

Sample Uptake
Rate (mL/min)	

2.25	

2.25	

2.25	

2.25

Standard and Sample Preparation
Per Test Method B of ASTM® D5863, the sample and standards
were prepared by solvent dilution. The solvent used was
V-SOLV™ from VHG Labs (Part No. N9308265), a refined
kerosene-like solvent. This method recommends the preparation
of the oil in solvent at either a 5% ratio or a 20% ratio,
depending on the actual concentration of the elements. In
this experiment, both ratios were run to encompass the range
of concentrations in the NIST® SRM and to determine if there
would be any bias between the two oil ratios.

Figure 1. PerkinElmer PinAAcle 900T and quick change burner assembly with
stainless steel nebulizer and air-acetylene burner head.

Default recommended conditions found in the WinLab32™
for AA software were used for most parameters (Table 1).
When analyzing high BTU organic solvents, however, the
sample flow rate must be reduced as typical hydrocarbon
solvents will flow faster than aqueous samples and hydrocarbon solvents are themselves fuel for the flame. The
sample rate of 2.25 mL/min for the kerosene solvent
(approximately 3 times lower than the typical 7 mL/min for
aqueous samples) generated a lean blue flame and met the
sensitivity checks for each element. For vanadium, which
used a nitrous oxide-acetylene flame, the acetylene flow rate
was adjusted to a slightly lower flow rate (6.0 L/min) from
the default value (7.5 L/min) to provide a more stable flame.

2

Calibration standards were Multi-Element Metallo-Organic
Standards (VHG labs) in 75 centistoke (cSt) hydrocarbon
base oil. Three V23 standards at: 10 µg/g (Part No. N0776109),
50 µg/g (Part No. N0776104) and 500 µg/g (Part No.
N0776106); along with a V21 standard at 100 µg/g (Part
No. N9308306) were used. The standards contained 23 and
21 elements, respectively, including nickel (Ni), vanadium (V),
sodium (Na), and iron (Fe). The blank was comprised of the
75 cSt hydrocarbon base oil (Part No. N0776103) diluted in
solvent. Each of the three calibration stock standards (10, 50,
and 500 µg/g) were diluted in V-SOLV™ to create calibration
standards at 0.5, 2.5, and 10 mg/kg in both 5% and 20%
total oil. The blank base oil was used to make up the difference, if necessary, between the calibration stock standard
and the needed 5% or 20% oil. This calibration range was
sufficient to address the observed concentration range of
the fuel oil sample. The 100 µg/g standard was diluted in
V-SOLV™ to produce a secondary source quality control (QC)
sample at 5 mg/kg in both 5% and 20% total oil.
The fuel oil analyzed was NIST® Standard Reference Material
1634c Trace Elements in Fuel Oil. The NIST® SRM included
certified values for V and Ni and a noncertified value for Na.
As no value was provided for Fe, a 3.62 mg/kg Fe matrix
spike was prepared from a 5000 µg/g stock organometallic
standard (VHG labs) for the NIST® sample.
In the analysis of aqueous samples for sodium and vanadium, it
is common to add 0.1% alkali salt such as KCl or LiCl to all
standards and samples to act as an ionization suppressant.
The high concentration of salt helps to control the ionization
effects in the flame and prevent bias in the results. ASTM®
D5863 does not call for the addition of an alkali salt, but
a third set of calibration samples and NIST® SRM were
prepared at 20% oil as stated above, but with the addition
of 250 mg/kg of Li (5000 µg/g, Conostan S21 Organometallic
Standard in Hydrocarbon Base Oil) to determine if vanadium
results would improve with the presence of an ionization
suppressant. It is difficult to spike significantly higher than
this without affecting the total oil percentage due to the
concentration of the stock organometallic standards.

Table 2. Recoveries of trace elements in NIST® SRM 1634c
using a 5% oil solution (mg/kg).
Replicate	

Iron	

1	

15.2	 18.0	35.0	 28.8

Nickel	 Sodium	Vanadium

2	

15.4	 18.2	34.4	 30.4

3	

15.4	 18.0	35.2	 28.8

Mean	

15.3	 18.1	34.9	 29.3

Standard Deviation	

0.12	

0.14	

0.42	

0.92

Certified Value 	

N/A	

17.54 ± 0.21	

37	

28.19 ± 0.40

% Recovery	

N/A	

103	

94.2	

104

*The uncertainty limits of the certified values are at a 95%
confidence level.

Table 3. Recoveries of trace elements in NIST® SRM 1634c
using a 20% oil solution (mg/kg).
Replicate	 Iron	 Nickel	 Vanadium	Vanadium
				 w/Li*

Results and Discussion

15.6	17.5	

26.5	

29.9

2	

15.5	17.7	

26.7	

29.7

3	

15.5	17.7	

26.7	

29.7

Mean	

15.5	17.6	

26.7	

29.7

Standard
Deviation	0.029	 0.13	

0.12	

0.17

% Recovery	

The instrument was optimized for the four elements prior
to analysis and the conditions are provided in Table 1. The
analytical sequence for each of the four elements was to
calibrate the instrument, analyze the blank and 5 mg/kg
QC sample, analyze the NIST® SRM and matrix spike where
applicable, and re-analyze the blank and QC sample.

1	

94.5	

106

N/A	

101	

*250 mg/kg Li ionization suppressant

NIST® and Spike Recoveries
Efficacy of the method was established by favorable comparison
of the obtained results to the certified values provided with
the NIST® SRM (Tables 2-3). Certified values were provided
for V and Ni and a noncertified value was provided for Na.
No reference value was provided for Fe, and instead, a
matrix spike was performed to demonstrate efficacy. The
NIST® SRM was prepared at the 5% oil ratio and spiked with
3.62 mg/kg of Fe. The spike concentration was mid range
for the calibration curve and approximately four times greater
than the observed (diluted) sample concentration (0.79 mg/
kg) at 5% oil. The observed concentration of iron was 4.44 mg/
kg in the spiked aliquot for a recovery of 101%. While this
does not specifically demonstrate the accuracy of the results,
it does provide support.

As can be seen by comparing the vanadium results between
Tables 2 and 3, the lithium ionization suppressant had no
significant effect on the results. These results support the
conclusion that although an ionization suppressant is needed
for aqueous samples, it is not necessary for organics and is
consistent with the ASTM® method.
Characteristic Concentration
The analytical conditions were modified from the typical
aqueous conditions to accommodate the matrix being
comprised of oil and solvent. However, the characteristic
concentration for each of the four elements was similar
to the recommended values provided in the WinLab32 for
AA software for aqueous conditions (Table 4 – Page 4).
Published data for the characteristic concentrations in
organic solutions was not available. However, considering
the differences in the rate of sample introduction and the
relative stability of aqueous and organic solutions, the
characteristic concentrations for the two different
matrices should be similar.

3
Table 4. Characteristic concentrations for the analysis of
metals in fuel oil. Reference values are for aqueous solutions
(mg/kg).
	
Analyte	

Aqueous		
Reference Value	

5	

% Oil
20	

20 w/Li

Iron	

0.1	

0.12	0.13	 N/A

Nickel	

0.14	

0.16	0.19	 N/A

Sodium	

0.012	

0.032	N/A	 N/A

1.9	

0.67	0.77	 0.79

Vanadium	

Calibration and Method Detection Limits
The calibration range used for all elements at both the 5%
and 20% dilution ratios was similar to that recommended
in ASTM® D5863 and also appropriate for the NIST® SRM.
All correlation coefficients were calculated with a non-linear
through zero calibration equation and were greater than
0.999. All calibration curves were verified with the secondary
source standard and returned recoveries of no more than
±5% of the prepared value (i.e., 5 mg/kg). Examples of two
calibration curves are shown in Figures 2 and 3.

Figure 3. Calibration curve for the detection of nickel in 5% oil using FAAS.

The calculated MDL results clearly demonstrate that this
method is more than adequate for the analysis of fuel oils
and has excellent sensitivity.
Table 6. MDL reported in mg/kg in varying oil content for
the analysis of metals in fuel oil by FAAS.
Analyte	

% Oil	

Std Dev	

MDL

Iron	

5	 0.0034	0.011

	

20	 0.0086	0.027

Nickel	 5	 0.0079	0.025
	

20	 0.0089	0.028

Sodium	 5	 0.0039	0.012
Vanadium	5	

0.033	

0.10

	

0.034	

0.11

20 (w/Li)	

Conclusions

Figure 2. Calibration curve for the detection of vanadium in 20% oil using FAAS.

In addition to the NIST® results comparison, the method
detection limits were estimated by repetitive analysis of the
0.5 mg/kg calibration standard (Table 6). This standard was
analyzed 7 times and the resultant standard deviation was
multiplied by the Student’s t-value for 6 degrees of freedom
and 99% confidence limits (3.143).
The percentage of oil did not appear to have any significant
effect on the method detection limit (MDL) results. The
more concentrated 20% oil solutions have slightly poorer
MDLs than that of the 5% solutions. Considering the
complex matrix in these sample solutions, these MDLs are a
very good indication that the instrument performs normally.
Better performance can be achieved, when desired, by additional
optimization of the operating parameters and maintaining
the cleanliness of the sample introduction system.

4

While ICP-OES and ICP-MS instrumentation may receive
more attention when it comes to metals analyses, FAAS is
a viable option particularly in the petroleum industry. There
are no less than 12 active ASTM® test methods available for
the analysis of petroleum products by AA techniques. FAAS
instrumentation offers rapid sample analysis, accuracy and
precision, simple operation, a small instrument footprint,
and all for a fraction of the price of the ICP instruments.
The PinAAcle 900T spectrometer is an excellent choice
for petroleum product analyses and can be used with the
ASTM® test methods. Very few and simple, optional modifications are suggested to handle the organic matrix. Excellent
accuracy has been demonstrated with a fuel oil SRM. The
quick-change spray chamber allows for fast and simple
conversion from aqueous to organic samples. The WinLab32
for AA software and its automated features simplify analyses,
freeing up more of the analyst’s time. The PinAAcle 900F
(flame only model) may also be used for this analysis.
References
1.	ASTM® Standard D5863, 2000a, “Standard Test Methods
for Determination of Nickel, Vanadium, Iron, and Sodium
in Crude Oils and Residual Fuels by Flame Atomic
Absorption Spectrometry,” ASTM® International, West
Conshohocken, PA, 2005, DOI: 10.1520/D5863-00AR05,
www.astm.org.

PerkinElmer, Inc.
940 Winter Street
Waltham, MA 02451 USA	
P: (800) 762-4000 or
(+1) 203-925-4602
www.perkinelmer.com

For a complete listing of our global offices, visit www.perkinelmer.com/ContactUs
Copyright ©2011, PerkinElmer, Inc. All rights reserved. PerkinElmer® is a registered trademark of PerkinElmer, Inc. All other trademarks are the property of their respective owners.
009830_01

Contenu connexe

Tendances

Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...
Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...
Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...eSAT Journals
 
Dissolved Gas Analysis of conventional diagnosis techniques for transformer
Dissolved Gas Analysis of conventional diagnosis techniques for transformer Dissolved Gas Analysis of conventional diagnosis techniques for transformer
Dissolved Gas Analysis of conventional diagnosis techniques for transformer Hardikarathod
 
Determination of Impurities in Organic Solvents used in the Semiconductor Ind...
Determination of Impurities in Organic Solvents used in the Semiconductor Ind...Determination of Impurities in Organic Solvents used in the Semiconductor Ind...
Determination of Impurities in Organic Solvents used in the Semiconductor Ind...PerkinElmer, Inc.
 
Pollutant abatement of nitrogen based fuel effluents over mono
Pollutant abatement of nitrogen based fuel effluents over monoPollutant abatement of nitrogen based fuel effluents over mono
Pollutant abatement of nitrogen based fuel effluents over monoimplax
 
Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...
Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...
Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...IOSR Journals
 
Dissolve gas anylysis measurement and interpretation technique
Dissolve gas anylysis measurement and interpretation techniqueDissolve gas anylysis measurement and interpretation technique
Dissolve gas anylysis measurement and interpretation techniqueArun Ramaiah
 
Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)
Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)
Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)chin2014
 
Postdoc Work at UWaterloo
Postdoc Work at UWaterlooPostdoc Work at UWaterloo
Postdoc Work at UWaterlooTony Rao
 
Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...
Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...
Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...chin2014
 
Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...
Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...
Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...Alexander Decker
 
Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...
Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...
Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...Shimadzu Scientific Instruments
 
Acetone gas sensors based on graphene zn fe2o4 composite prepared
Acetone gas sensors based on graphene zn fe2o4 composite preparedAcetone gas sensors based on graphene zn fe2o4 composite prepared
Acetone gas sensors based on graphene zn fe2o4 composite preparedUğur Acar
 
Investigation of Significant Process Parameter in Manganese Phosphating of Pi...
Investigation of Significant Process Parameter in Manganese Phosphating of Pi...Investigation of Significant Process Parameter in Manganese Phosphating of Pi...
Investigation of Significant Process Parameter in Manganese Phosphating of Pi...IJERA Editor
 
PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...
PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...
PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...PerkinElmer, Inc.
 
Harcourt-Essen Reaction
Harcourt-Essen ReactionHarcourt-Essen Reaction
Harcourt-Essen ReactionRafia Aslam
 

Tendances (20)

Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...
Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...
Effect of cu co mixed metal oxides on the combustion of psan-htpb based solid...
 
Dissolved Gas Analysis of conventional diagnosis techniques for transformer
Dissolved Gas Analysis of conventional diagnosis techniques for transformer Dissolved Gas Analysis of conventional diagnosis techniques for transformer
Dissolved Gas Analysis of conventional diagnosis techniques for transformer
 
Determination of Impurities in Organic Solvents used in the Semiconductor Ind...
Determination of Impurities in Organic Solvents used in the Semiconductor Ind...Determination of Impurities in Organic Solvents used in the Semiconductor Ind...
Determination of Impurities in Organic Solvents used in the Semiconductor Ind...
 
Pollutant abatement of nitrogen based fuel effluents over mono
Pollutant abatement of nitrogen based fuel effluents over monoPollutant abatement of nitrogen based fuel effluents over mono
Pollutant abatement of nitrogen based fuel effluents over mono
 
Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...
Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...
Multi-Element Determination of Cu, Mn, and Se using Electrothermal Atomic Abs...
 
228 20
228 20228 20
228 20
 
Snehesh-Presentation-PDF
Snehesh-Presentation-PDFSnehesh-Presentation-PDF
Snehesh-Presentation-PDF
 
Dissolve gas anylysis measurement and interpretation technique
Dissolve gas anylysis measurement and interpretation techniqueDissolve gas anylysis measurement and interpretation technique
Dissolve gas anylysis measurement and interpretation technique
 
Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)
Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)
Enhancing the Kinetcs of Mill Scale Reduction: An Eco-Friendly Approach (Part 2)
 
Mq2420912096
Mq2420912096Mq2420912096
Mq2420912096
 
Postdoc Work at UWaterloo
Postdoc Work at UWaterlooPostdoc Work at UWaterloo
Postdoc Work at UWaterloo
 
Prasad gas chromatography
Prasad  gas chromatographyPrasad  gas chromatography
Prasad gas chromatography
 
Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...
Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...
Enhancing the Kinetics of Mill Scale Reduction: An Eco-Friendly Approach (Par...
 
Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...
Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...
Determination of vanadium, nickel, copper and iron as complexes of bis acetyl...
 
Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...
Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...
Sulfur Analysis by GC-SCD using Shimadzu’s SCD-2030 for ASTM D5504, D5623, an...
 
G33029037
G33029037G33029037
G33029037
 
Acetone gas sensors based on graphene zn fe2o4 composite prepared
Acetone gas sensors based on graphene zn fe2o4 composite preparedAcetone gas sensors based on graphene zn fe2o4 composite prepared
Acetone gas sensors based on graphene zn fe2o4 composite prepared
 
Investigation of Significant Process Parameter in Manganese Phosphating of Pi...
Investigation of Significant Process Parameter in Manganese Phosphating of Pi...Investigation of Significant Process Parameter in Manganese Phosphating of Pi...
Investigation of Significant Process Parameter in Manganese Phosphating of Pi...
 
PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...
PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...
PerkinElmer Application Note: Monitoring volatile organic compounds in beer p...
 
Harcourt-Essen Reaction
Harcourt-Essen ReactionHarcourt-Essen Reaction
Harcourt-Essen Reaction
 

Similaire à Analysis of Vanadium, Nickel, Sodium, and Iron in Fuel Oils using Flame Atomic Absorption Spectrophotometry

Analysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OES
Analysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OESAnalysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OES
Analysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OESPerkinElmer, Inc.
 
From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111
From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111
From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111Shimadzu Scientific Instruments
 
Analysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OES
Analysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OESAnalysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OES
Analysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OESPerkinElmer, Inc.
 
G03702054060
G03702054060G03702054060
G03702054060theijes
 
Determination of Carbon Dioxide, Ethane And Nitrogen in Natural Gas by Gas C...
Determination of Carbon Dioxide, Ethane  And Nitrogen in Natural Gas by Gas C...Determination of Carbon Dioxide, Ethane  And Nitrogen in Natural Gas by Gas C...
Determination of Carbon Dioxide, Ethane And Nitrogen in Natural Gas by Gas C...Gerard B. Hawkins
 
125882919 crude-oil
125882919 crude-oil125882919 crude-oil
125882919 crude-oilGuman Singh
 
Practicing DGA - Diagnóstico DGA
Practicing DGA - Diagnóstico DGAPracticing DGA - Diagnóstico DGA
Practicing DGA - Diagnóstico DGATRANSEQUIPOS S.A.
 
Effect of performance and emission
Effect of performance and emissionEffect of performance and emission
Effect of performance and emissionprjpublications
 
Determination of physico chemical properties of castor biodiesel a potential
Determination of physico chemical properties of castor biodiesel  a potentialDetermination of physico chemical properties of castor biodiesel  a potential
Determination of physico chemical properties of castor biodiesel a potentialIAEME Publication
 
Method development for the analysis of mono-carbonyl compounds in e-vapor pro...
Method development for the analysis of mono-carbonyl compounds in e-vapor pro...Method development for the analysis of mono-carbonyl compounds in e-vapor pro...
Method development for the analysis of mono-carbonyl compounds in e-vapor pro...Rana Tayyarah
 
Copper Strip Corrossion Test in Various Aviation Fuels
Copper Strip Corrossion Test in Various Aviation FuelsCopper Strip Corrossion Test in Various Aviation Fuels
Copper Strip Corrossion Test in Various Aviation Fuelsinventy
 
Concrete Containment Tendon Grease Sampling and Analysis
Concrete Containment Tendon Grease Sampling and AnalysisConcrete Containment Tendon Grease Sampling and Analysis
Concrete Containment Tendon Grease Sampling and AnalysisRich Wurzbach
 
BENFIELD LIQUOR - DETERMINATION OF IRON
BENFIELD LIQUOR - DETERMINATION OF IRONBENFIELD LIQUOR - DETERMINATION OF IRON
BENFIELD LIQUOR - DETERMINATION OF IRONGerard B. Hawkins
 
Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...
Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...
Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...PerkinElmer, Inc.
 
Nitrogen_Protein Determination of Spirulina Algae.pdf
Nitrogen_Protein Determination of Spirulina Algae.pdfNitrogen_Protein Determination of Spirulina Algae.pdf
Nitrogen_Protein Determination of Spirulina Algae.pdfNguyenMinhChau22
 
Production of Hydrocarbons from Palm Oil over NiMo Catalyst
Production of Hydrocarbons from Palm Oil over NiMo CatalystProduction of Hydrocarbons from Palm Oil over NiMo Catalyst
Production of Hydrocarbons from Palm Oil over NiMo Catalystdrboon
 
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)inventionjournals
 
Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...
Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...
Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...QUESTJOURNAL
 

Similaire à Analysis of Vanadium, Nickel, Sodium, and Iron in Fuel Oils using Flame Atomic Absorption Spectrophotometry (20)

Analysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OES
Analysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OESAnalysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OES
Analysis of Oil Additives Following ASTM D4951 with the Avio 200 ICP-OES
 
From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111
From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111
From Crude to Fuels – Trace Metals Analysis by ICP-OES for ASTM D7691 and D7111
 
Analysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OES
Analysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OESAnalysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OES
Analysis of In-Service Oils Following ASTM D5185 with the Avio 200 ICP-OES
 
G03702054060
G03702054060G03702054060
G03702054060
 
Determination of Carbon Dioxide, Ethane And Nitrogen in Natural Gas by Gas C...
Determination of Carbon Dioxide, Ethane  And Nitrogen in Natural Gas by Gas C...Determination of Carbon Dioxide, Ethane  And Nitrogen in Natural Gas by Gas C...
Determination of Carbon Dioxide, Ethane And Nitrogen in Natural Gas by Gas C...
 
DIESEL.PPT
DIESEL.PPTDIESEL.PPT
DIESEL.PPT
 
125882919 crude-oil
125882919 crude-oil125882919 crude-oil
125882919 crude-oil
 
Practicing DGA - Diagnóstico DGA
Practicing DGA - Diagnóstico DGAPracticing DGA - Diagnóstico DGA
Practicing DGA - Diagnóstico DGA
 
Effect of performance and emission
Effect of performance and emissionEffect of performance and emission
Effect of performance and emission
 
Determination of physico chemical properties of castor biodiesel a potential
Determination of physico chemical properties of castor biodiesel  a potentialDetermination of physico chemical properties of castor biodiesel  a potential
Determination of physico chemical properties of castor biodiesel a potential
 
Method development for the analysis of mono-carbonyl compounds in e-vapor pro...
Method development for the analysis of mono-carbonyl compounds in e-vapor pro...Method development for the analysis of mono-carbonyl compounds in e-vapor pro...
Method development for the analysis of mono-carbonyl compounds in e-vapor pro...
 
Copper Strip Corrossion Test in Various Aviation Fuels
Copper Strip Corrossion Test in Various Aviation FuelsCopper Strip Corrossion Test in Various Aviation Fuels
Copper Strip Corrossion Test in Various Aviation Fuels
 
Concrete Containment Tendon Grease Sampling and Analysis
Concrete Containment Tendon Grease Sampling and AnalysisConcrete Containment Tendon Grease Sampling and Analysis
Concrete Containment Tendon Grease Sampling and Analysis
 
BENFIELD LIQUOR - DETERMINATION OF IRON
BENFIELD LIQUOR - DETERMINATION OF IRONBENFIELD LIQUOR - DETERMINATION OF IRON
BENFIELD LIQUOR - DETERMINATION OF IRON
 
Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...
Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...
Method 8260C by Purge and Trap Gas Chromatography Mass Spectrometry using the...
 
Nitrogen_Protein Determination of Spirulina Algae.pdf
Nitrogen_Protein Determination of Spirulina Algae.pdfNitrogen_Protein Determination of Spirulina Algae.pdf
Nitrogen_Protein Determination of Spirulina Algae.pdf
 
Understanding Diesel Fuel
Understanding Diesel FuelUnderstanding Diesel Fuel
Understanding Diesel Fuel
 
Production of Hydrocarbons from Palm Oil over NiMo Catalyst
Production of Hydrocarbons from Palm Oil over NiMo CatalystProduction of Hydrocarbons from Palm Oil over NiMo Catalyst
Production of Hydrocarbons from Palm Oil over NiMo Catalyst
 
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)
 
Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...
Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...
Comparison of The Experimental TBP Curve with Results of Empirical Correlatio...
 

Plus de PerkinElmer, Inc.

Detectando a Pré Eclampsia no 1º Trimestre
Detectando a Pré Eclampsia no 1º TrimestreDetectando a Pré Eclampsia no 1º Trimestre
Detectando a Pré Eclampsia no 1º TrimestrePerkinElmer, Inc.
 
As Tecnologias que Definem o Desempenho
As Tecnologias que Definem o DesempenhoAs Tecnologias que Definem o Desempenho
As Tecnologias que Definem o DesempenhoPerkinElmer, Inc.
 
GCMS Portátil: Análises em 5 minutos!
GCMS Portátil: Análises em 5 minutos!GCMS Portátil: Análises em 5 minutos!
GCMS Portátil: Análises em 5 minutos!PerkinElmer, Inc.
 
Nós transformamos complexidade em simplicidade
Nós transformamos complexidade em simplicidadeNós transformamos complexidade em simplicidade
Nós transformamos complexidade em simplicidadePerkinElmer, Inc.
 
Janus G3: Rapidez e Automação que você precisa.
Janus G3: Rapidez e Automação que você precisa.Janus G3: Rapidez e Automação que você precisa.
Janus G3: Rapidez e Automação que você precisa.PerkinElmer, Inc.
 
Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?PerkinElmer, Inc.
 
Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?PerkinElmer, Inc.
 
O Mercado da Carne no Brasil
O Mercado da Carne no BrasilO Mercado da Carne no Brasil
O Mercado da Carne no BrasilPerkinElmer, Inc.
 
KITS de Preparo para Biblioteca NGS
KITS de Preparo para Biblioteca NGSKITS de Preparo para Biblioteca NGS
KITS de Preparo para Biblioteca NGSPerkinElmer, Inc.
 
Escolha um parceiro e não um fornecedor
Escolha um parceiro e não um fornecedorEscolha um parceiro e não um fornecedor
Escolha um parceiro e não um fornecedorPerkinElmer, Inc.
 
Eletroforese Capilar Automatizada
Eletroforese Capilar Automatizada Eletroforese Capilar Automatizada
Eletroforese Capilar Automatizada PerkinElmer, Inc.
 
Analysis of Trace Elements in Fertilizer with AVIO 200 ICP-OES
Analysis of Trace Elements in Fertilizer with AVIO 200 ICP-OESAnalysis of Trace Elements in Fertilizer with AVIO 200 ICP-OES
Analysis of Trace Elements in Fertilizer with AVIO 200 ICP-OESPerkinElmer, Inc.
 
Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...
Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...
Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...PerkinElmer, Inc.
 
New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...
New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...
New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...PerkinElmer, Inc.
 
High Quality DNA Isolation Suitable for Ultra Rapid Sequencing
High Quality DNA Isolation Suitable for Ultra Rapid SequencingHigh Quality DNA Isolation Suitable for Ultra Rapid Sequencing
High Quality DNA Isolation Suitable for Ultra Rapid SequencingPerkinElmer, Inc.
 

Plus de PerkinElmer, Inc. (20)

Detectando a Pré Eclampsia no 1º Trimestre
Detectando a Pré Eclampsia no 1º TrimestreDetectando a Pré Eclampsia no 1º Trimestre
Detectando a Pré Eclampsia no 1º Trimestre
 
É A VEZ DO PRIME
É A VEZ DO PRIMEÉ A VEZ DO PRIME
É A VEZ DO PRIME
 
TREC PARA A VIDA
TREC PARA A VIDATREC PARA A VIDA
TREC PARA A VIDA
 
As Tecnologias que Definem o Desempenho
As Tecnologias que Definem o DesempenhoAs Tecnologias que Definem o Desempenho
As Tecnologias que Definem o Desempenho
 
GCMS Portátil: Análises em 5 minutos!
GCMS Portátil: Análises em 5 minutos!GCMS Portátil: Análises em 5 minutos!
GCMS Portátil: Análises em 5 minutos!
 
Nós transformamos complexidade em simplicidade
Nós transformamos complexidade em simplicidadeNós transformamos complexidade em simplicidade
Nós transformamos complexidade em simplicidade
 
Janus G3: Rapidez e Automação que você precisa.
Janus G3: Rapidez e Automação que você precisa.Janus G3: Rapidez e Automação que você precisa.
Janus G3: Rapidez e Automação que você precisa.
 
Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?
 
Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?Como a PerkinElmer contribui para diagnósticos mais rápidos?
Como a PerkinElmer contribui para diagnósticos mais rápidos?
 
Aspirina Vs Pré Eclampsia
Aspirina Vs Pré Eclampsia Aspirina Vs Pré Eclampsia
Aspirina Vs Pré Eclampsia
 
O Mercado da Carne no Brasil
O Mercado da Carne no BrasilO Mercado da Carne no Brasil
O Mercado da Carne no Brasil
 
KITS de Preparo para Biblioteca NGS
KITS de Preparo para Biblioteca NGSKITS de Preparo para Biblioteca NGS
KITS de Preparo para Biblioteca NGS
 
O que é X Frágil?
O que é X Frágil?O que é X Frágil?
O que é X Frágil?
 
Escolha um parceiro e não um fornecedor
Escolha um parceiro e não um fornecedorEscolha um parceiro e não um fornecedor
Escolha um parceiro e não um fornecedor
 
Eletroforese Capilar Automatizada
Eletroforese Capilar Automatizada Eletroforese Capilar Automatizada
Eletroforese Capilar Automatizada
 
Analysis of Trace Elements in Fertilizer with AVIO 200 ICP-OES
Analysis of Trace Elements in Fertilizer with AVIO 200 ICP-OESAnalysis of Trace Elements in Fertilizer with AVIO 200 ICP-OES
Analysis of Trace Elements in Fertilizer with AVIO 200 ICP-OES
 
Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...
Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...
Analysis of Impurities in Semiconductor-Grade Hydrochloric Acid with the NexI...
 
New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...
New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...
New Research Evaluating Cisplatin Uptake in Ovarian Cancer Cells by Single Ce...
 
CG Clarus® All In One
CG Clarus® All In OneCG Clarus® All In One
CG Clarus® All In One
 
High Quality DNA Isolation Suitable for Ultra Rapid Sequencing
High Quality DNA Isolation Suitable for Ultra Rapid SequencingHigh Quality DNA Isolation Suitable for Ultra Rapid Sequencing
High Quality DNA Isolation Suitable for Ultra Rapid Sequencing
 

Dernier

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CVKhem
 

Dernier (20)

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 

Analysis of Vanadium, Nickel, Sodium, and Iron in Fuel Oils using Flame Atomic Absorption Spectrophotometry

  • 1. a p p l i c at i o n N o t e Atomic Absorption Author Stan Smith PerkinElmer, Inc. Shelton, CT 06484 USA Analysis of Vanadium, Nickel, Sodium, and Iron in Fuel Oils using Flame Atomic Absorption Spectrophotometry Introduction Elemental analysis of fuel oil is an important step in quantifying its quality. Combustion of fuels containing metals can lead to the formation of low melting-point compounds that are corrosive to metal parts. The presence of certain metals, even at trace levels, can deactivate or foul catalysts used during the processing of the oil. ASTM® International publishes numerous test methods for the analysis of petroleum products, including fuel oils. ASTM® D5863-00a (2005), “Standard Test Methods for Determination of Nickel, Vanadium, Iron, and Sodium in Crude Oils and Residual Fuels by Flame Atomic Absorption Spectrometry”, is an industry-standard method for the analysis of fuel oils. Due to its multi-element capabilities, inductively coupled plasma optical emission spectroscopy (ICP-OES) may be the preferred technique for petroleum analyses requiring many elements, however, flame atomic absorption spectrophotometry (FAAS) methods are still quite effective and rapid for smaller numbers of elements such as those required for fuel oil analyses. In addition, flame AA instrumentation is significantly more compact than ICP-OES instruments, costs a fraction of the price, and requires less operator training.
  • 2. Experimental Conditions Instrumentation The analysis of a National Institute for Standards and Technology® (NIST®) Standard Reference Material (SRM) fuel oil was performed using a PerkinElmer® PinAAcle™ 900T spectrometer (Figure 1) operated in the flame mode. A stainless steel nebulizer (Part Nos. Nebulizer: N3160143; End Cap: N3160102) was used along with a solvent-resistant Kalrez® o-ring (Part No. N9300065) in the burner chamber and a solvent-resistant drain assembly. Hollow cathode lamps (Part Nos. V: N3050186, Ni: N3050152, Na: N3050148, Fe: N3050126) were used for all analyses and an air-acetylene flame was used for all elements except vanadium which was analyzed with a nitrous oxide-acetylene flame (Burner Head Part No. N0400100). Optimized parameters for each element are listed in Table 1. Table 1. Optimized experimental conditions for the analysis of metals in fuel oil using the PinAAcle 900T spectrometer. Analtye Wavelength (nm) Vanadium Nickel Sodium Iron 318.40 232.00 589.00 248.33 Slit Width (nm) 0.7 0.2 0.2 0.2 Read Time (sec) 3.0 3.0 3.0 3.0 Nitrous Oxide Air Air Air Oxidant Oxidant Flow (L/min) 6.0 10.0 10.0 10.0 Acetylene Flow (L/min) 6.7 2.5 2.5 2.5 Sample Uptake Rate (mL/min) 2.25 2.25 2.25 2.25 Standard and Sample Preparation Per Test Method B of ASTM® D5863, the sample and standards were prepared by solvent dilution. The solvent used was V-SOLV™ from VHG Labs (Part No. N9308265), a refined kerosene-like solvent. This method recommends the preparation of the oil in solvent at either a 5% ratio or a 20% ratio, depending on the actual concentration of the elements. In this experiment, both ratios were run to encompass the range of concentrations in the NIST® SRM and to determine if there would be any bias between the two oil ratios. Figure 1. PerkinElmer PinAAcle 900T and quick change burner assembly with stainless steel nebulizer and air-acetylene burner head. Default recommended conditions found in the WinLab32™ for AA software were used for most parameters (Table 1). When analyzing high BTU organic solvents, however, the sample flow rate must be reduced as typical hydrocarbon solvents will flow faster than aqueous samples and hydrocarbon solvents are themselves fuel for the flame. The sample rate of 2.25 mL/min for the kerosene solvent (approximately 3 times lower than the typical 7 mL/min for aqueous samples) generated a lean blue flame and met the sensitivity checks for each element. For vanadium, which used a nitrous oxide-acetylene flame, the acetylene flow rate was adjusted to a slightly lower flow rate (6.0 L/min) from the default value (7.5 L/min) to provide a more stable flame. 2 Calibration standards were Multi-Element Metallo-Organic Standards (VHG labs) in 75 centistoke (cSt) hydrocarbon base oil. Three V23 standards at: 10 µg/g (Part No. N0776109), 50 µg/g (Part No. N0776104) and 500 µg/g (Part No. N0776106); along with a V21 standard at 100 µg/g (Part No. N9308306) were used. The standards contained 23 and 21 elements, respectively, including nickel (Ni), vanadium (V), sodium (Na), and iron (Fe). The blank was comprised of the 75 cSt hydrocarbon base oil (Part No. N0776103) diluted in solvent. Each of the three calibration stock standards (10, 50, and 500 µg/g) were diluted in V-SOLV™ to create calibration standards at 0.5, 2.5, and 10 mg/kg in both 5% and 20% total oil. The blank base oil was used to make up the difference, if necessary, between the calibration stock standard and the needed 5% or 20% oil. This calibration range was sufficient to address the observed concentration range of the fuel oil sample. The 100 µg/g standard was diluted in V-SOLV™ to produce a secondary source quality control (QC) sample at 5 mg/kg in both 5% and 20% total oil.
  • 3. The fuel oil analyzed was NIST® Standard Reference Material 1634c Trace Elements in Fuel Oil. The NIST® SRM included certified values for V and Ni and a noncertified value for Na. As no value was provided for Fe, a 3.62 mg/kg Fe matrix spike was prepared from a 5000 µg/g stock organometallic standard (VHG labs) for the NIST® sample. In the analysis of aqueous samples for sodium and vanadium, it is common to add 0.1% alkali salt such as KCl or LiCl to all standards and samples to act as an ionization suppressant. The high concentration of salt helps to control the ionization effects in the flame and prevent bias in the results. ASTM® D5863 does not call for the addition of an alkali salt, but a third set of calibration samples and NIST® SRM were prepared at 20% oil as stated above, but with the addition of 250 mg/kg of Li (5000 µg/g, Conostan S21 Organometallic Standard in Hydrocarbon Base Oil) to determine if vanadium results would improve with the presence of an ionization suppressant. It is difficult to spike significantly higher than this without affecting the total oil percentage due to the concentration of the stock organometallic standards. Table 2. Recoveries of trace elements in NIST® SRM 1634c using a 5% oil solution (mg/kg). Replicate Iron 1 15.2 18.0 35.0 28.8 Nickel Sodium Vanadium 2 15.4 18.2 34.4 30.4 3 15.4 18.0 35.2 28.8 Mean 15.3 18.1 34.9 29.3 Standard Deviation 0.12 0.14 0.42 0.92 Certified Value N/A 17.54 ± 0.21 37 28.19 ± 0.40 % Recovery N/A 103 94.2 104 *The uncertainty limits of the certified values are at a 95% confidence level. Table 3. Recoveries of trace elements in NIST® SRM 1634c using a 20% oil solution (mg/kg). Replicate Iron Nickel Vanadium Vanadium w/Li* Results and Discussion 15.6 17.5 26.5 29.9 2 15.5 17.7 26.7 29.7 3 15.5 17.7 26.7 29.7 Mean 15.5 17.6 26.7 29.7 Standard Deviation 0.029 0.13 0.12 0.17 % Recovery The instrument was optimized for the four elements prior to analysis and the conditions are provided in Table 1. The analytical sequence for each of the four elements was to calibrate the instrument, analyze the blank and 5 mg/kg QC sample, analyze the NIST® SRM and matrix spike where applicable, and re-analyze the blank and QC sample. 1 94.5 106 N/A 101 *250 mg/kg Li ionization suppressant NIST® and Spike Recoveries Efficacy of the method was established by favorable comparison of the obtained results to the certified values provided with the NIST® SRM (Tables 2-3). Certified values were provided for V and Ni and a noncertified value was provided for Na. No reference value was provided for Fe, and instead, a matrix spike was performed to demonstrate efficacy. The NIST® SRM was prepared at the 5% oil ratio and spiked with 3.62 mg/kg of Fe. The spike concentration was mid range for the calibration curve and approximately four times greater than the observed (diluted) sample concentration (0.79 mg/ kg) at 5% oil. The observed concentration of iron was 4.44 mg/ kg in the spiked aliquot for a recovery of 101%. While this does not specifically demonstrate the accuracy of the results, it does provide support. As can be seen by comparing the vanadium results between Tables 2 and 3, the lithium ionization suppressant had no significant effect on the results. These results support the conclusion that although an ionization suppressant is needed for aqueous samples, it is not necessary for organics and is consistent with the ASTM® method. Characteristic Concentration The analytical conditions were modified from the typical aqueous conditions to accommodate the matrix being comprised of oil and solvent. However, the characteristic concentration for each of the four elements was similar to the recommended values provided in the WinLab32 for AA software for aqueous conditions (Table 4 – Page 4). Published data for the characteristic concentrations in organic solutions was not available. However, considering the differences in the rate of sample introduction and the relative stability of aqueous and organic solutions, the characteristic concentrations for the two different matrices should be similar. 3
  • 4. Table 4. Characteristic concentrations for the analysis of metals in fuel oil. Reference values are for aqueous solutions (mg/kg). Analyte Aqueous Reference Value 5 % Oil 20 20 w/Li Iron 0.1 0.12 0.13 N/A Nickel 0.14 0.16 0.19 N/A Sodium 0.012 0.032 N/A N/A 1.9 0.67 0.77 0.79 Vanadium Calibration and Method Detection Limits The calibration range used for all elements at both the 5% and 20% dilution ratios was similar to that recommended in ASTM® D5863 and also appropriate for the NIST® SRM. All correlation coefficients were calculated with a non-linear through zero calibration equation and were greater than 0.999. All calibration curves were verified with the secondary source standard and returned recoveries of no more than ±5% of the prepared value (i.e., 5 mg/kg). Examples of two calibration curves are shown in Figures 2 and 3. Figure 3. Calibration curve for the detection of nickel in 5% oil using FAAS. The calculated MDL results clearly demonstrate that this method is more than adequate for the analysis of fuel oils and has excellent sensitivity. Table 6. MDL reported in mg/kg in varying oil content for the analysis of metals in fuel oil by FAAS. Analyte % Oil Std Dev MDL Iron 5 0.0034 0.011 20 0.0086 0.027 Nickel 5 0.0079 0.025 20 0.0089 0.028 Sodium 5 0.0039 0.012 Vanadium 5 0.033 0.10 0.034 0.11 20 (w/Li) Conclusions Figure 2. Calibration curve for the detection of vanadium in 20% oil using FAAS. In addition to the NIST® results comparison, the method detection limits were estimated by repetitive analysis of the 0.5 mg/kg calibration standard (Table 6). This standard was analyzed 7 times and the resultant standard deviation was multiplied by the Student’s t-value for 6 degrees of freedom and 99% confidence limits (3.143). The percentage of oil did not appear to have any significant effect on the method detection limit (MDL) results. The more concentrated 20% oil solutions have slightly poorer MDLs than that of the 5% solutions. Considering the complex matrix in these sample solutions, these MDLs are a very good indication that the instrument performs normally. Better performance can be achieved, when desired, by additional optimization of the operating parameters and maintaining the cleanliness of the sample introduction system. 4 While ICP-OES and ICP-MS instrumentation may receive more attention when it comes to metals analyses, FAAS is a viable option particularly in the petroleum industry. There are no less than 12 active ASTM® test methods available for the analysis of petroleum products by AA techniques. FAAS instrumentation offers rapid sample analysis, accuracy and precision, simple operation, a small instrument footprint, and all for a fraction of the price of the ICP instruments. The PinAAcle 900T spectrometer is an excellent choice for petroleum product analyses and can be used with the ASTM® test methods. Very few and simple, optional modifications are suggested to handle the organic matrix. Excellent accuracy has been demonstrated with a fuel oil SRM. The quick-change spray chamber allows for fast and simple conversion from aqueous to organic samples. The WinLab32 for AA software and its automated features simplify analyses, freeing up more of the analyst’s time. The PinAAcle 900F (flame only model) may also be used for this analysis.
  • 5. References 1. ASTM® Standard D5863, 2000a, “Standard Test Methods for Determination of Nickel, Vanadium, Iron, and Sodium in Crude Oils and Residual Fuels by Flame Atomic Absorption Spectrometry,” ASTM® International, West Conshohocken, PA, 2005, DOI: 10.1520/D5863-00AR05, www.astm.org. PerkinElmer, Inc. 940 Winter Street Waltham, MA 02451 USA P: (800) 762-4000 or (+1) 203-925-4602 www.perkinelmer.com For a complete listing of our global offices, visit www.perkinelmer.com/ContactUs Copyright ©2011, PerkinElmer, Inc. All rights reserved. PerkinElmer® is a registered trademark of PerkinElmer, Inc. All other trademarks are the property of their respective owners. 009830_01