AN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION SPECTROMETER FOR THE DETECTION OF NONMETALS IN THE VACUUM ULTRAVIOLET

BY

CARL G. YOUNG

A Dissertation Submitted to the Graduate Faculty of

WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES

in Partial Fulfillment of the Requirements

for the Degree of

DOCTOR OF PHILOSOPHY

Chemistry

August 2011

Winston-Salem, North Carolina

Approved By:

Bradley T. Jones, Ph.D., Advisor

Joaquim A. Nóbrega, Ph.D., Chairman

Ulrich Bierbach, Ph.D.

Christa L. Colyer, Ph.D.

Willie L. Hinze, Ph.D.

ii

ACKNOWLEDGEMENTS

This is an important accomplishment in my life, and I cannot share in this

moment without giving thanks to an important number of people. I am also extremely

blessed for having the chance to receive a graduate education at a fine institution like

Wake Forest University.

None of this work would have been possible without the grace, love, and mercy of

the living God. I am amazed at how far he has allowed me to bounce back after going

through some setbacks. I would like to thank my father, Lawrence R. Young, Sr. He has

shown me how to live with integrity and respect for my fellow man. I would like to thank

my mom, Carlene, for always believing in me. I want to thank my incredible wife Valerie

for always being there to give me encouragement and lift my spirits. I want to express

extreme gratitude to my in-laws Stan, Sue, and Jeramy Lowe. They have shown me what

it means to treat a stranger like family, and I am incredibly grateful for all of the time I

have spent with them.

The support of my friends here at Wake has been tremendous. To my former

labmates Dr. George Donati, Dr. Jiyan Gu, Dr. Summer Hanna, and Kathryn Pharr,

thanks for always offering advice and opinions on research. I will look back fondly on the

all of the time we spent in the lab together and the times we hung out outside of the

chemistry department. To Dr. Lindsey Oliver Davis, thanks for always being a great

friend and visiting Winston-Salem when your schedule allowed. Seeing you and Kricket

always made me laugh! To Dr. Tara Massie, your friendship has meant a lot to both

Valerie and I. Thanks for all of the words of encouragement and support.

iii

I would like to extend my extreme gratitude to my advisor Dr. Bradley T. Jones.

He has always been there to go over data, provide alternative suggestions for research,

and always took the time to explain something I did not understand. I would like to thank

my Richter Scholarship project advisor, and friend Dr. Joaquim A. Nóbrega. You are a

great example of treating your fellow man as you would yourself. Thanks for always

telling me “tudo bem.”

I would also like to thank my committee, Dr. Ulrich Bierbach, Dr. Christa Colyer,

and Dr. Willie L. Hinze, for their time and suggestions in completing this work. Thanks

to the Department of Chemistry, and especially Dr. Albert Rives, for being supportive

and encouraging in order to promote a great learning environment. It has been a pleasure

to perform research here.

iv

TABLE OF CONTENTS

PAGE

LIST OF TABLES AND FIGURES v

LIST OF ABBREVIATIONS ix

ABSTRACT xi

Chapter

I. INTRODUCTION 1

Published in Applied Spectroscopy Reviews, November 2009

II. DETERMINATION OF SULFUR IN BIODIESEL MICROEMULSIONS USING SUMMATION OF MULTIPLE LINES 47 Published in Talanta, January 2011

III. AN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION SPECTROMETER AS AN EMPIRICAL FORMULA DETECTOR FOR GC 72

IV. DETERMINATION OF THE TOTAL CARBON CONTENT IN SOFT DRINKS BY TUNGSTEN COIL ELECTROTHERMAL VAPORIZATION INDUCTIVELY COUPLED PLASMA SPECTROMETRY 92 Published in Microchemical Journal, March 2011

V. CONCLUSION 116

SCHOLASTIC VITA 118

v

LIST OF TABLES AND FIGURES

TABLES PAGE

CHAPTER I

1. Strong ICP-OES Lines in the VUV Region. 4

2. Relative Limits of Detection in the VUV and UV Regions. 8

3. Determination of Sulfur in the VUV Region. 12

4. Critical Concentration Ratios at the S 180.73 nm Line. 17

5. Determination of Phosphorus in the VUV Region. 19

6. Determination of Iodide in the VUV Region. 21

7. Determination of Carbon at 193.07 nm. 23

8. Absolute Detection Limits for Nonmetals in the NIR. 27

CHAPTER II

1. ICP-OES Parameters. 54

2. Emission Lines Used for Signal Summation. 57

3. Analytical Figures of Merit for the Method. 62

4. Detection Limits, PRESS, and RMSEP for the Lines

and Combinations of Emission Lines. 64

5. Addition and Recovery Experiment for Sample C. 65

6. Sample Volumes and Recoveries. 66

7. Sulfur Determination in Biodiesel Samples. 68

CHAPTER III

vi

1. Wavelengths Used in the UV and the Vis. 84

2. Empirical Formula Comparison to the Molecular Formula. 87

CHAPTER IV

1. ICP-AES Instrument Parameters Used. 100

2. Tungsten Coil Heating Cycle. 102

3. Tungsten Coil Aging Program. 104

4. Summary of Carbon Determination Results. 108

5. Analytical Figures of Merit for the Method. 108

vii

FIGURES PAGE

CHAPTER I

1. VUV ICP-OES Spectrum for a Solution Containing

Approximately 500 mg L-1 Br, Cl, I, P, and S. 6

2. Photographs of an Axial Purge Path (A) and Radial

Purge Path (B). 10

CHAPTER II

1. Noise Source Determination for 182.562 nm. 59

2. Comparison of Measured Noise and Calculated Noise

For Emission Line Combinations 1+2 and 1+2+3. 60

CHAPTER III

1. Schematic for the ICP-AES Empirical Formula Detector. 78

2. Relationship Between Dial Setting and Temperature of the

Oven for the Gow-Mac 350. 81

3. Relationship Between Dial Setting and Injection Port

Temperature for the Gow Mac 350. 82

4. Plot of the Emission Intensity of Carbon at 247.856 nm

and Hydrogen at 656.285 nm. 85

CHAPTER IV

viii

1. Schematic of the W-coil ICP-AES System. 99

2. Standard Addition Plots for the Determination of Carbon in

Pepsi (♦) Gatorade G2 (▲), and Fanta Orange (●). 106

ix

LIST OF ABBREVIATIONS

Abbreviation Definition

BEC Background Equivalence Concentration

CCD Charge Coupled Device

CID Charge Injection Device

ETA-LEAFS Electrothermal Atomization Laser Excited

Atomic Fluorescence Spectrometry

ETV Electrothermal Vaporization

FT Fourier Transform

GC Gas Chromatography

HPLC High Performance Liquid Chromatography

ICP AES Inductively Coupled Plasma Atomic

Emission Spectrometry

ICP-MS Inductively Coupled Plasma Mass

Spectrometry

ICP OES Inductively Coupled Plasma Optical

Emission Spectrometry

LDR Linear Dynamic Range

LOD Limit of Detection

NIR Near-infrared

NMR Nuclear Magnetic Resonance

NR Not Reported

PRESS Predicted Error Sum of Squares

x

PTFE Polytetrafluoroethylene

RCC Residual Carbon Content

RF Radio Frequency

RMSEP Root Mean Square Error of Prediction

SBR Signal to Background Ratio

S/N Signal-to-Noise Ratio

TRA Time Resolved Analysis

UV/Vis Ultraviolet/Visible

VUV Vacuum Ultraviolet

WCAAS Tungsten Coil Atomic Absorption

Spectrometry

WCAES Tungsten Coil Atomic Emission

Spectrometry

xi

ABSTRACT

Young, Carl G.

AN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION SPECTROMETER FOR THE DETECTION OF NONMETALS IN THE

VACUUM ULTRAVIOLET

Dissertation under the direction of Bradley T. Jones, Ph.D., Professor of Chemistry and Associate Dean of the Graduate School

Inductively coupled plasma atomic emission spectrometry (ICP-AES) has

emerged as a dominant spectroscopic technique for the determination of metals in a

plethora of sample types. The bulk of the interest has been placed on trace metal analysis,

and the analysis of nonmetals has been gaining increased interest since the 1980’s. In this

work, an inductively coupled plasma atomic emission spectrometer is used for the

determination of nonmentals in different sample types. The present research covers three

projects using ICP-AES to detect nonmetals by monitoring their emission in the vacuum

ultraviolet region of the electromagnetic spectrum.

In the first project, microemulsion is used for sample preparation and the

summation of the intensities of multiple emission lines is used for the determination of

sulfur in biodiesel samples. The sulfur atomic emission is monitored at 181.972 nm,

180.669 nm, and 182.562 nm. The experimentally determined amounts of sulfur ranged

from 2 to 7 mg L-1. Three different approaches were used to investigate the accuracy of

the analysis method.

xii

The second project demonstrates the utility of coupling a packed column GC to an

ICP-AES for the determination of the empirical formula of simple hydrocarbons. The

ICP monitors the carbon emission at 247.856 nm and the hydrogen emission at 656.285

nm. The emission signal is proportional to the mass of element present, so the empirical

formula can be determined independent of molecular structure. The capability of the

system is demonstrated using a mixture of hexane, benzene, and toluene separated with a

20% Carbowax on Chromsorb-P packed GC column, and helium as the mobile phase.

The third project determines the total carbon content in soft drinks using a

tungsten coil electrothermal vaporizer prior to analysis by ICP-AES. The tungsten coil is

extracted from a commercially produced 150 W, 15 V microscope bulb. The standard

additions method is employed to correct any matrix effects from the samples, and carbon

emission is monitored at 193.091 nm. Carbon content determined for the samples was in

the range of 13 to 60 g in one 8 fl oz serving, and these values agreed very well with the

label values (except for one sample, Orange Fanta, which provided a 200% recovery).

The detection limits for carbon range from 0.4 to 3 mg L-1, and absolute detection limits

range from 12 ng to 90 ng for a 30 µL aliquot of sample on the coil.

1

CHAPTER 1

INTRODUCTION

INDUCTIVELY COUPLED PLASMA OPTICAL EMISSION SPECTROMETRY

IN THE VACUUM ULTRAVIOLET REGION

Peng Wu,1 Xi Wu,

1 Xiandeng Hou,

1 Carl G. Young,

2 and Bradley T. Jones

2

1Analytical & Testing Center, Sichuan University, Chengdu, Sichuan, China

2Department of Chemistry, Wake Forest University, Winston-Salem, North Carolina

The following manuscript was published in Applied Spectroscopy Reviews, 2009, 44,

507-533 (doi: 10.1080/05704920903069398). Stylistic variations are due to the

requirements of the journal. First authorship is shared equally between Carl G. Young

and Peng Wu. The manuscript was edited by Bradley T. Jones.

2

ABSTRACT

Inductively coupled plasma optical emission spectrometry has been applied for

trace metal determination in a myriad of sample types. However, the detection of

nonmetals is a challenge. For example, the high excitation energies associated with most

nonmetals is a barrier for populating the excited state of these elements. Even in the

presence of sufficient excitation energy, the principal resonance lines for nonmetals

usually lie in the vacuum ultraviolet region, where atmospheric species like oxygen and

water vapor absorb the radiation. Several nonmetals (nitrogen, oxygen, and carbon) are

also present in the atmosphere, so contamination or background emission signals can

hinder quantification. A common approach to solving these problems is to increase

throughput by purging the optical path with an inert gas. In addition, unnecessary mirrors

or lenses are eliminated when possible. This review provides a survey of the applications

of inductively coupled plasma optical emission spectrometry in the vacuum ultraviolet

region, with particular emphasis on the detection of sulfur, phosphorus, iodine, and

carbon. The alternative of employing nonresonance lines for these elements in the near-

infrared region is discussed briefly as well.

Keywords: Inductively coupled plasma, optical emission spectrometry, vacuum ultra-

violet region, near-infrared region, nonmetals, carbon, iodine, phosphorus, sulfur

3

INTRODUCTION

Inductively coupled plasma optical emission spectrometry (ICP-OES) is one of

the most popular techniques for the determination of trace metals in a myriad of sample

types (1). Relatively few reports have described the detection of nonmetals, whose

principal resonance emission lines lie in the vacuum ultraviolet (VUV) region of the

spectrum. Observation of these lines with conventional instrumentation is complicated by

absorption due to oxygen and water vapor in the atmosphere and by the poor reflectivity

of mirrors and poor transmittance of lenses and windows in this region. As a result,

conventional spectrometers and detectors are not equipped to operate at wavelengths less

than 180 nm. With the proper equipment, however, elements such as sulfur, phosphorus,

iodine, and carbon may be detected with better sensitivity in the VUV than in the UV.

This review provides a summary of these applications. In a few cases, when VUV

sensitivity is low, nonresonant, near-infrared (NIR) transitions may be exploited.

ICP-OES IN THE VUV REGION

The VUV region is generally defined as the wavelength region below 200 nm, where

atmospheric oxygen and water vapor strongly absorb electromagnetic radiation. Though

VUV lines are not monitored as often as ultraviolet or visible ones in modern ICP-OES,

many elements have corresponding emission lines in the VUV. Nygaard and Leighty (2)

reported the ICP-OES lines for a variety of elements in the region between 160 and 200

nm, and the most analytically useful wavelengths are summarized in Table 1. These lines

were identified with 1000 mg L−1

stock solutions along with comparison to reference

wavelength tables (2). A survey of existing references reveals that all elements have

emission lines in the VUV except for H, He, Li, Na, K, Sc, Zn, Kr, Cd, Xe, Cs, Ce,

4

Table 1. Strong ICP-OES lines in the VUV region

Element Wavelengthsa (nm) Element Wavelengthsa (nm) Ag 170.93 Mn 191.54 Al 167.08, 176.64 Mo 198.8 As 189.04, 193.76 N 149.26, 149.28, 174.27 Au 174.047, 197.82 Nb 198.15 B 182.59, 182.64 Ni 174.15 Ba 192.42 O 130.22, 130.49, 130.60 Be 199.8 P 177.50, 178.29, 178.77 Bi 190.24 Pb 182.2 Br 157.48, 157.64, 163.34 Pd 193.23 C 165.8, 156.1, 193.07 Pt 177.71 Ca 184.01, 183.80 Re 190.94 Cl 133.57, 134.72, 135.17 Ru 187.56 Co 194.13, 195.01 S 166.67, 180.73, 182.04 Cr 189.89 Sb 187.62 Cu 197.99 Se 196.09 Fe 170.2 Si 185.07, 198.90 Ga 184.63 Sn 189.99 Ge 164.92 Sr 177.84 Hf 196.42 Te 182.24 Hg 184.95, 194.23 Ti 190.63, 190.83 I 178.28, 183.04 Tl 190.86 In 193.05 V 190.78

Mg 182.8 W 196.21 Zr 199.59

aWavelegnths above 160 nm are reported in Nygaard and Leighty (2); below 160 nm, in Heine et al. (5).

5

Rb, Y, Tc, Rh, Th, and U.

The use of the VUV lines for analytical ICP-OES applications was first proposed by

Kirkbright and coworkers (3, 4) in the early 1970s. In 1980, Denton also investigated the

qualitative aspects of an ICP in the spectral region between 120 and 185 nm (5). A

number of lines for oxygen, nitrogen, carbon, bromine, sulfur, and chlorine were

observed upon introduction of the appropriate gas or volatile organic liquid (Table 1).

The most promising analytical lines included the O triplet at 130 nm; the N line at 174.27

nm and the doublet at 149 nm; Br, 153.17 nm, 163.34 nm, and doublet at 157 nm; S,

180.73 nm, 166.67 nm, and doublet at 182 nm; and Cl, 134.72 nm, 133.57 nm, and

135.17 nm (Figure 1). The C line at 193.09 nm has been employed as an element-

selective detector for chromatographic separation (6). However, impurities are common

in the ICP in argon gas. Carbon, nitrogen, and oxygen peaks were observed in the ICP

background spectrum between 120 and 195 nm (5). Similar impurity peaks were

observed in the deeper VUV (down to 85 nm) (7), so plasma gas quality is a critical issue

in this region.

Some elements, such as sulfur and phosphorus, have their best analytical emission

lines in the VUV (8). For sulfur, there are no practical analytical lines in the ultraviolet or

visible regions, whereas for phosphorus, severe interferences are observed from iron and

copper at the 214.9 or 213.6 nm lines. Zarcinas reported that the Pb 168 nm line had a

detection limit superior to the conventional Pb 220 nm line (9). The 168 nm line was also

less prone to matrix interference, background continuum radiation interference, and

interelement interference from high concentrations of Al and Fe. The Pb 168 nm line was

therefore highly recommended for the analysis of soil samples. Elements in groups 13–15

often lack sensitive ionic emission lines in the UV, but their ionic emission lines in the

6

Figure 1. VUV ICP-OES spectrum for a solution containing approximately 500 mg L−1

Br, Cl, I, P, and S.

7

VUV are promising for analytical applications. Uehiro and coworkers reported that the

ionic emission lines for groups 13–15 elements in the VUV were much stronger than

those in the UV (10, 11). The most sensitive emission lines for Cl, Br, I, S, P, B, Tl, Hg,

and As lie in the VUV range (12–15). Heitland determined nonmetals in waste oils with

limits of detection (LODs) near or below the 1 µg g-1 level (14): 0.9 µg g-1 Cl, 2 µg g-1 Br,

0.5 µg g-1 I, 0.04 µg g-1 P, and 0.07 µg g-1 S. Naozuka and coworkers reported an

Ag+

precipitation/ammonia dissolution method for the determination of Cl, Br, and I in

milk samples with LODs of 0.8 µg mL−1

Cl, 1 µg mL−1

Br, and 2 µg mL−1

I (16). Using

oxidative chemical vapor generation, the sensitivity for halogens was further improved

and µg L−1

level LODs were obtained: Cl (134.72 nm) 1 µg L−1

, Br (154.06 nm) 2 µg L−1

,

and I (178.27 nm) 0.4 µg L−1

(17). In two more recent communications (18, 19), the

advantages of many VUV emission lines (125–180 nm) were enumerated. A suite of test

elements (Al, Br, Cl, Ga, Ge, I, In, N, P, Pb, Pt, S, and Te) had VUV emission lines with

higher signal-to-background ratios than those in the UV. Limits of detection improved by

factors in the range of 4–35 when switching from the UV to the VUV lines (Table 2).

Spectral interferences occurred less often in the VUV than in the UV region as well. For

example, for iron-containing samples, the intense Ga emission line at 417.204 nm line

overlapped the Fe emission line at 417.206 nm. The Ga emission line at 141.444 nm,

however, experienced no spectral interference. Similar findings have been reported for

Au, B, Ge, In, Pb, Te, and Tl. Nakahara et al. (20) and Wallace (21) demonstrated that

the routine determination of B in steel samples using the UV emission lines was hindered

by spectral interferences from Fe, but the B 182.64 emission line was interference free.

Linear working ranges have also been extended by using emission lines in the VUV

8

Table 2. Relative limits of detection in the VUV and UV regions (18)

Elements VUV (nm) LODa (µg L-1) UV (nm) LODa (µg L-1) Improvement factor Al 167.080 0.04 396.152 1 25 Ga 141.444 0.8 417.204 6 8 Ge 164.919 1 265.117 4 4 In 158.637 0.2 230.686 7 35 P 177.500 0.9 213.618 7 8

aLimits of detection are reported with one significant figure.

9

region.

ICP-OES spectrometers may be purged with an inert gas to prevent absorption of

radiation by oxygen in the VUV region. The purged optical paths for a commercial ICP-

OES system are shown in Figure 2. Alternatively, the spectrometer may be evacuated

with a vacuum pump, but the potential back-streaming of hydrocarbon vapor from the

pump oil is a serious concern. These vapors may eventually lead to the deposition of

particles on optical surfaces and clouding of the optical path. As a result, purge gas

systems are much more common.

Several different inert purge gases may be employed in the VUV. Kirkbright et al.

used nitrogen (3, 4), and Denton et al. used He (5). Nakahara argued that argon was the

better purge gas because it provided higher signal-to-background ratios and smaller

background equivalent concentrations (22). Using Ar as both the plasma and purge gas

can occasionally lead to the unwanted formation of a secondary plasma in the purge gas

tube (Figure 2). Drawbacks to purged systems include the increased instrumental

complexity and higher operating costs.

In ICP mass spectrometry, ion extraction is accomplished by immersing a water-

cooled metal sampler cone directly into the plasma. The sample gas in the central channel

of the plasma passes through the orifice in the cone and enters the vacuum system of the

mass spectrometer. A similar arrangement may be employed to eliminate atmospheric

interference in the VUV region. Houk et al. used a copper skimmer cone to detect VUV

emission lines for argon (23) and other nonmetals (24, 25). Helium purge gas flowed

through the spectrometer and sampling cone. The optical path was kept free of lenses,

mirrors, and windows to eliminate transmission and reflection loss in the deep

10

Figure 2. Photographs of an axial purge path (A) and radial purge path (B). (Photographs

courtesy of Teledyne Leeman Labs)

11

VUV region. With this arrangement, argon resonance lines down to 58 nm were observed.

Two intense argon lines were observed at 106.67 and 104.82 nm. Ultrasonic nebulization

yielded at least a one-order-of-magnitude improvement in LODs compared to

conventional pneumatic nebulization for most elements in the VUV (24). A direct

injection probe for gaseous samples provided LODs of 50, 20, 80, and 20 pg for Br, C, Cl,

and S, respectively (25). The technique showed promise for the determination of low

amounts of persistent organic pollutants.

Though many nonmetals have resonant emission lines in the VUV region, most

published applications involve the determination of sulfur, phosphorus, iodine, and

carbon. Other elements, like arsenic and mercury (26), have some applications in the

VUV region, but they are typically detected at their conventional wavelengths, so they

are not covered in detail here.

SULFUR DETERMINATION

The conventional approaches for sulfur determination include gravimetric, tur-

bidmetric, and methylene-blue–based spectrophotometric methods. In general, these

methods are time consuming and insufficiently sensitive for routine sample analyses. As

a result, more applications have been reported for the VUV ICP-OES determination of S

than any other element (Table 3). Interest in total S content covers a broad range: from its

role in the formation of acid rain to its effect on the mechanical properties of steel.

Common sample types include water (11, 27–35), steel and metal solids (36–42), coal

and fuels (43–51), soil and agricultural materials (52–61), and biological and nutrition

samples (62–69). Sulfur may be present in these samples as several different species,

such as sulfate or sulfite, so high-performance liquid chromatography (HPLC) has been

12

Table 3. Determination of sulfur in the VUV region

Sample matrix and method

Wavelength (nm)

Purge gas LOD (µg mL-1)a Ref.

Sea water, direct determination

180.731 Ar 0.02 11

Natural water and boiler feed water,

on-line preconcentration of

sulfate using alumina

180.73 NR 0.003 27

Natural water, direct determination

180.73 Ar 0.08 28

Water and brines 180.73 Ar 0.07 29 Groundwaters,

converted sulfide to H2S vapor

180.7 Ar 0.0002 30

Fountain solutions 182.037 NR NR 31 Waste water, HPLC coupled with ICP-

OES

180.7 NR 20 ng 32

Marine ecosystem 180.780 NR NR 33 Surface water, ion-pair adsorption, Sc as internal standard

180 NR 0.0001 34

Water samples, vapor generation of

H2S

180.669 N2 0.005 35

Steel, matrix matched calibration

180.73 182.04 182.63

N2 0.9 1 3

36

Steel, electrolyte dissolution

180.7 Ar 0.6 µg g-1 37

Steel, direct solid sampling

conductive heating vaporization

180.676 NR 0.08 µg 38

Tantalum powder, solvent extraction

181.978 NR 0.2 39

Steel and gallium phosphide crystals, vapor generation of

H2S

180.73 NR 0.003 40

High-purity iron, 180.73 Ar 0.3 µg g-1 41

13

on-line preconcentration Fe-catalyst, matrix matched calibration

182.034 Ar 0.2 42

Crudes and heavy crude fractions,

direct determination

182.04 NR 100 43

Bituminous and subbituminous coal,

slurry sampling

182.04 Ar NR 44

Coal liquefaction, Se 190.09 nm as internal standard

180.73 Ar 0.003 45

Fuel and diesel fuel-like fractions,

direct determination

180.731 182.034

NR NR 46

Coal products, In 325.609 as internal

standard

180.731 Ar 1 µg g-1 47

Crude oils and related materials,

Parr bomb digestion

181.9 Ar NR 48

Heavy crude oil, emulsion crude oil

in water

181.9 Ar 0.6 49

Coal and related materials, Eschka

digestion, and matrix-matching

standards

180.731 Ar NR 50

Oil samples, on line supercritical fluid

extraction

182.7 NR 0.2 51

Biological and soil materials, acid

digestion

180.735 NR NR 52

Soil, chloroform extraction, fuming

HNO-KNO3 digestion

182.037 NR NR 53

Fodder, direct determination

180.731 NR NR 54

Peat material, comparison of acid-extraction and total

digestion

182.0 NR 0.05 55

14

Forest soil 180.669 N2 0.4 56 Soybean flour,

HPLC coupled with ICP-OES

180.6 NR NR 57

Conifer needles 182.04 N2 1 58 Fertilizers, direct

determination 180.731 NR NR 59

Soil and human hair, anion exchange

preconcentration

NR NR 0.006 60

Plant extracts, ion chromatography

coupled with ICP-OES

180.734 NR 0.02 0.09b

61

Amino acids, HPLC coupled with

ICP-OES

180.73 Ar 1-3 62

Metalloprotein, HPLC with ICP-

OES

180.73 N2 NR 63

Biological samples, acid digestion in a

Teflon bomb

180.7 N2 0.01 64

Wine samples, vapor generation of

SO2

180.676 NR 0.3 1c

65

Biological samples, oxygen bomb combustion digestion

181.912 NR NR 66

Rat organs, HPLC coupled with ICP-

OES

NR NR NR 67

Nutrition supplements, direct

determination

180.731 NR 3 68

Rat tissues, direct determination

NR NR NR 69

HPLC coupled with ICP-OES, post

column SO2 vapor generation

182.037 NR 0.6

70

Inorganic sulfates, HPLC coupled with

ICP-OES

182.04 NR 0.0008d 20 ng

71

15

NR: Not reported

aUnits for LOD are µg mL-1 (unless otherwise stated) and values are reported to one significant figure.

b0.02 (Sulfate) and 0.09 (organic) µg mL-1

c0.3 (Free SO2) and 1 (total SO2) µg mL-1

d0.06 (Sulfate) and 0.0008 (sulfite) µg mL-1

16

coupled to ICP-OES to perform sulfur speciation (32, 33, 57, 62, 63, 67, 70, 71).

Volatilization of sulfur-containing species by the addition of acid has improved transport

efficiency and led to improved detection power:

S2− + 2H

+→ H2S

HSO3−

+ H+→ H2O + SO

2

Sulfur has three strong emission lines in the VUV: 180.73 nm, 182.04 nm, and

182.63 nm. These arise from the triplet state via the 3P-

3S0 transition. The 180.73 nm line

is usually the most intense (50, 72). For some sample types, spectral interferences must

be taken into account. Kirkbright reported significant interferences at the S 180.73 nm

line due to Ni, Mn, and Fe at only a 50-fold concentration ratio (3). Lee and Pritchard

reported that the interferences from the Ni 180.45 nm line could be resolved using an ICP

spectrometer of higher resolution than Kirkbright’s (73). Calcium, Mn, Al, and Fe caused

interferences, however, and Table 4 lists their critical concentration ratios (concentration

ratio at which the interferent gives rise to a signal equal to that of the analyte). Several

other elements, including Cr, Cu, Ni, and Se, caused no interference at the S 180.73 nm

line. The interference due to Ca or Mn could be reduced by observing S emission at a

lower observation height in the plasma. Calcium caused significant spectral overlap with

the S 180.73 nm line (74), so trace determinations were difficult in real samples. Eames

and Cosstick defined a concentration factor to correct the spectral interference from Ca

(75). The instrument was calibrated with pure sulfur standard solutions. Then a series of

calcium standard solutions was analyzed as if they were S-containing samples. A

17

Table 4. Critical concentration ratios at the S 180.73 nm line (26)

Interferent Critical concentration ratioa Ca 90 Mn 303 Al 3330 Fe 15,000

aAt the critical concentration ratio, the analyte and the interferent give rise to the same signal. The concentration of the interferent is the numerator, and that for the analyte is the denominator.

18

regression line constructed from the Ca solutions revealed an apparent sulfur

concentration as a function of calcium concentration. By measuring the Ca concentration

in the sample at a different wavelength, a correction factor could then be applied to the

measured S concentration. A second Ca interference-correcting method based upon

multiple linear regression was recommended by Kola and coworkers (76).

PHOSPHORUS DETERMINATION

Phosphorus has three VUV emission lines at 177.50 nm, 178.29 nm, and 178.77

nm. The 178.29 nm line is typically the strongest (77). Unlike sulfur, phosphorus has two

strong emission lines in the conventional UV region of the spectrum as well: 213.62 nm

and 214.91 nm. The 213.62 nm line encounters spectral interference from Cu, Cr, Fe, V,

and Ti. Likewise, the 214.91 nm line experiences spectral interference from Cu, Fe, Al,

and V. The VUV lines are therefore employed in methods for samples containing high

amounts of these interferents, such as the determination of P in metals (38, 78, 79). As

with S, P has been detected in water samples using the VUV lines (11, 80, 81).

Phosphorus has also been detected in foods (82, 83), drugs (84, 85), and p-

nitrophenylphosphate (86). A summary of ICP-OES methods for the determination of

phosphorus using VUV lines is given in Table 5.

IODINE DETERMINATION

Iodine has two commonly employed emission lines in the VUV region: the 178.3

nm resonance line and a 183.0 nm line. Direct determination of I in the VUV is

complicated by high concentrations of chlorine in the sample matrix. Oxidation to

produce elemental iodine is a common approach for improving sample transport

efficiency and reducing chlorine interference. Frequently used oxidants are bromate,

19

Table 5. Determination of phosphorus in the VUV region Sample matrix and

method Wavelength

(nm) Purge gas LOD (µg mL-1) Ref. a

Tantalum powder, solvent extraction

178.229 NR 0.2 38

Carbon ferro-chrome, matrix matched

calibration

178.3 Ar 0.006% 78

Ferromanganese, matrix matched calibration

178.287 NR 0.03% 79

Sea water, direct determination

177.499 Ar 0.008 11

Wastewater, direct determination of total P

178.287 177.499

N 0.02 2 0.5

80

Water samples, direct determination

178.822 NR 0.03 81

Food, microwave digestion, and direct

determination

178.29 NR 0.004 82

Milk 178.6 NR NR 83 Cyclophosphamide, direct determination

178.287 NR 0.01 84

Multivitamins preparations, slurry

sampling

177.495 NR NR 85

p-Nitrophenylphosphate, hydride generation sampling, thermal reduction to PH

178.287

3

NR NR 86

NR: Not reported aUnits for LOD are µg mL-1 (unless otherwise stated) and values are reported to one significant figure.

20

peroxodisulfate, and hydrogen peroxide (87). The oxidation equations follow:

BrO3−+ 6I

−+ 6H

+→ Br

−+ 3I2 + 3H2

S

O

2O82−

+ 2I−+ 2H

+→ 2HSO4

−+ I2

H2O2 + 2I−+ 2H

+→ I2 + 2H2

The elemental iodine resulting from the oxidation reactions is volatile. The

transport efficiency of the reaction product is therefore much improved over conventional

pneumatic nebulization techniques. Dolan et al. reported on-line pre-concentration

combined with oxidation to improve the LOD for iodine using an Ar/He mixture gas

discharge (88). An improvement factor of 200 was obtained for the LOD for I−

(0.8 ng

mL−1

), but only a factor of 15 improvement was reported for IO3 −

after reduction to

elemental iodine. Therefore, the oxidant concentration must be optimized so that I2 is not

further oxidized to IO3 −:

O

I2 + BrO3−→ Br2 + 2IO3

−

If the I2 is partially oxidized to IO3−, the full effect of the increase in transport

efficiency would not be realized. The VUV lines have been used to detect iodine in water

samples (11, 89–93), foods and dietary supplements (94–96), and gas streams (97). VUV

iodine applications are summarized in Table 6.

CARBON DETERMINATION

A single wavelength has been reported for almost all of the carbon applications in

the VUV region: 193.07 nm. This emission line may not be the most intense (5), but its

21

Table 6. Determination of iodine in the VUV region

Sample Wavelength (nm)

Purge gas LOD (µg mL-1)a Ref

Sea water 178.276 183.038

Ar 0.02 0.08

11

Ground water, oxidation, and

using a membrane gas-liquid separator

178.276 NR 0.005 89

Water, iodide, and iodate

178.28 Ar 0.002 90

Brines, continuous

vapor generation

178.28 183.04

N2 0.0004 0.0006

91

Synthetic sea water, vapor generation

178.267 NR 0.01 92

Synthetic sea water, on-line

oxidation

178.28 NR 0.04 93

Dietary supplement

products

178.26 183.038

NR 0.4 0.7

94

Enriched chlorella

182.980 Ar 0.03 95

Milk sample, vapor

generation

178.218 NR 0.02 96

Process off-gas, gas sampling

178.28 N2 0.0002 97

NR: Not reported

aLOD values are reported with one significant figure.

22

wavelength is easiest to reach with conventional spectrometers. Carbon is practically

ubiquitous, so some carbon background is almost always present. Air contains carbon

dioxide, which becomes entrained into the ICP, and this significantly contributes to the

carbon background level. An extended ICP torch minimizes entrained air and improves

background levels for both carbon and nitrogen (98). All aqueous regents must be

purified to reduce the risk of carbon contamination in the blank. High-purity Ar plasma

gas is required as well.

The ICP-OES determination of carbon using the VUV line has been applied to the

determination of amino acids (99, 100) and carbohydrates (101). Carbon also has been

detected in water samples (102) and foods (103). The main limitation to C determination

by direct ICP-OES is the nonspecificity. The ICP measures total carbon content only

(102), so more often than not a separation step (such as HPLC) is performed prior to the

elemental analysis. For example, sucrose, glucose, and fructose (which have poor

sensitivity by HPLC with a UV detector) can be easily quantified by HPLC -ICP-OES

(101). In fact, a single calibration curve can be used for multiple analytes with similar

mass percent carbon (104). A summary of reported methods for the VUV ICP-OES

determination of carbon is given in Table 7.

ELECTROTHERMAL VAPORIZATION IN THE VUV REGION

Though nonmetals may be detected in the VUV as described above, LODs are

generally poor compared to metals detected in the UV or visible regions of the spectrum.

The common pneumatic nebulizer is known to have very low mass transport efficiency

(less than 10%). This affects sensitivity in all regions of the spectrum, but it could be

especially problematic in the VUV. Furthermore, the removal of solvent from the sample

23

Table 7. Determination of carbon at 193.07 nm

Sample Method LOD (as carbon)a Ref. Amino acids HPLC coupled to

ICP-OES 200 ng 99

Amino acids HPLC coupled to ICP-OES,

enantiomeric separation

3 ng 100

Aqueous carbohydrate

HPLC coupled to ICP-OES

50 ng 101

Water samples Total organic carbon and

inorganic carbon determination

0.007 µg mL-1b 0.0007 µg mL-1b

102

Foods Carbohydrates, carboxylic acids, alcohols, HPLC

coupled to ICP-OES

2-7 µg mL-1 103

Amino acids Multi-analyte HPLC calibration curve

2-5 µg mL-1 104

aLOD values are reported with one significant figure

b0.07 (Organic) and 0.007 (inorganic) µg mL-1.

24

mist could lead to more efficient excitation of nonmetals. The electrothermal vaporizer

(ETV) addresses both of these deficiencies. The analyte is separated from the solvent

prior to sample introduction, and the ETV efficiency may approach 80%. In addition, the

ETV is capable of selective vaporization of particular analytes in a complicated sample.

Okamoto and coworkers used an ETV sample introduction device for the determination

of P and S in environmental samples (105). Wennrich compared pneumatic nebulization,

ultrasonic nebulization, and ETV sample introduction for the determination of S, P, I, and

Br (106). Subnanogram amounts of S, P, and I could be detected in microsamples with

the ETV system. Wennrich and coworkers subsequently investigated the relationship

between type of sulfur (107) or phosphorus (108) species present in the sample and their

evolution from the ETV device. In the absence of matrix modifiers, significant errors

were possible. The temperature required for the release of phosphorus or sulfur from the

ETV was significantly lower than the temperature at which thermal decomposition took

place. The universal modifier used for metal determination with electrothermal

atomization atomic absorption spectrometry, Pd(NO3)2, also stabilized the phosphates

and sulfates during the thermal treatment steps with the ETV.

ICP-OES IN THE NIR REGION

Though nonmetals may be detected in the VUV region, sensitivity may be low

and poor optical throughput requires special instrumentation and the cost of an additional

purge gas. A viable alternative is to view nonresonance lines for these elements in the

NIR region of the spectrum. Near-IR emission lines arise from transitions between upper

states with energies in the 11 to 16 eV range to lower states with energies from 9 to 11

eV. Some NIR emission lines are very intense and can be observed with air-path

25

spectrometers. The optimal viewing position for NIR lines may differ from that in the UV

or visible regions. The areas between the load coil turns tend to be the zones of maximum

emission. As with the VUV determination of nonmetals, entrained gases from the

atmosphere could cause background contamination, so an extended ICP torch is

recommended for the NIR as well.

The first application of ICP-OES in the NIR region was reported by Fry and

coworkers at Kansas State University in 1980 (109). They used an argon ICP to populate

the quintet, triplet, and singlet states of atomic oxygen up to15.94 eV. The same group

published a series of manuscripts describing the NIR detection of N (110), F (111), Cl

and Br (112), and C and S (113). The NIR atomic emission lines for O and N have been

employed for detection in gas chromatography (114, 115). Mitko and Bebek evaluated

the 700.52 nm line for the determination of Br in salinated water, but they observed that

the VUV lines provided much higher sensitivity (116).

Spectral interference in the NIR may arise from argon emission lines and perhaps

from C and N impurities in the plasma gas. For example, the strongest N line observed in

the ICP spectrum in the NIR region occurs at 868.027 nm. This line is in the vicinity of

the Ar line at 867.843 nm, which may be rather intense. The N 821.631 nm line may be

employed instead, if a large spectral bandpass is used to improve S/N. The strongest line

for I in the NIR occurs at 905.833 nm, which is in the proximity of the C lines at 906.143

and 906.247 nm. Alternative C lines exist at 804.374 nm and 902.240 nm. In any event,

all of these spectral lines are easily isolated with only modest spectral resolution. The

NIR region is otherwise relatively free from spectral interferences.

26

Several ICP applications in the NIR have been performed with linear photodiode

array detectors (117–119). In fact, most modern ICP instruments are equipped with two-

dimensional array detectors, but these usually do not cover the VUV or NIR regions.

Multielement detection of nonmetals could be of interest to synthetic chemists for the

potential elemental analyses of reaction products. Because spectral interferences are rare

in the NIR, a low-cost, low-dispersion instrument could be developed for this purpose.

Fourier transform interferometers have been employed in the NIR region (120,

121). In these cases, simultaneous determination of nonmetals is also possible, and the

interferometer provides the classic throughput advantage, which balances the relative

insensitivity of detectors in the IR region. Furthermore, the longer wavelengths in the

NIR are easier to sample with the precise movement of the interferometer than the very

short VUV wavelengths. FT ICP spectrometers have led to the discovery of new emission

lines for C and S in the NIR.

Because the electronic structure of the He atom is quite simple, the spectral

background for the He ICP in the NIR region is expected to be even less complicated

than that of the Ar plasma (122). Unfortunately, He ICP systems are much more

expensive to operate than their Ar counterparts. Stubley and Horlick (123) developed a

low-resolution (8 cm−1

) interferometer with a PbS detector and a mixed gas plasma (Ar-

N2) to determine nonmetals in the NIR.

Table 8 summarizes the most intense ICP-OES emission lines for nonmetals in

the NIR region.

27

Table 8. Absolute detection limits for nonmetals in the NIR

Element Strongest line (nm) LOD (µg) Ref. O 715.680 0.5 109 N 868.027 0.3 110 F 685.602 0.4 111 Cl 837.597 0.05 112 Br 827.244 0.05 112 C 909.483 0.1 113 S 921.291 0.006 112 I 905.833 NR 118 H 656.28 NR 119

NR: Not reported.

28

CONCLUSION

ICP-OES may be employed for the determination of nonmetals in the VUV region

of the spectrum. Due to the high excitation energies for these elements, VUV sensitivities

may be low. Other difficulties with the VUV region may be overcome by purging the

light path with an inert gas and carefully controlling the purity of the plasma gas.

Alternatively, nonresonant transitions for the nonmetals may be monitored in the NIR,

where atmospheric gases are allowable in the optical path and spectral interferences are

less common. Though detection limits for nonmetals do not approach those observed for

most transition metals, the multitude of potential applications for nonmetal detection

warrants further investigation.

ACKNOWLEDGEMENTS

This material is based upon work supported by the National Science Foundation and the

Department of Homeland Security through the joint Academic Research Initiatives

program: CBET 0736214 and Grant Award Number 2008-DN-077ARI001-02. Xiandeng

Hou acknowledges the financial support for this project from the National Natural

Science Foundation of China (No. 20675053).

29

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47

CHAPTER II

DETERMINATION OF SULFUR IN BIODIESEL MICROEMULSIONS USING

SUMMATION OF MULTIPLE LINES

Carl G. Young, Renata S. Amais, Daniela Schiavo, Edivaldo E. Garcia, Joaquim A.

Nóbrega, and Bradley T. Jones

The following manuscript was published in Talanta, 2011, 84, 995-999 (doi:

10.1016/j.talanta.2011.01.008), and is reprinted with permission. Stylistic variations are

due to the requirements of the journal. All of the presented research was conducted by

Carl G. Young with assistance from Renata S. Amais. The manuscript was prepared by

Carl G. Young and edited by Joaquim A. Nóbrega and Bradley T. Jones.

48

ABSTRACT

A method for the determination of sulfur in biodiesel samples by inductively

coupled plasma optical emission spectrometry which uses microemulsion for sample

preparation and the summation of the intensities of multiple emission lines has been

developed. Microemulsions were prepared using 0.5 mL of 20% v/v HNO3, 0.5 mL of

Triton X-100, 2 - 3 mL of biodiesel sample, and diluted with n-propanol to a final volume

of 10 mL. Summation of the emission intensities of multiple sulfur lines allowed for

increased accuracy and sensitivity. The amounts of sulfur determined experimentally

were between 2 and 7 mg L-1, well below legislative standards for many countries.

Recoveries obtained ranged from 72 to 119%, and recoveries obtained for the 182.562

nm line were slightly lower. This is most likely due to its lower sensitivity. Using

microemulsion for sample preparation and the summation of the intensities of multiple

emission lines for the successful determination of sulfur in biodiesel has been

demonstrated.

Keywords: Biodiesel, microemulsion, inductively coupled plasma optical emission

spectrometry (ICP OES), multiple lines, summation of signal intensities

49

1. INTRODUCTION

Due to the instability in the petroleum market in recent years, development of an

alternative fuel is gaining increased importance. Moreover, the use of petrol products has

inundated the environment with pollutants such as NOx, SOx

Limits to the sulfur content in biodiesel have been restricted by certain governments

and agencies across the world. According to EN 14214 in Europe, the maximum

allowable amount of sulfur in biodiesel is 10 mg kg

, CO and metals such as Cd,

Co, Cu, Pb, V, and Ni [1]. One alternative fuel attracting a lot of attention in publications

and government agencies is biodiesel. Biodiesel is created by the alcoholic

transesterification of vegetable oil, vegetable fat, or animal fat in the presence of catalyst

[2]. Biodiesel is advantageous to the environment because it is mainly produced from

renewable resources.

-1, compared with that of 500 mg kg-1

according to ASTM D6751 in the United States [3]. Although, the sulfur content in

biodiesel is generally believed to be between 0.2 and 25 mg kg-1, depending on the

feedstock and the supplier [4]. In order to measure such low levels, analytical methods

with high sensitivity are needed. However, relatively little work is described in the

literature regarding the analysis of sulfur in biodiesel. The published work for sulfur

analysis ranges from chromatographic to spectroanalytical methods. A combustion ion

chromatographic system has been described for the simultaneous, speciated analysis of

halides (F, Cl, Br, I) and sulfur compounds in any nonaqueous sample matrix [5].

Detection limits in the sub-ppm range were reported. X-ray fluorescence may be

successfully applied for determining S in petroleum diesel because it is rapid, precise,

inexpensive, and accurate if properly calibrated [4]. X-ray fluorescence with gravimetric

50

standard additions method was performed for the determination of S in biodiesel to help

overcome the ca. 16 % low bias caused by an oxygen matrix effect [4]. The use of the

standard additions method overcame the low biased measurements obtained with using

petroleum diesel for calibration at the 3, 7, and 12 mg kg-1

Ultrasound-assisted oxidative desulfurization is used for the removal of sulfur from

petroleum product feedstock [6]. Under optimized conditions, the sulfur removal was

about 95% after 9 min of ultrasonic irradiation using hydrogen peroxide and acetic acid,

followed by extraction with methanol. However, the procedure developed by Mello et al.

[6] is strictly for sulfur removal and not quantification. The total amount of sulfur had to

be determined by other spectroscopic techniques such as ultraviolet fluorescence and ICP

OES.

levels. However, if hundreds

of biodiesel samples are to be analyzed, using the standard additions method may be

impractical.

Sample preparation is a critical step in any analytical procedure. Microwave- assisted

digestion in a closed system was compared to an open system with conventional heating

for the simultaneous determination of Ca, P, Mg, K, and Na in biodiesel by ICP OES

with axial viewing [7]. The optimized microwave assisted digestion procedure provided

recoveries of 89.0-103.0 % and deviations lower than 5%, in most cases. Microwave-

assisted digestion procedures are desirable because they do not require the preparation of

calibration standards, or the use of toxic solvents [7]. Organic samples may also be

analyzed by emulsions. An emulsion is a heterogeneous system made up of two liquid

phases, one of them dispersed in the other by means of a mechanical process [1]. Murillo

and Chirinos emulsified NIST crude oil samples in water for the determination of S, Ni,

51

and V in crude oil [8]. Aqueous calibration standards were made with the same amount of

emulsifier and solvent. No statistically significant differences were reported for the

results of their method and the certified values. Emulsions are not very stable systems

and have a problem with the miscibility of the liquids, although adding surfactant can

improve emulsion stability [1].

Alternatively, a microemulsion is a transparent, three component system composed of

water, oil, and an amphiphilic compound, such as an alcohol [2]. The benefits to using a

microemulsion are the following: instant formation, thermodynamically stable, and low

viscosity [2]. The main difference between an emulsion and a microemulsion is the

droplet size. Since a microemulsion shows characteristic structural dimensions between 5

and 100 nm, the medium present is a poor scatterer of visible light, thus transparency is a

consequence [9]. Perhaps the biggest advantage that microemulsions provide is the

ability to use an inorganic standard to perform a matrix matched calibration [11].

Preparation of calibration solutions with a matrix that matches that of the sample will

provide accurate results. Direct introduction of biodiesel samples into an ICP-MS by

using microemulsions for the determination of Cd, Co, Cu, Mn, Ni, Pb, Ti, and Zn has

been described [12]. An argon-oxygen gas mixture was introduced to the plasma as an

auxiliary gas to help correct any matrix effects caused by the high carbon load from the

microemulsion preparation.

In this work, an analytical procedure using microemulsion for sample preparation

and the summation of the intensities of multiple emission lines was evaluated for the

determination of sulfur in biodiesel samples made from different vegetable and animal

sources. The summation of signal intensities was recently demonstrated for ICP-OES

52

measurements [10]. In order to avoid out-of-control error propagation some criteria

should be met for successfully applying the summation of signal intensities procedure:

1. No line added should be critically affected by spectral interferences;

2. No line added may present poor repeatability for successive measurements of

signal intensities;

3. Lines with very low relative intensities should not be used because their

contribution to sensitivity will be minor, but they may exert a major effect on

repeatability;

4. Samples with a deviation higher than ± 20% should be omitted from

calculating the mean sample concentration value in order to avoid bias to the

global data.

These criteria must be applied when the analyte presents a large number of

suitable emission lines, but they may be too restrictive for elements with a lower number

of emission lines which are also less intense.

53

2. Materials and Methods

2.1 Instrumentation and Operating Conditions An inductively coupled plasma optical emission spectrometer (Varian Vista AX,

Mulgrave, Australia) with an axially viewed configuration and CCD solid state detector

cooled at -35 °C by a Peltier system was employed. The echelle polychromator was

thermostated and allows for spectral measurements in the 174-766 nm range. An

additional gas flow controller (AGM-1, Varian) for adding oxygen (99.99%, White

Martins, Sertãozinho, SP, Brazil) as auxiliary gas in the ICP was used. Instrumental

parameters are summarized in Table 1.

2.2 Chemicals and Reagents

All reagents used were of analytical grade unless otherwise specified. Solutions were

prepared with distilled and deionized water obtained by using a Milli-Q® system

(Millipore, Billerica, MA, USA) to a resistivity of 18.2 MΩ cm. In order to avoid

contamination, all glassware and polypropylene flasks were washed and soaked in a 10%

v/v HNO3

For microemulsion preparation, HNO

solution and rinsed thoroughly with deionized water prior to use.

3 (Merck, Darmstadt, Germany) previously purified

using a sub-boiling system (Milestone, Sorisole, Italy) was used. Polyoxyethylene (10)

octylphenyl ether (Triton X-100) (Acros Organics, Morris Plains, NJ, USA), n-propanol,

and a certified MR-1824 light mineral oil (Tedia, Rio de Janeiro, RJ, Brazil) were used

without subsequent purification. Sulfur calibration solutions were prepared by dilution

from a 1000 mg L-1

The biodiesel samples were composed of the following mixtures: soy oil and cooking oil,

soy oil and cottonseed oil, soy oil and beef tallow.

S stock solution (Qhemis High Purity, Hexis, São Paulo, SP, Brazil).

54

Table 1

ICP OES Parameters

Parameter Value

Generator Frequency (MHz) 40

Torch Inner diameter 2.3 mm

Sample Introduction System

Spray Chamber Cyclonic

Nebulizer Concentric

RF Applied Power (kW) 1.4

Signal Integration Time (s) 1.0

Plasma gas flow rate (L min-1 15 )

Auxiliary gas flow rate (L min-1 1.5 )

Oxygen flow rate (mL min-1 165.0 )

Nebulizer gas flow rate (L min-1 0.7 )

Sample flow rate (mL min-1 1.0 )

55

2.3 Microemulsion Preparation

A homogenous, transparent microemulsion was obtained when 0.5 mL of 20% v/v

HNO3

A similar procedure was used for the preparation of reference solutions. To obtain a

similar matrix to the biodiesel samples, 0.4 mL of mineral oil was added to the

microemulsion. It was demonstrated that adding a fivefold lower volume of mineral oil

than biodiesel adjusts the solution viscosity so that variations in aspiration rate and

aerosol formation are avoided [12]. A small amount of the inorganic standard was added

so that the microemulsion would be stable. The maximum concentration of reference

solution used was 50 mg L

, 0.5 mL of Triton X-100, and 2 - 3 mL of biodiesel sample was added to a

graduated polypropylene flask. The solution was diluted with n-propanol to a final

volume of 10 mL. The mixture was homogenized using a vortex mixer for 2 min.

-1

. However, it should be pointed out that this solution was

opaque after being vortexed, and cannot be considered a microemulsion.

56

3. RESULTS AND DISCUSSION

3.1 Behavior of Sulfur in the ICP OES

Sulfur determination in aqueous media is nontrivial. Sulfur has elevated ionization

energy (10 eV) [13] and its main emission lines from the plasma are in the vacuum

ultraviolet (110-200 nm) due to its electronic structure. It is reasonable to presume that

sulfur determination in organic media will present difficulties as well. Selection of a

single, sensitive emission line not affected by matrix effects may be critical for

quantitative determinations in ICP OES when working with less sensitive elements.

It has been suggested that the use of multiple emission lines to carry out quantitative

analysis may improve the sensitivity, precision and accuracy, and provide high flexibility

in the measurements, such as expansion of the linear range [10]. Factors to consider for

selecting the best emission line or combination of emission lines are elevated slope, a

correlation coefficient (r) close to unity, a near zero intercept, and emission lines with the

best accuracy [10]. Two additional parameters were also used to aid in the selection as

well: PRESS (Predicted error sum of squares) and RMSEP (Root mean square error of

prediction). The best combinations of lines have low PRESS and RMSEP values. The

summation of intensities of multiple emission lines was performed after selecting three

lines with the highest intensity. All possible combinations between these lines were tested.

Table 2 lists the emission lines used for this work.

57

Table 2 Emission lines used for signal summation.

Element Wavelength (nm) Relative Intensity

S (I)

a

181.972 323.6

S (I) 180.669 304.0

S (I) 182.562 77.7

a: Relative intensities obtained from the Varian ICP Expert Database.

58

The propagation of error using the summation of intensities of multiple emission lines

needs to be considered. Plots of the logarithm of the signal versus the logarithm of the

signal-to-noise ratio (S/N) were constructed for all emission lines used, and the dominant

source of noise present at each emission line was determined. The log-log plot for the

182.562 nm emission line is the most illustrative plot, and its result can be seen in Figure

1. The major source of noise present at 182.562 nm is a combination of shot noise and

detector noise, as evidenced by the slope of the log-log plot having a value of 0.85. The

log-log plots for the other emission lines had similar slopes (not shown in Figure 1), thus

the major source of noise present at those emission lines is also a combination of shot

noise and detector noise. In addition, a graph of all the measured noise points for the

181.972 nm + 180.669 nm and 181.972 nm + 180.669 nm + 182.562 nm emission line

combinations versus the calculated quadratic sum of the individual noises for those same

points was constructed, and can be seen in Figure 2. Below a threshold of approximately

30 signal units, the measured noise is often less than the calculated noise using the

quadratic sum. In this region, detector noise and shot noise are expected to be the major

noise sources, and the measured value results in a significant improvement of the S/N.

Above the threshold, the measured noise is often larger than the calculated noise. In this

region, flicker noise and shot noise are expected to be the dominant noise sources, so no

improvement in the S/N will be observed.

One aspect to keep in mind when considering the choice of emission lines is the

spectral environment. The background emission at one line could be considerably

different from the background emission at another line. A reasonable presumption is that

most emission lines are free from spectral interferences, but this is critically dependent on

59

Figure 1. Noise source determination for 182.562 nm.

0.0

0.5

1.0

1.5

2.0

2.5

1.4 1.9 2.4 2.9 3.4

Log

(S/N

)

Log S

60

Figure 2. Comparison of measured noise and calculated noise for emission line

combinations 1+2 and 1+2+3.

0

20

40

60

80

100

120

140

0 50 100 150 200 250

Calc

ulat

ed N

oise

Measured Noise

61

on the complexity of the sample medium. Back calculating the analyte concentration

from emission intensities should lead to the same analyte concentration. However,

emission lines affected by interference would produce results that deviated from an

assumed threshold value. If this is the case, the concentration value obtained from this

emission line should be omitted from the calculation of the mean concentration value. It

has been suggested that samples with a deviation higher than 20% should not be used in

the calculation of the mean concentration value [10]. Using the summation procedure

may overcome any interference caused by the spectral environment and provide more

accurate results for sulfur determination.

The oxygen gas flow rate in the composition of the auxiliary gas was optimized,

taking into account signal intensity and signal to background ratio (SBR). The oxygen

gas flow rate was varied from 12.5 to 212.5 mL min-1, and the variation of signal

intensity and SBR was not significantly different. Thus, an oxygen gas flow rate of 165

mL min-1

The nebulization gas flow rate also had to be considered, and it was evaluated

from 0.7 to 1.0 L min

was chosen because observed Swan bands were very low.

-1. When the nebulization gas flow rate was increased, a decrease of

signal intensity was observed, while the SBR value became slightly lower. Therefore, 0.7

L min-1

Analytical figures of merit are an indication of how well an instrumental

technique performs for the method of analysis. The figures of merit calculated for this

method include accuracy, precision, sensitivity, detection limit, linearity, and linear

dynamic range. Analytical figures of merit can be seen in Table 3.

was used for subsequent experiments. It is important to mention that under the

optimized conditions, carbon deposits on the torch were not observed.

62

Table 3

Analytical figures of merit for the method.

λ (nm) Precision (%RSD) Sensitivity Linear Dynamic Range

181.972 1.98 132.02 1.9 180.669 2.28 113.76 2.4 182.562 27.66 42.92 1.8

181.972 + 180.669 1.64 245.78 2.1 181.972 + 182.562 2.23 174.94 1.9 180.669 + 182.562 4.50 156.68 2.1 181.972 + 180.669

+ 182.562 1.82 288.70 2.0

63

The accuracy of the method will be discussed further below. The detection limits were

calculated using the concept of background equivalence concentration (BEC). The BEC

is defined as the concentration of analyte that produces a signal equal to the background

emission intensity at the spectral line of interest. Limits of detection were calculated for

all of the combinations used and can be seen in Table 4.

3.2 Determination of Sulfur in Biodiesel

Accuracy is how close an obtained experimental value is to a certified or theoretical

value. Addition and recovery experiments were performed in order to determine the

accuracy of the method. In one approach, a known amount of sulfur standard was spiked

into the microemulsion prepared for sample C. Results can be seen in Table 5. All

recoveries were acceptable, and between 93% and 119%. This indicates that a minimal

amount of sulfur is lost to the microemulsion preparation, followed by ICP OES

determination. The lowest recovery obtained was 93% for the 182.562 nm line. The

slightly lower recovery obtained for this line is most likely due to the lower relative

intensity of the 182.562 nm line. Further accuracy experiments were performed to double

check the validity of the traditional accuracy determination.

In the second approach, 2.5 mL and 3 mL of biodiesel sample were added to the

microemulsion for samples D-F, and the results were compared to the result obtained

when 2 mL of biodiesel was added. Results can be seen in Table 6. The recoveries were

mostly between 78% and 109%. It must be pointed out that the recoveries obtained for

the 182.562 nm line were in general lower than those obtained for the other lines and

combinations, i.e. from 51.6 to 71.1% for 5 of the 6 samples (not shown in Table 6). This

64

is most likely due to 182.562 nm having the least sensitivity when compared to the other

lines. The recoveries produced for the internal recovery are normalized to the theoretical

amount of intensity increase expected. For this reason, it appears that the recoveries are

slightly lower than the traditional recovery experiment mentioned above.

Table 4

Detection limits, PRESS, and RMSEP for the lines and combinations of emission lines.

Wavelength (nm) LOD

(mg L-1 PRESS )

RMSEP

1 181.972 0.60 1.2768 0.5053

2 180.669 0.21 0.0892 0.1336

3 182.562 0.80 1.8026 0.6004

1 + 2 181.972 + 180.669 0.42 0.5314 0.3260

1 + 3 181.972 + 182.562 0.63 0.2846 0.2386

2 + 3 180.669 + 182.562 0.36 0.0473 0.0973

1 + 2 + 3 181.972 + 180.669 +

182.562 0.46 0.1829 0.1913

65

Table 5

Addition and Recovery Experiment for Sample C.

Observed wavelength, λ (nm) % Recovery of Sample C

181.972 119

180.669 108

182.562 93.0

181.972 + 180.669 114

181.972 + 182.562 113

180.669 + 182.562 104

181.972 + 180.669 + 182.562 111

66

Table 6

Sample Volumes and Recoveries.

λ (nm) Sample D Sample E Sample F

%

Recovery

of 2.5 mL

spike

%

Recovery

of 3 mL

spike

%

Recovery

of 2.5 mL

spike

%

Recovery

of 3 mL

spike

%

Recovery

of 2.5 mL

spike

%

Recovery

of 3 mL

spike

181.972 109 105 98.0 96.5 96.0 105

180.669 106 90.4 105 91.6 88.3 87.4

181.972 +

180.669

108 98.5 101 94.6 92.9 97.7

181.972 +

182.562

95.0 93.4 91.5 85.6 98.8 97.0

180.669 +

182.562

89.9 81.5 93.4 78.2 93.6 80.3

181.972 +

180.669 +

182.562

98.8 92.4 95.8 87.6 95.0 93.5

67

It was presumed that using the best combination of emission lines would provide

better accuracy than using the most intense emission line alone. In a third approach, the

amount of sulfur was determined using different emission lines and their combinations.

The amounts of sulfur determined in the biodiesel samples can be seen in Table 7. The

amount of sulfur found in each sample is between 2 and 7 mg L-1, below the 10 mg kg-1

requirement by EN 14214 and 500 mg kg-1 by ATSM D6751 in the US [3]. Very similar

sulfur concentrations have been obtained when the sulfur concentration was determined

using different emission lines. The amounts of sulfur determined from emission lines

with the highest relative intensity were the most similar. Emission lines with lower

relative intensity produced sulfur concentrations that deviated slightly from the other

values. When the combination of lines was used, the line with the higher relative intensity

has greater influence on the concentration of sample determined. As a result, the

magnitude of the deviation in the sample concentration is lessened.

The three pronged approach for accuracy determination has produced interesting

results. Recoveries for the traditional spiking of a known amount of standard into sample

C and the internal recovery approach were acceptable. Since the recoveries obtained from

both approaches were near 80% and above, either approach will produce accurate results.

However, the internal recovery approach may be the best to use if any matrix effects are

likely. Adding increased amounts of the same sample will presumably have identical

qualitative matrices, but with larger amounts of concomitants. The amount of sulfur

determined at each emission line and their combinations was very similar. Based upon

the experimental evidence, the accuracy of the method for the determination of sulfur in

biodiesel has been established using simple and easily implemented approaches.

68

Table 7

Sulfur Determination in Biodiesel Samples.

λ (nm) Sample A Sample B Sample C Sample D Sample E Sample F

181.972 2.70 1.62 5.72 5.80 6.73 7.23

180.669 3.58 1.71 5.57 5.16 5.13 5.59

182.562 5.14 4.42 6.25 7.07 6.93 3.96

181.972 +

180.669

3.10 1.65 5.64 5.50 5.98 6.46

181.972 +

182.562

3.23 2.24 5.79 6.05 6.72 6.37

180.669 +

182.562

3.98 2.42 5.73 5.65 5.59 5.12

181.972 +

180.669 +

182.562

3.37 2.03 5.70 5.70 6.09 6.07

Average

concentration

± std dev

(mg L-1)

3.59 ±

0.79

2.30 ±

0.98

5.77 ±

0.22

5.85 ±

0.60

6.19 ±

0.67

5.83 ±

1.06

69

4. CONCLUSIONS

In the proposed procedure, an alternative approach for sample preparation was

demonstrated by simple and fast microemulsion formation. The main advantages

compared to the dilution method are the use of inorganic standards in the microemulsions

for calibration and the non-use of carcinogenic organic solvents. The summation of the

intensities of multiple emission lines in ICP OES was successful for the determination of

sulfur in biodiesel samples and it allows for better sensitivity, and good accuracy.

ACKNOWLEDGEMENTS

The authors would like to thank the Richter Scholarship for research funding. The authors

would like to extend their extreme gratitude to the Center for Characterization and

Development of Materials (CCDM), UFSCar-UNESP, São Carlos, SP, Brazil for the ICP

OES used for this work. Grant funds provided by Fundação de Amparo à Pesquisa do

Estado de São Paulo (FAPESP, Grant 2006/59083-9) and Conselho Nacional de

Desenvolvimento Científico e Tecnológico (CNPq, INCTAA) are appreciated. The

authors are also thankful to Prof. Dr. Edenir Rodrigues Pereira Filho for helpful

discussions about data treatment.

70

REFERENCES [1] E.S. Chaves, T.D. Saint’Pierre, E.J. dos Santos, L. Tormen, V.L.A.F. Bascuñan, A.J.

Curtius, J. Braz. Chem. Soc. 19 (2008) 856-861.

[2] J.S.A. Silva, E.S. Chaves, E.J. dos Santos, T.D. Saint’Pierre, V.L.A. Frescura, A.J.

Curtius, J. Braz. Chem. Soc. 21 (2010) 620-626.

[3] I.P. Lôbo, S.L.C. Ferreira, R.S. da Cruz, Quim. Nova. 32 (2009) 1596-1608.

[4] L.R. Barker, W.R. Kelly, W.F. Guthrie, Energy and Fuels 22 (2008) 2488-2490.

[5] C. Emmenegger, A. Wille, A. Steinbach, LC-GC North America Suppl. S Jun (2010)

40-43.

[6] P.A. Mello, F.A. Duarte, M.A.G. Nunes, M.S. Alencar, E.M. Moreira, M. Korn, V.L.

Dressler, E.M.M. Flores, Ultrason. Chem. 16 (2009) 732-736.

[7] M.G.A. Korn, D.C.M.B. dos Santos, M.A.B. Guida, I.S. Barbosa, M.L.C. Passos,

M.L.M.F.S. Saraiva, J.L.F.C. Lima, J. Braz. Chem. Soc. 21 (2010) 2278-2284.

[8] M. Murillo, J. Chirinos, J. Anal. At. Spectrom. 9 (1994) 237-240.

[9] J.L. Burguera, M. Burguera, Talanta 64 (2004) 1099-1108.

[10] D. Schiavo, L.C. Trevizan, E.R. Pereira-Filho, J.A. Nóbrega, Spectrochim. Acta Part

B 64 (2009) 544-548.

71

[11] R.Q. Aucélio, A. Doylea, B.S. Pizzornoa, M.L.B. Tristão, R.C. Campos, Microchem.

J. 78 (2004) 21-26.

[12] R.S. Amais, E.E. Garcia, M.R. Monteiro, A.R.A. Nogueira, J.A. Nóbrega,

Microchem. J. 96 (2010) 146-150.

[13] D.R. Lide (Ed.), CRC Handbook of Chemistry and Physics. 89th edition, Boca Raton,

CRC Press, 2008.

72

CHAPTER III

AN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION

SPECTROMETER AS AN EMPIRICAL FORMULA DETECTOR FOR GAS

CHROMATOGRAPHY

73

ABSTRACT

The present research focuses on empirical formula determination of organic

compounds using inductively coupled plasma atomic emission spectrometry (ICP-AES)

following separation by gas chromatography (GC). A mixture containing compounds of

interest was injected onto a packed GC column, and separated according to their boiling

point and interaction with the GC stationary phase. After exiting the GC, the effluent was

directed towards the base of the ICP torch and traveled to the plasma. The plasma reaches

temperatures of 6,000 K to 10,000 K, which will dissociate all of the constituent

molecules to their respective atoms. Once in their atomic state, the atoms will be excited

to higher energy states by the plasma and will emit light at a characteristic wavelength,

which can be detected by a charge injection device (CID) detector. Most of the organic

compounds of interest will consist of C, H, N, O, and S. The high energy and stable

environment of the plasma will allow for the determination of an empirical formula,

regardless of structure.

74

INTRODUCTION

Structure elucidation is an important step in the characterization of a new

compound. Natural products, or compounds derived from plants, account for more than

40% of the newly registered hits in the present drug discovery program.1 The

conventional way of studying natural products includes fractionation of a crude mixture

or extract, separation and isolation of the individual components using liquid

chromatography (LC), and structure elucidation using various spectroscopic methods.1

The analytical techniques in the arsenal of structure elucidation include ultraviolet/visible

(UV/Vis) spectroscopy, infrared (IR) spectroscopy, nuclear magnetic resonance (NMR),

combustion analysis, and inductively coupled plasma mass spectrometry (ICP-MS).

However, some shortcomings of the techniques mentioned above are worth noting, and

are briefly mentioned.

UV/Vis spectroscopy is generally used to qualitatively and quantitatively

investigate molecular structure because it causes electronic transitions at wavelengths

characteristic of the molecular structure of the molecule.2 However, it cannot provide an

unambiguous identification of an organic compound because only the presence of certain

functional groups that act as chromophores are detected.6

IR spectroscopy deals with the rotation and vibration of molecules. The mid-

infrared (2.5 to 14.9 µm) is the most widely used region for both qualitative and

quantitative analysis.6 Sample handling is the most difficult and time consuming part of

IR spectroscopy, and no good solvents exist that are transparent in this region.6

75

LC and NMR are routinely used in mixture analysis, so coupling them could

potentially save a lot of time.1 LC-NMR can be used in two analysis modes: continuous

and stopped-flow. In the continuous flow mode, the NMR can be thought of like a UV

detector for an LC, and the result is generally plotted as a two-dimensional time-

frequency plot consisting of two dimensional spectra (frequency domain) versus retention

time.1 For one type of stopped flow mode, the chromatographic run is stopped shortly

after the analyte passes the LC detector, and an NMR spectrum is obtained. After NMR

data acquisition, the chromatographic run is restarted and the procedure is repeated for

the next analyte.1 The delay time, td, is the time it takes the analyte to travel from the LC

detector to the NMR flow cell. The second type of stopped flow mode is called the loop-

storage mode, and it does not disrupt the chromatographic run. As the name implies, each

analyte peak is stored in an individual capillary loop for NMR analysis at a later stage.1

Two time delays for this mode must be determined, td, and the delay between the loop

storage device and the NMR flow cell, tFC. The continuous flow measurements suffer

from poor signal-to-noise ratios (S/N) for the NMR spectra and reduced chromatographic

resolution, especially if one reduces the flow rate to increase the S/N ratio of the NMR

spectra.1 The drawbacks to stopped flow techniques include disturbing the separation

quality, memory effects in the NMR flow cell, and the analytes must be stable (if using

the loop-storage mode).1

In combustion analysis, a compound is placed in a furnace and all of its carbon is

converted to CO2, hydrogen to H2O, nitrogen to N2, and sulfur to SO2.4 The amounts of

each compound produced from oxidative decomposition are usually found by

determining the mass increase on the system’s absorbers. The masses of each absorbed

76

compound are then used to determine an empirical formula. Combustion analysis is a

great way to provide confirmation of purity.3 Sample sizes for combustion analysis are in

the 1 mg range, and most times samples have to be sent away for analysis. A better

alternative would be to perform elemental analysis in house.

ICP-MS has dominated inorganic trace and ultratrace analysis due to its

unmatched sensitivity, elemental specificity, multi-element measurement capability, and

the possibility of the accurate determination of elemental isotope ratios.8 However, ICP-

MS cannot analyze elements in the atmosphere (mainly N, O, C, Ar) because it is an open

system.9 The most prohibitive feature of the ICP-MS is its cost, particularly for research

labs on a tight budget. The proposed instrumentation will be a more economic alternative

for elemental analysis than ICP-MS.

The past 40 years have seen a rise in the interest of speciation analysis. Speciation

analysis is the term given for the process of identification and quantification of the

different forms of an element in a sample.5 Typically, an analyte of interest is separated

from its matrix by a separation technique, namely liquid chromatography (LC) or gas

chromatography (GC). A detection system then aids in sample identification and

quantitation. However, a number of detection systems can be used, and selecting the

appropriate one depends mainly on the chemical properties of the analyte.

A universal detector sensitive to all elements would simplify the process. The ICP

atomizes samples more completely and in a chemically inert environment, has small or

nonexistent ionization interference effects, has a relatively uniform temperature cross

section, and is capable of providing simultaneous determinations for up to 70 elements.6,7

77

The optics of the instrument allow for high efficiency at many wavelengths and high

resolution over a broad spectral window.7 These characteristics make the ICP-AES a

great candidate as a universal detector for GC. The instrumental setup is depicted in

Figure 1.

GC-ICP Interface. An important component of the instrumental setup is the

interface from the GC to the ICP. The interface should keep the analytes in gaseous form

during transport from the GC column to the ICP.8 This is generally accomplished by

thorough heating of the interface to prevent condensation of the analyte in the interface.

Direct interfacing and mixing the GC effluent in the spray chamber with aqueous aerosol

are the two most common interface types.

The simplest type of direct interface is a connection of the GC effluent to the base

of the plasma torch via a short 0.5 mm stainless steel tube, which was kept at 250°C in

order to avoid sample loss.10 However, carbon deposition was observed on the torch, and

a small amount of oxygen was bled into the carrier gas flow at the mid-point of the

transfer line to stop the carbon buildup.10

Mixing the GC effluent in the spray chamber offers a little more flexibility. For

the analysis of arsine, mono-, di, and trimethyl arsine in the gaseous emissions of soil

samples, the end of a GC-capillary was introduced into the sample inlet tube of a

conventional Meinhard nebulizer, which was connected to the end of the torch by a

polytetrafluoroethylene (PTFE) tube.11 If condensation of the separated species occurred,

use of the Meinhard nebulizer meant any generated aerosols were transferred to the

plasma without being adsorbed on the tube’s surface, negating additional heating of the

78

Figure 1. Schematic of the ICP-AES Empirical Formula Detector.

79

tube.11 For a summary of additional interfaces reported in the literature see the review by

Bouyssiere et al.8

ICP-MS as a Detector for GC. Many of the most commonly studied trace

elements of toxicological interest- arsenic, tin, lead, and chromium- make their way into

the environment via industrial processes.12 ICP-MS has proven its value for speciation

analysis of organometallics in environmental samples.8 Application areas of speciation

using GC-ICP-MS include the analysis of air, natural waters, dust and soil/sediments,

biological tissues, and energy related samples. One example of each has been given

below.

Analysis of air and atmospheric samples. Gases of municipal waste deposits were

sampled and analyzed using GC-ICP-MS and were found to have volatile Mo and W

compounds in addition to the known hydrides and methylated compounds of As, Se, Sn,

Sb, Te, Hg, Pb and Bi.13 The volatile Mo compounds’ concentration was 0.2-0.3 µg of

Mo/m3 and the volatile W compounds’ concentration was 0.005-0.01 µg W/m3. Landfill

gas samples were cryotrapped and then thermally desorped for sample preconcentration.

Retention time matching of the samples to those of the standards showed that Mo(CO)6

and W(CO)6 samples were present in landfill gas.

Natural Waters. Natural water samples include rain, snow, seawater, and

geothermal samples. Water samples taken from the Rhine estuary were analyzed by

cyrogenic GC-ICP-MS.14 Detection limits of 0.5-10 pg for selected alkyl-metal(loid)

species of As, Ge, Hg, and Sn in 0.5 L water samples were reported.

80

Dust, Soil, and Sediments. Separation and detection of butylated trimethyllead

(TML), dimethyllead (DML), triethyllead (TEL) and diethyllead (DEL) in airborne

particulate matter was performed and compared to the determination of TML in CRM

605.15 Method detection limits, as Pb, were 3.2 fg for TML, 2.4 fg for DML, 1.8 fg for

TEL and 9 fg for DEL for a 1 mL sample injection.

Biological Samples. A method for purge and trap multicapillary GC-ICP-MS for

the analysis of methylmercury in fish samples was developed and validated.16 The

experimentally determined detection limit of 0.2 ng/g was reported.16

Energy Related Samples. The ICP-MS has been successfully used as a GC

detector of organolead in fuel, metalloporphyrin in shale, and organomercury and

organoarsenic in gas condensates.8

EXPERIMENTAL

Characterization of the GC. All GC work was performed on a Gow-Mac Series

350 isothermal gas chromatograph. Familiarization experiments were performed in order

to determine temperature settings for the oven and injection port. The results were plotted

in Excel and a regression equation related the dial settings to temperature, so the

appropriate temperatures for the oven and injection port were obtained (Figures 2 and 3).

Packed GC columns were used for all separations. The resolution is far from ideal and

peaks are broad on packed columns, but higher flow rates and larger sample sizes can be

used.5, 17

ICP Wavelength Selection. Two wavelength regions were used, ultraviolet (UV)

and the visible (Vis). The regions have strengths and

81

Figure 2. Relationship between dial setting and oven temperature for the Gow-Mac 350.

0

100

200

300

400

500

600

0 10 20 30 40 50 60 70 80

Ove

n Te

mpe

ratu

re (

°C)

Dial Setting

82

Figure 3. Graph showing the relationship between the dial setting and injection port

temperature for the Gow-Mac 350.

0

100

200

300

400

500

600

0 10 20 30 40 50 60 70 80 90 100

Inje

ctio

n Po

rt T

emer

atur

e (°

C)

Dial Setting

83

weaknesses, so both were investigated. For example, many elements have emission lines

in the UV. Table 1 includes the wavelengths that were used. In addition, some figures of

merit including the limit of detection (LOD), linearity, linear dynamic range (LDR),

precision, signal-to-noise ratio (S/N), and sensitivity were calculated for a mixture

containing hexane and ethanol. Linearity is defined as how well observed data fit a

straight line. Sensitivity is defined as the response of an instrument or method to a given

amount of analyte.

Example Separation. A solution containing a mixture of the hydrocarbons hexane,

benzene, and toluene was made. A 2 µL aliquot of the mixture was injected onto a 20%

Carbowax on Chromsorb-P packed GC column (1.2 m x 0.64 cm). The column

temperature was set at 90°C and the injection port temperature was 110°C. The GC-ICP

interface was made up of 1/8 inch outer diameter copper tubing. The interface was

partially heated by the heater on injection port B on the GC. The GC effluent was then

directed to the inlet part of a polytetrafluoroethylene (PTFE) micro-nebulizer. The micro-

nebulizer was then fed into a custom glass piece that attaches to the torch. This setup

allows for 100% sample transport efficiency. A sample chromatogram for carbon

emission at 247.856 nm and hydrogen emission at 656.258 nm is seen in Figure 4. The

retention time of hexane was 28 s, benzene was 106 s, and toluene was 195 s.

84

Table 1. Wavelengths used in the UV and Vis.

Element Emission

λ (nm)

LOD

(mg L-1)

Linearity LDRb Precisiona S/N Sensitivity Window

C 247.9 < 1000 1.1 2.8 > 2-3% 3626c

20.9 UV

H 656.3 < 194 0.96 2.8 > 2-3% 1177d 20.7 Vis

a Manual injection repeatability from reference 6.

b Linear dynamic range in decades.

c Signal-to-noise ratio for a 106 mg L-1 C solution.

d Signal-to-noise ratio for a 2.7 x 104 mg L-1 H solution.

85

Figure 4. Carbon chromatogram at 247.856 nm (top) and hydrogen chromatogram at

656.285 nm (bottom).

0

100000

200000

300000

400000

500000

600000

700000

0 50 100 150 200 250 300

Carb

on E

mis

sion

Inte

nsit

y (a

rbit

rary

un

its)

Time (s)

14000

34000

54000

74000

94000

114000

134000

154000

0 50 100 150 200 250 300

Hyd

roge

n Em

issi

on In

tens

ity

(arb

itra

ry

unit

s)

Time (s)

86

Determination of the Empirical Formula. The emission response for the ith

element can be described by the following equation:

Si = Ki x mi (1)

where S is the emission signal, K is the ICP response constant, and m is the mass present

at a given retention time. A standard similar in structure to the compounds of interest is

usually run beforehand to determine the ICP response constant, K. Once the

chromatograms for each element were obtained, the area under the curve (AUC) of each

peak was approximated by a Riemann sum. The mass of each element present was then

summed to obtain the total mass at a given retention time. From the total mass and the

mass of each element present, a mass percent can be calculated. The quantity of matter of

each compound is then found by dividing the mass percent by the atomic weight. The

element that has the least number of moles is used as a normalization factor in order to

obtain the empirical formula. Table 2 shows the results of the GC-ICP analysis of the

hydrocarbon mixture. The percent error in the found empirical formula is around 1-15%,

depending on the compound.

87

Table 2. Empirical formula comparison to the molecular formula.

Compound Empirical Formula Molecular

Formula

Retention Time

(s)

Founda Theoretical

Hexane C3H6.93 C3H7 C6H14 28

Benzene CH1.15 CH C6H6

106

Toluene C7H9.03 C7H8

C7H8 195

a The presented results are from one experimental run. The experiment was run multiple

times, and similar results were obtained each time.

88

CONCLUSIONS

An alternative method for the determination of an empirical formula of a simple

hydrocarbon has been demonstrated. The total mass of the compound was found by

monitoring the carbon emission at 247.856 nm, and the hydrogen emission at 656.285 nm.

The total mass of the carbon and hydrogen present was determined from the area under

the curve of the carbon and hydrogen peaks from the chromatogram. The empirical

formulas obtained for hexane, benzene, and toluene were: C3H6.93, CH1.15, and C7H9.03,

respectively. The percent error associated with the results was between 1% and 15%,

depending on the compound. For an unknown organic compound, this method could

provide an empirical formula which takes into account only the hydrocarbons present.

Once an empirical formula was obtained, a GC-MS separation can then be run in order to

obtain the molecular weight of the compound. Armed with the empirical formula and a

molecular weight, the molecular formula for the unknown organic compound can be

deduced.

89

REFERENCES

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Albert, K. LC-NMR Coupling Technology: Recent Advancements and

Applications in Natural Product Analysis. Magnetic Resonance in Chemistry.

2005, 43, 681-687.

2. Ingle, J.D.; Crouch, S.R. Spectrochemical Analysis, 1st ed.; Prentice Hall: Upper

Saddle River, 1988.

3. Molyneux, R.J.; Schieberle, P. Compound Identification: A Journal of

Agricultural and Food Chemistry Perspective. Journal of Agricultural and Food

Chemistry. 2007, 55, 4625-4629.

4. Fadeeva, V.P.; Tikhova, V.D.; Nikulicheva, O.N. Elemental Analysis of Organic

Compounds with the Use of Automated CHNS Analyzers. Journal of Analytical

Chemistry. 2008, 63, 1094-1106.

5. Lobinski, R.; Adams, F.C. Speciation Analysis by Gas Chromatography with

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92

CHAPTER IV

DETERMINATION OF THE TOTAL CARBON IN SOFT DRINKS BY

TUNGSTEN COIL ELECTROTHERMAL VAPORIZATION INDUCTIVELY

COUPLED PLASMA SPECTROMETRY

Carl G. Young and Bradley T. Jones

The following manuscript was published in Microchemical Journal, 2011, 98, 323-327

(doi: 10.1016/j.microc.2011.03.001), and is reprinted with permission. Stylistic variations

are due to the requirements of the journal. All of the presented research was conducted by

Carl G. Young. The manuscript was prepared by Carl G. Young, and edited by Bradley T.

Jones.

93

ABSTRACT

A method is developed for the direct determination of carbon in soft drinks by

electrothermal vaporization inductively coupled plasma atomic emission spectrometry. A

tungsten coil is used as the electrothermal vaporizer, and is extracted from a

commercially produced 150 W, 15 V microscope bulb. The standard additions method is

employed to correct any matrix effects from the samples. Carbon emission is monitored

at 193.091 nm. Carbon content determined for the samples was in the range of 13 to 60 g

in one 8 fl oz serving, and these values agreed with the label values in the range 93 to 137%

(except for one sample, Orange Fanta, which provided a 200% recovery. This was likely

due to non-carbohydrate carbon containing species in that sample). The precision of the

technique was always better than 20% relative standard deviation (n=10). The detection

limits for carbon range from 0.4 to 3 mg L-1, and absolute detection limits range from 12

ng to 90 ng for a 30 µL aliquot of sample on the coil. This method could be an alternative

approach for determining the carbon content of nonvolatile compounds, and complement

HPLC-ICP-AES determination of those same species.

Keywords: Carbon emission, soft drinks, electrothermal vaporization, inductively

coupled plasma, tungsten coil

94

1. INTRODUCTION

The consumption of soft drinks in the United States is popular, as demonstrated

by their total revenue of approximately $70.1 billion per year [1]. The main

components of soft drinks are water, carbon dioxide, sweeteners, flavors, colors, and

caffeine [2]. The global consumption of sugar has increased from 193 calories per

person per day in 1961-1963, to 243 calories per person per day in 2001-2003 [3]. In

the United States, high fructose corn syrup is often used as a sweetener and has been

linked to excessive body weight, and other chronic conditions [3]. The soft drink

industry is under regulation by the United States government, so accurate and reliable

analytical methodologies are needed to verify the constituents and composition of

these drinks. High performance liquid chromatography (HPLC) and infrared

spectroscopy (IR) have been previously used to determine the carbohydrate content of

soft drinks [4, 5]. When IR spectroscopy is used, the spectra of the individual

components are very similar, resulting in band overlap, so sophisticated spectral

correlation approaches may be needed [5]. Inductively coupled plasma atomic

emission spectrometry (ICP-AES) has been used for the determination of the residual

carbon content (RCC), and the carbon sources used were urea, L-cysteine, and

glucose [6]. However, for the direct determination of the RCC by ICP-AES, no soft

drink samples were analyzed. A method of analysis which can unequivocally identify

and quantify the carbohydrates present in soft drinks is highly desirable.

The high separation efficiency and resolving power of capillary electrophoresis

provides an alternate method of analysis. A rapid capillary electrophoresis method

employing micellar electrokinetic chromatography has been used to determine artificial

95

sweeteners, preservatives, and colors used as additives in carbonated soft drinks [7]. The

limit of quantification when retail soft drink samples were analyzed was 0.01 mg mL-1.

However, this method needs further validation performed if it is to be used for routine

analysis [7]. In the last decade, Peters et al. [8] demonstrated the utility of a high

performance liquid chromatography system coupled to an inductively coupled plasma

atomic emission spectrometer for the determination of sugars in a variety of juice

samples. Carbon emission was monitored at 193.091 nm and an absolute carbon detection

limit of 0.05 µg was obtained. The same system has also been used for the separation of

amino acid enantiomers [9]. Here, an absolute carbon detection limit of 2.5 ng was

obtained. More recently, the hyphenated HPLC-ICP technique has been used for the

simultaneous determination of carbohydrates, carboxylic acids, alcohols, and heavy

metals in juices and wines [10, 11]. The major advantages of the carbon emission

detector are its sensitive, universal detection for any carbon-containing compound, the

possibility for obtaining a complete calibration curve with five or more points from a

single injection, and a single calibration curve for the analysis of multiple analytes [9, 10,

12]. The carbon emission detector is not without its drawbacks. The system is susceptible

to background carbon emission. The causes for this background carbon emission have

been attributed to carbon contamination in the plasma, organic solvents in the mobile

phase, and carbon dioxide from the atmosphere [9].

Use of tungsten atomizers for electrothermal atomization atomic absorption

spectrometry and electrothermal atomization atomic fluorescence spectrometry was first

described in the early 1970’s [13]. Since that time, their use has effused into other areas

of analytical atomic spectrometry like electrothermal atomization laser excited atomic

96

fluorescence spectrometry (ETA-LEAFS), inductively coupled plasma atomic emission

spectrometry (ICP-AES), and inductively coupled plasma mass spectrometry (ICP-MS),

just to name a few [13]. Numerous publications can be found in the literature for the

determination of metals, metalloids, and some nonmetals by tungsten coil atomic

absorption spectrometry (WCAAS) [14-16]. A more recent use of the tungsten coil has

been as an atomic emission spectrometer [17]. Donati et al. [18] have used tungsten coil

atomic emission spectrometry (WCAES) to simultaneously determine the lanthanides,

and obtained detection limits in the range of 0.8 (for Yb) to 600 µg L-1 (for Pr). WCAES

has also been used for the detection of nonmetals. Donati et al. [19] developed a

procedure for the indirect determination of iodide which makes use of the reaction

between iodide and indium to form InI.

ICP-AES has a number of sample introduction methods and they include pneumatic

nebulization, hydride generation, electrothermal vaporization (ETV), direct sample

insertion, and laser abalation [20]. ETV-ICP has employed a wide variety of atomizers

including carbon rods, carbon cups, graphite boats, tungsten boats, tungsten coils, and

other metal filaments [13]. The use of the ETV as a source for sample introduction for

ICP-AES significantly increases sample transport efficiency when compared to

conventional pneumatic nebulization [20]. ETV has been used successfully as a sample

introduction source for ICP-AES for multi-element determinations and the determination

of cadmium in urine [21, 22].

In this work, the tungsten coil is used as an ETV for the analysis of soft drinks by

ICP-AES. The total carbon content is determined at carbon’s emission wavelength of

193.091 nm. The standard addition method for calibration is used to minimize any

97

matrix effects from the samples. This is the first report of carbon determination by

tungsten coil ETV ICP-AES.

98

2. EXPERIMENTAL

2.1. Instrumentation

Figure 1 shows a diagram of the instrumental arrangement. The tungsten filament is

used as the vaporizer. The coil is extracted from a 150 W, 15 V commercially available

halogen display lamp (Osram Xenophot HLX 64633, Pullach, Germany) by removing the

fused silica casing. The bulb base is left intact, and is mounted in a standard two-pronged

ceramic power socket. An aluminum atomization cell (fabricated in house) is used to

house the extracted filament. The aluminum atomization cell is about 7.6 cm long, and

has three openings. The first opening is parallel to the plasma, and houses the ceramic

power socket that holds the tungsten coil. A second opening is on the top of the housing

and is made up of a ¼ inch Swagelok fitting used as the introduction for purge gas. The

third and final port is used for connecting the tungsten coil cell and the ICP. The

connection is realized via a metal-to-glass fitting (part # SS-4-UT-6, Swagelok,

Plainsville, OH, USA). A 10% H2-Ar purge gas mixture is used to prevent coil oxidation

and cool the atomizer. A programmable, solid state DC power supply (BatMod, Vicor,

Andover, MA, USA) provides constant current for resistively heating the coil during

heating cycles. The ICP-AES used for this work is a Prodigy-D (Teledyne Leeman Labs,

Hudson, NH, USA) equipped with a transient response analysis package. The ICP

operating parameters can be seen in Table 1. A hand refractometer (Vista A336ATC, AO

Scientific Instruments, Buffalo, NY, United States) is used to take specific gravity

measurements of all the sample solutions, which were later converted to refractive index.

99

Figure 1. Schematic diagram of the W-coil ICP-AES system.

100

Table 1

ICP-AES instrument parameters used.

Parameter Value Generator Frequency (MHz) 41

Torch Inner diameter (mm)

2.5

Sample Introduction System

RF Applied Power (kW)

1.2

Coolant flow rate (L min-1)

18

Auxiliary gas flow rate (L min-1)

0

Nebulizer pressure (psi)

0

Time Resolved Analysis

View

Axial

Elapsed time (s)

15

Time slice (s)

0.1

Dynamic memory

off

101

2.2. Sample preparation

All reagents were of analytical grade unless otherwise specified. A 1000 mg L-1

carbon stock solution containing sucrose (Fisher, Fair Lawn, NJ, USA) was prepared by

dissolving the solid in distilled, deionized water from a Milli-Q system (Millipore,

Billerica, MA, USA) with a resistivity of 18.2 MΩ·cm. Six different soft drinks were

obtained for this work: Welch’s Calcium 100% Grape Juice in a 64 oz plastic jug, Ocean

Spray Cranberry Juice Cocktail in a 64 oz plastic jug, Gatorade G2 Fruit Punch in a 32 oz

plastic bottle, Fanta Orange in a 20 oz plastic bottle, Dr. Pepper in a 20 oz plastic bottle,

and Pepsi in a 20 oz plastic bottle. The standard addition method was employed for the

soft drink samples in order to reduce matrix effects. Each sample (0.1 mL) was diluted

1:1000 with distilled, deionized water. Multiple aliquots of each sample were prepared,

resulting in 5 standard addition points having added C concentrations in the range of 0 to

100 mg L-1. All reference solutions were brought to a final volume of 100 mL using

distilled, deionized water. The carbon intensity was plotted against the added volume of

the 1000 mg L-1 C solution, and the x-intercept provided the theoretical volume of 1000

mg L-1 C needed to reproduce the original sample.

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Table 2

Tungsten coil heating cycle.

Step Applied Current (A) Time (s) 1 2.5 45 2 2.0 35 3 1.7 15 4 1.5 15 5 0 15 6 8 10 7 0 60

103

2.3. Heating cycle

A sample aliquot of 30 µL was placed on the tungsten coil using a micropipette

(Finnpipette 5-50 µL, Thermo Fisher, Waltham, MA, USA). The purge gas flow rate was

0.7 L min-1, and the heating cycle in Table 2 was applied. The coil was dry at the end of

step 2, as evidenced by an increase in the voltage necessary to maintain a constant current

during the last seconds of this stage. The ashing procedure occurred in steps 3 and 4,

where lower currents were employed. In these steps analyte loss was minimized by using

sequentially less current, and this kept the coil from glowing red. A brief cooling period

was used in step 5, and this helped to provide a reproducible atomization step. The

reasonably high current (8 A) used during the vaporization step generated an atomic

cloud which was swept into the plasma by the 10% H2-Ar purge gas. The detector was

triggered at the beginning of step 6, and the carbon emission at 193.091 nm was

continuously monitored using the transient response analysis package of the ICP control

software.

New tungsten coils used for this work had been subjected to a conditioning program

in order to improve the analytical signal. Conditioning the coil prior to performing

analyses modifies the surface of the tungsten [18]. The coil conditioning program has

been described elsewhere [18], and is reproduced in Table 3.

104

Table 3

Tungsten coil aging program.

New coil conditioninga New coil cleaningb Step Applied Current

(A) Time (s) Applied Current

(A) Time (s)

1 3 10 3.5 250 2 5 5 4.5 250 3 0 10 5.5 300 4 5 5 7 150 5 0 20 10 35 6 0 40

a Conditioning occurred in open air.

b New coil cleaning occurred with a purge gas flow rate of 1.4 L min-1.

105

3. RESULTS AND DISCUSSION

3.1. Coil surface and analytical signal

When a new, untreated coil was used, the observed carbon atomic emission signal for

a sample solution started off low, and slowly increased with each successive firing.

Eventually, the signal would reach a stable plateau, and a working analytical curve could

be produced from the emission intensities. For this work, the analytical signal produced

from a conditioned coil was about 10 times higher than the analytical signal from a fresh

coil. Previous workers reported that the analytical signal produced from a fresh coil is

usually 50% lower than the signal produced from a conditioned coil [18]. The surface of

a new coil is smooth, while the surface of an aged coil contains pits, and perhaps this

allows the analyte to adhere more strongly [14]. Donati et al. [18] suggests that tungstate

crystals formed from the volatilization and deposition of tungsten during the heating

cycle increase the coil’s surface area, and allow for better adhesion of analyte atoms

during the heating cycle. Conditioning of new coils is therefore strongly recommended.

For this work, the average coil lifetime was 40 firings. Typically, a tungsten coil

has a lifetime of 150-500 firings [13, 18]. However, tungsten coils exhibit shorter

lifetimes when carbon containing compounds are present [17, 23, 24]. Tungsten carbides

could be formed, and the lower melting point of those carbides reduces the lifetime [13].

3.2. Sample Analysis

The six drink samples were analyzed with the same carbon (C) standard solution. The

C emission signal was monitored at 193.091 nm. The peak height of C was measured and

plotted against the volume of C standard solution to the sample. Figure 2 shows three of

106

Figure 2. Standard addition plots for the determination of carbon in Pepsi (♦), Gatorade G2 (▲), and Fanta Orange (●).

107

these standard addition plots on the same graph. Notice that the three slopes have similar

magnitude, but different values. The slope is clearly dependent on the sample matrix, so

the standard additions method was necessary. The other samples were analyzed in a

similar manner. The results are summarized in Table 4. The method produces accurate

results, with % recovery near 100% in many cases. Some recoveries are excessively high.

This could be due to the other carbon-containing compounds present in the samples (such

as dyes or caffeine). The label value for the soft drinks represents only C in the form of

carbohydrates. With the tungsten coil ETV-ICP method, all carbon containing species

are detected simultaneously.

As a comparison, the total amount of C in each original sample was determined

by the refractive index method. The refractive index was measured with a simple

refractometer, and this value was converted to % sugar using standard tables for the

conversion [25]. The refractive index results are similar to, but higher than, those found

by the standard additions method.

108

Table 4.

Summary of carbon determination results.

Sample Amount of carbohydrate from labela

(g)

Amount of carbohydrate from

experiment (g)

% Recovery Amount of carbohydrate from Refractive Index

(g) Pepsi 28 32 114 40

Dr. Pepper 27 31 115 40

Orange Fanta 30 60 200 > 41

Gatorade Perform G02

14 13 93.0 23

Grape juice 42 46 110 > 41 Cranberry juice 30 41 137 > 40

aThe amount of carbohydrate in one 8 fl oz serving size (240 mL)

Table 5.

Analytical figures of merit for the method.

Sample Limit of detection (mg L-1)

Absolute Limit of detection

(ng)

Slopea LDRb Precisionc S/Nd

Pepsi 0.4 12 5.9 2.4 7.4 774 Dr. Pepper 0.6 18 4.2 2.2 5.3 617

Fanta 3 90 4.1 1.5 7.2 807 Gatorade 2 60 7.2 1.7 6.8 800

Grape Juice 1 30 5.0 2.0 16 884 Cranberry

Juice 3 90 4.4 1.5 2.5 816

aUnits: relative emission intensity/mL C standard added

b Linear dynamic range in decades.

c Percent relative standard deviation for 10 replicates of a sample with a 50 mg L-1 C spike.

d Signal-to-noise ratio for a sample solution with a 50 mg L-1 C spike.

109

3.3. Analytical figures of merit

Analytical figures of merit were determined for the drink sample solutions (Table 5).

Limits of detection (LOD) were calculated as 3 times the standard error in the x variable

from the regression equation statistics calculated from Microsoft Excel, divided by the

slope of the calibration curve. Since the x variable was in volume units, this was

converted to concentration units prior to obtaining the LOD. The average carbon LOD

obtained from all six standard addition curves was 2 mg L-1. Absolute detection limits

range from 12 ng C to 90 ng C. The LOD’s for the six samples are dissimilar because of

the differing sample matrices, resulting in differing slopes and varying degrees of linear

fit for the standard addition plots (Table 5). The average detection limit of 2 mg L-1 is

comparable to detection limits of 1.5 mg L-1 carbon for the separation and detection of

nine amino acids by HPLC-ICP-AES [12]. Other detection techniques employing liquid

chromatography have been used for the determination of underivatized amino acids [26].

The reported detection limits are the following: evaporative light scanning (1-10 mg L-1),

ultraviolet absorbance at 210 nm (0.9-4.5 mg L-1), non-suppressed conductivity detection

(1-25 mg L-1), refractive index detection (50 mg L-1), stopped flow NMR (100-500 mg L-

1), chemiluminescent nitrogen detection (0.3-0.7 mg L-1), mass spectrometry (0.2-5 mg L-

1), and tandem mass spectrometry (0.08-0.8 mg L-1). These detection limits were for the

entire amino acid, and if one assumes that amino acids have 40% to 50% carbon content,

the detection limits mentioned above range from 0.03-200 mg L-1 carbon. In addition,

detection limits of 33 mg L-1 C and 34 mg L-1 C were reported for the residual carbon

content determination by ICP-AES in the radial and axial configurations, respectively [6].

The 2 mg L-1 detection limit for the carbon ETV-ICP-AES setup is near the lower end of

110

the previously mentioned range for the LC detectors, and about one order of magnitude

lower than the LOD’s obtained by ICP-AES.

The precision of the method was calculated and reported by the percent relative

standard deviation (RSD, n =10) for carbon. The midpoint of the calibration curve was

chosen (50 ppm C). The precision was always below 20%, and often below 10%. Signal

to noise ratios (S/N) were calculated as the net intensity of each 50 mg L-1 C peak,

divided by the standard deviation of the raw intensity counts. The S/N for each sample

was in the 600 to 900 range. The linear dynamic range for carbon was typically around

1.5 decades, and over two decades for Pepsi and Dr. Pepper.

The recoveries obtained for carbon were in an acceptable range, and it is clear that

carbon can be determined with acceptable accuracy and precision using the standard

addition method. The results using the simple calibration curve method were worse. One

cause of this could be the interference effects of concomitants on the analytical signal as

seen with tungsten coil atomic absorption spectrometry (as described in the literature)

[27]. Some reported interference effects observed are the formation of mixed oxides

between the analyte and concomitants, analyte occlusion in oxide/salt matrices, non-

dissociation of refractory compounds, and alkaline elements present as concomitants that

decrease the availability of hydrogen during the pyrolysis and atomization steps [27, 28].

111

4. CONCLUSIONS

The direct determination of carbon in soft drinks is accomplished by ETV- ICP-AES

using the standard additions method. The average experimental detection limit of 2 mg

L-1 is comparable to the detection limits obtained for the liquid chromatography detectors

and previously reported ICP-AES methods. The amount of carbon determined in the

samples was between 13 and 60 g in an 8 fl oz serving size. This method could be an

alternative approach for determining the carbon content of nonvolatile compounds, and

complement an HPLC-ICP-AES analysis of those same species. Minimal hardware

modification of a commercial ICP-AES is needed to interface the tungsten coil housing to

the ICP.

ACKNOWLEDGEMENTS

The authors would like to thank Wake Forest University for funding. CGY would

like to extend extreme gratitude to Dr. Joaquim A. Nóbrega and Dr. George L. Donati for

helpful discussions about the tungsten coil. CGY would also like to thank Dr. Ronald

Dimock for use of his refractometer.

112

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Valcarcel, On-line separation and preconcentration of cadmium, lead and nickel in a

fullerene (C60) minicolumn coupled to flow injection tungsten coil atomic absorption

spectrometry, Analytica Chimica Acta, 368 (1998) 255-263.

[25] R.C. Weast, CRC Handbook of Chemistry and Physics, in: CRC Handbook of

Chemistry and Physics, CRC Press, Boca Raton, Florida, 1979.

[26] K. Petritis, C. Elkafir, M. Dreux, A comparative study of commercial liquid

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animal feces by tungsten coil electrothermal atomic absorption spectrometry, Talanta, 47

(1998) 613-623.

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CHAPTER V

CONCLUSIONS

Inductively coupled plasma atomic emission spectrometry is a powerful tool for

the determination of nonmetals. A simple method for the direct determination of sulfur in

biodiesel has been realized. Using microemulsion for sample preparation allowed for an

alternative and simple approach for sample preparation. Using the summation of the

intensities of multiple emission lines allowed for increased accuracy and sensitivity. A

noise threshold of about 30 signal units resulted in significant improvement in the signal

to noise ratio of the CCD detector. Extensive sample pretreatment and the use of toxic

organic solvents are eliminated with this analysis method. This method could potentially

be applied to determine the halogens (F, Cl, Br, and I) and phosphorus in nontrivial

sample matrices.

The ICP-AES could potentially provide a more economic alternative to elemental

analysis than other approaches like combustion analysis and ICP-MS. The empirical

formulas of simple hydrocarbons were successfully demonstrated. Moreover, the

interfacing of the GC to the ICP-AES required little hardware modification, and most

materials could potentially be found in-house. Separations of more complex

hydrocarbons using a capillary GC column could potentially provide better quality

separation and increase the accuracy of the empirical formula determinations.

The third project employed electrothermal vaporization for sample introduction to

the ICP-AES to determine the carbon content of soft drinks. The standard additions

method allowed for the accurate determination of carbon in the soft drinks, regardless of

117

the sample matrix present. Detection limits for carbon were near the lower end of the

detection limit range for LC detectors, and about one order of magnitude lower than the

LOD’s obtained by the direct determination of carbon by ICP-AES. The results suggest

that this could be an alternative approach for determining the carbon content of

nonvolatile compounds, and complement an HPLC-ICP-AES analysis of those same

species.

This research has shown that ICP-AES could be used for the successful

determination of sulfur, carbon, and hydrogen in different sample types using the vacuum

ultraviolet for monitoring atomic emission from the plasma. Although increased

instrumental complexity and higher operating costs are critical points to consider when

deciding to use ICP-AES in the VUV, the increased analytical capacity of the ICP-AES

makes it a more attractive alternative. Many elements on the periodic table have emission

lines in the VUV, so other elements could potentially be determined with similar

accuracy.

118

SCHOLASTIC VITA

CARL GILBERT YOUNG

BORN: November 16, 1982, Raleigh, North Carolina

UNDERGRADUATE STUDY: East Carolina University

Greenville, North Carolina

B.S. Chemistry, 2005

GRADUATE STUDY: Wake Forest University

Winston-Salem, North Carolina

Ph.D., 2011

SCHOLASTIC AND PROFESSIONAL EXPERIENCE:

Graduate Teaching Assistant, Wake Forest University, 2007-2011

Preclinical Research Intern, Targacept, 2009

Graduate Research Assistant, Wake Forest University, 2008-2009

QC Contractor, Scynexis, 2006-2007

PROFESSIONAL SOCIETIES:

Society of Applied Spectroscopy, 2008-Present

American Chemical Society, 2004-Present

HONORS AND AWARDS:

Richter Memorial Scholarship, 2010

Alumni Student Travel Award, 2010

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PUBLICATIONS:

Peng Wu, Xi Wu, Xiandeng Hou, Carl G. Young, Bradley T. Jones. Inductively Coupled Plasma Optical Emission Spectrometry in the Vacuum Ultraviolet Region. Applied Spectroscopy Reviews. 2009, 44, 507-533. doi 10.1080/05704920903069398

Jiyan Gu, George L. Donati, Carl G. Young, Bradley T. Jones. Continuum Source Tungsten Coil Atomic Fluorescence Spectrometry. Applied Spectroscopy. 2011, 65, 382-385. doi 10.1366/10-06158

Carl G. Young, Renata S. Amais, Daniela Schiavo, Edivaldo E. Garcia, Joaquim A. Nobrega, Bradley T. Jones. Determination of Sulfur in Biodiesel Microemulsions Using the Summation of the Intensities of Multiple Emission Lines. Talanta. 2011, 84, 995-999. doi:10.1016/j.talanta.2011.01.008

Carl G. Young, and Bradley T. Jones. Determination of the Total Carbon in Soft Drinks by Tungsten Coil Electrothermal Vaporization Inductively Coupled Plasma Spectrometry. Microchemical Journal. 2011, 98, 323-327. doi:10.1016/j.microc.2011.03.001

POSTER PRESENTATIONS:

“An Inductively Coupled Plasma Atomic Emission Spectrometer for Indirect Detection in High Performance Liquid Chromatography,” WFU Graduate Student Research Day, April 6th, 2009

“Use of an Inductively Coupled Plasma Atomic Emission Spectrometer as an Empirical Formula Detector for Gas Chromatography,” WFU Graduate Student Research Day, March 23rd, 2010

“Use of an Inductively Coupled Plasma Atomic Emission Spectrometer as an Empirical Formula Detector for Gas Chromatography,” 10th Annual Poster/Vendor Night at Syngenta, April 13th, 2010

“Use of an Inductively Coupled Plasma Atomic Emission Spectrometer as an Empirical Formula Detector for Gas Chromatography,” 37th Annual FACSS Conference, October 17th and 18th, 2010

“Use of an Inductively Coupled Plasma Atomic Emission Spectrometer as an Empirical Formula Detector for Gas Chromatography,” Pittsburgh Conference, March 14th, 2011.