Atmospheric Microplasma Jet: Spectroscopic Database Development and
Analytical Results
Randall L. Vander Wal1,*, Jane H. Fujiyama-Novak1, Chethan Kumar Gaddam1, Debanjan
Das1, Aditya Hariharan1, Benjamin Ward2
1
Dept. of Energy and Mineral Engineering & The EMS Energy Institute, The Pennsylvania
State University, State College, PA 16802, USA.
2
Makel Engineering, Inc., Cleveland, OH 44128, USA.
*Randall L. Vander Wal
Dept. of Energy and Mineral Engineering & The EMS Energy Institute, The Pennsylvania
State University, University Park, PA 16802, USA.
Phone: (814) 865–5813
Fax: (814) 865-3248
Email: ruv12@psu.edu
Abstract: This paper presents a developed dielectric barrier discharge-based “sniffer” that
offers unique characteristic not available from other techniques. It is portable, highly
specific and sensitive detector that operates at atmospheric pressure. It provides both
molecular and elemental information of organic and inorganic gases and particulate
aerosols. Measurements were made to electrically characterize the plasma and calculate the
energy coupled into the plasma. We created a signature database for diverse chemicals based
on the atomic and diatomic emission spectrum that serves to classify the compound and
ideally recognize it by composition with the optical emission intensity corresponding to
concentration. Limits of detection extend to ppb levels for some species such as decane, 2decanol and nitrobenzene. Results are presented for differentiation of classes of organic
compounds such as alkanes, aromatics, oxygenates, chlorinated and nitrogen-contained
organic compounds.
Keywords: Plasma, dielectric barrier discharge, optical emission spectrometry, spectral
database
1. Introduction
In plasma emission spectroscopy,
one of the basic underlying processes is the
excitation of the particles (atoms,
molecules, ions) by electron impact to
higher electronic level and followed by their
decay into the ground electronic state
resulting in the observed line and band
emissions[i]. The electrons in an otherwise
non-thermal plasma also dissociate the
species of interest. The atomic emission
spectrum serves to classify the compound(s)
and ideally its molecular identify with
concentration provided by its spectral
intensity.
In this work we constructed a novel
dielectric barrier discharge configuration
with which to implement OES in a
miniature flowing plasma tube for the
purpose of detecting and classifying several
organics as aromatics, oxygenates, alkanes,
nitrogen and chlorine-containing species.
1
Based on the provided both molecular and
elemental information, a recognition
algorithm was developed and the
experimental results confirmed the potential
of this technique for analytical applications
as a highly specific and sensitive detector.
2. Experimental
The experimental set-up used in this
study consisted of gas cylinders, a bubbler
in an ice-water bath, a plasma jet, an AC
power supply, an oscilloscope for voltagecurrent measurements and a miniature
spectrometer
for
capturing
atomic/molecular optical emission.
3. Results
For the development of the spectral
database, spectra of 15 compounds between
200 and 900 nm at room temperature were
collected with spectral resolution of 0.4 nm.
Selected species were used to represent the
different compound classes such as alkanes
alcohols and acetone, aromatics, nitrogencontaining compounds and organochlorides
(as will be presented).
Figure 1 illustrates the plasma
spectra of four aliphatic hydrocarbons. A
typical plasma spectrum is composed of
several
atomic
emission
lines,
corresponding to transitions of neutral
atoms or ions of those atomic species; and
bands related to the rovibrational transitions
from excited diatomic species. Due to the
difference in the concentration of the
compounds in the vapor phase, we have
normalized all the spectra intensities with
respect to the C2 Swan band intensity at 563
nm, which is given a relative value 1 as
intensity. All four spectra show strong
emission bands due to the electronic
relaxation of C2 (d3Πg-a3Πa; triplet Swan
band systems) at 473, 516 and 563 nm
(corresponding to the v’ – v” 1-0, 0-0 and 01 vibrational bands, respectively). The
medium and weak emission is mainly due to
excited CH (B2Σ—X2Π) and CH (A2Δ—
X2Π) radicals, respectively at 387 and 431
nm. This figure illustrates the dependence
of the dissociation/excitation process upon
the
carbon
number
for
aliphatic
hydrocarbons; a slight decreasing intensity
ratio of CH (431 nm) and C2 (473 nm)
bands along the homologous series.
Figure 1. Emission spectrum of pentane, hexane, heptane
and decane in argon. The spectra are dominated by
molecular bands related to CH (B2Σ—X2Π) at 387 nm, CH
(A2Δ—X2Π) at 431 nm, and C2 Swan bands (d3Πg-a3Πa) at
473, 516 and 563 nm.
Emission spectra of methanol,
hexanol, decanol are presented in Figure 2.
In general, similar to the n-alkanes, the
spectra of the alcohols are dominated by the
emission of the diatomic radicals CH and
C2. In addition, emission bands from OH
(A2Σ+—X2Π) at 310 nm and the atomic
carbon (C 1P01S) line at 247 nm are also
observed. Although these members of the
alcohol (homologous) group are similar in
structure, their optical emission spectra
differ in the relative intensity of the carbon
line (247 nm) with respect to the OH band
(310 nm). An acetone emission spectrum is
also presented in Figure 2. Its spectrum is
similar to that of the hydrocarbons
exhibiting only diatomic bands of CH and
C2 species. The slight increase in the CH
(A-X) population (431 nm) with respect to
C2 species (473 nm) is seen as well in the
alcohol and acetone spectra. This trend is
opposite
for
aliphatic
saturated
hydrocarbons.
organics), nitrogen-contained substances
(nitrogenous compounds, characteristic of
many
traditional
explosives)
and
[ii]
organochlorides (representative of TICs &
pesticides). The goal of the work described
here is to demonstrate the analytical
capability of the new detector in identifying
and classifying unknown compounds.
We foresee that in the future it will
be necessary to include spectra of both
inorganic and organic compounds in order
to enhance this capability for the absolute
identification of the unknown chemicals
within a variety of environments.
Table 1 – Summary of the identified species, electronic
transitions and their dominant bands or line positions for
different compound class.
Compound
Class
Alcohols
Figure 2. Emission spectra of methanol, hexanol, decanol
and acetone in argon. For the alcohols the main
characteristic band is OH(A2Σ+-X2Π) at 309 nm
For
the
evaluation
of
the
dissociation/excitation
of
aromatic
structures by the micro-plasma, toluene and
chlorobenzene were tested under similar
conditions. Three different nitrogencontained
compounds,
acetonitrile,
nitropropane and nitrobenzene.
Aliphatic
Hydrocarbons
4. Development of recognition algorithm
for spectral classification or identification
Aromatic
To discern whether the plasma-based OES
could provide compound classification or
identification of unknown organics, an
algorithm was developed by which to
compare spectra of unknown compounds to
those within a spectra database, developed
using the micro-plasma system. Notably this
algorithm includes comparison of both
atomic and diatomic electronic emission.
For the “starter set” library we have
collected 15 spectral data sets from the
following compound classifications, alkanes
(saturated organics), alcohols and acetone,
(oxygenates),
aromatics
(unsaturated
Nitrogencontaining
Chlorinecontaining
Spectral transitions and
line position (nm)
C (1P01S) at 247, OH
(A2Σ+-X2Π) at 309, CH
(B2Σ—X2Π) at 387, CH
(A2Δ-X2Π) at 431.25 and
C2 (d3Πg-a3Πa) at 473,
516, 563
C (1P01S) at 247, CH
(B2Σ—X2Π) at 387, CH
(A2Δ-X2Π) at 431.25 and
C2 (d3Πg-a3Πa) at 473,
516, 563
C (1P01S) at 247, CH
(B2Σ—X2Π) at 387, CH
(A2Δ-X2Π) at 431 and C2
(d3Πg-a3Πa) at 473, 516,
563
N2 (C3Πu—B3Πg) at 337
and 358, CN (B2Σ+-X2Σ+)
at 388 and C2 (d3Πg-a3Πa)
at 473, 516, 563
Cl (4D0-4P) at 821, 833,
838, Cl2 2(3Πg)1(3Πu) at
251
In general both the relative
intensities, and presence (or absence) of
3
particular spectral peaks, as characteristic of
particular atomic and diatomic radicals
served as the basis for (a) classifying an
unknown compound against the references
classes of compounds as well as (b) to
potentially identify the unknown substance
by comparison to the spectral library.
Spectra for compounds within each
category were observed to exhibit high
similarity, sufficiently so that these were
averaged to yield the nominal spectrum
representing the particular species category.
Table 1 lists the related spectral transitions
that characterize substances of different
chemical class.
In summary, this program software
is able to match the spectrum of an
unknown sample with the compound from
the spectral database or identifying its
compound class, thereby automatically
performing spectrum matching and library
searching operations. In addition, this
program is readily expanded by adding
further spectrum of new standard
(reference) compounds. Further details will
be presented.
5. Conclusions
A new spectroscopic analysis
technique based on the use of plasma as an
atomization and excitation source for
atomic
emission
spectroscopy
was
presented in this research. The electronic
sniffer or dielectric barrier discharge pencil
detector has real-time detection capabilities
with the advantage of simultaneously
extracting
elemental
and
molecular
information from organic and inorganic
samples. It operates at atmospheric pressure
and it miniaturized.
A spectral signature database has
been created based on the emission spectra
of a variety of organic compounds such as
alkanes (saturated organics), alcohols and
acetone,
(oxygenates),
aromatics
(unsaturated organics), nitrogen-containing
compounds
(nitrogenous
compounds,
characteristic
of
many
traditional
explosives)
and
organochlorides
(representative of TICs & pesticides). In
addition we developed a simple method for
the classification or identification based
upon a spectral recognition algorithm that
calculates the variance between the most
intense lines and bands of unknown
substance and a compound class or a
specific compound from spectral library.
Acknowledgments
The work was supported through a
Phase II STTR with the U.S. Navy Naval
Air Warfare Center, (NAVAIR), Contract
No. N68335-08-C-0020.
References
i
Y. Sun, Y. Qiu, A. Nie, X. Wang, IEEE
Transactions on Plasma Sci., 35 (2007)
1496-1500.
ii
D. Peyerimoff and R. J. Buenker, Chem.
Phys. 57 (1981) 279