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Article
DFT−Spectroscopy Integrated Identification Method on Unknown
Terrorist Chemical Mixtures by Incorporating Experimental and
Theoretical GC-MS, NMR, IR, and DFT-NMR/IR Data
Keunhong Jeong,*,⊥ Honghyun Kim,⊥ Sein Min, Young Wook Yoon, Yoonjae Cho, Choon Hwa Park,
Tae In Ryu, Seung-Ryul Hwang, and Sung Keon Namgoong
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*
ABSTRACT: In the event of a chemical attack, the rapid identification of
unknown chemical agents is critical for an effective emergency response and
treatment of victims. However, identifying unknown compounds is difficult,
particularly when relying on traditional methods such as gas and liquid
chromatography−mass spectrometry (GC-MS, LC-MS). In this study, we
developed a density functional theory and spectroscopy integrated
identification method (D-SIIM) for the possible detection of unknown or
unidentified terrorist materials, specifically chemical warfare agents (CWAs).
The D-SIIM uses a combination of GC-MS, nuclear magnetic resonance
(NMR) spectroscopy, infrared (IR) spectroscopy, and quantum chemical
calculation-based NMR/IR predictions to identify potential CWA candidates
based on their chemical signatures. Using D-SIIM, we successfully verified the
presence of blister and nerve agent simulants in samples by excluding other
compounds (ethyl propyl sulfide and methylphosphonic acid), which were predicted to be candidates with high probability by GCMS. The findings of this study demonstrate that the D-SIIM can detect substances that are likely present in CWA mixtures and can
be used to identify unknown terrorist chemicals.
D
spectrum; however, its application is limited to individual
molecules. Therefore, it is important to develop complementary techniques for the identification of the unknown
compounds. NMR and infrared (IR) spectroscopy are
powerful techniques that provide complementary information
on the structure and functional groups of unknown
compounds.19−24 In addition, density functional theory
(DFT) calculations can be used to predict the NMR and IR
spectra of compounds.25−32
The identification of unknown compounds can be
significantly improved by combining various analytical
techniques, including GC-MS, NMR, IR, and DFT calculations. This multifaceted approach is essential for overcoming
the limitations of individual methods and enhancing the
reliability of compound identification.
Recently, several studies have demonstrated the potential of
combining various techniques�MS, NMR, IR, and DFT-
uring the past few decades, it has been difficult to achieve
a comprehensive approach for the determination of
unknown chemicals used in terrorist attacks because of the vast
number of chemical libraries and the continuous synthesis of
new compounds over time.1−10
The identification of unknown compounds is necessary in
many fields, including pharmaceuticals, environmental sciences, and forensics. Gas chromatography−mass spectrometry
(GC-MS) and liquid chromatography−mass spectrometry
(LC-MS) are widely used to identify unknown compounds.11−13 However, these techniques rely on library
matching, which is not always feasible for newly discovered
compounds that have limited reference data.14,15 Even though
the recently developed 2D-GC/TOF-MS and Orbitrap-MS
methods provide exact masses with reliable molecular
formulas, enormous structural isomers cannot be used to
identify unknown chemicals. Certain molecules produce
minimal mass spectral fragmentation patterns that cannot be
used to identify compounds, such as diastereomers and
positional isomers, and cannot be readily differentiated by
mass spectroscopy.16−18 Proper sample preparation is crucial
for accurate analysis, and errors in this process can result in
unreliable results. As an identification method, nuclear
magnetic resonance (NMR) spectroscopy has a crucial role
in library search and structural elucidation using a 2-D
© 2023 American Chemical Society
Received:
Revised:
Accepted:
Published:
694
August 15, 2023
December 11, 2023
December 12, 2023
December 28, 2023
https://doi.org/10.1021/acs.analchem.3c03647
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Figure 1. DFT−spectroscopy integrated identification method (D-SIIM) and its procedure for identifying unknown terrorist chemicals.
NMR/IR methods�for the identification of unknown
compounds.33−36 However, no study has integrated all of
these systems to identify chemicals, which would allow for a
comprehensive analysis of unknown compounds by combining
the strengths of each technique. The goal of this study is to
evaluate the effectiveness of this combined approach for
identifying unknown compounds and to demonstrate its
potential in real-world applications. In particular, we focus
on the application of this approach to the identification of
hazardous terrorist chemicals that are of great importance for
public safety and environmental protection. Moreover,
terrorists can intentionally modify the structures of known
chemical warfare agents (CWAs) to avoid detection, making it
more challenging to identify these compounds. Therefore,
alternative and complementary techniques are required to
improve the accuracy and reliability of the identification of
unknown compounds.
As a proof of concept, the DFT−spectroscopy integrated
identification method (D-SIIM) was applied to a set of
simulant and actual CWA samples (Figure 1). For simulant
samples, the study focused on detecting diethyl sulfide (DES)
as a simulant of the blister agent HD and diisopropyl
methylphosphonate (DIMP) and dimethyl methylphosphonate (DMMP) as simulants of nerve agents. For the actual
CWA samples, the study analyzed a mixture of blister and
nerve agents as well as mixtures of different types of CWAs.
A GC-MS library was used as an initial screening method to
identify potential CWA candidates. However, owing to the
possibility of false positives, further analysis is necessary to
confirm the identity of the CWA candidates. We performed
NMR and IR experiments and quantum chemical calculations
on the CWA candidates and compared the experimental data
to theoretical predictions to confirm their identity. Overall, the
D-SIIM approach demonstrated promising results for the
identification and confirmation of CWA candidates in
simulants and actual CWA samples. This approach could be
useful for identifying unknown or unidentified terrorist
materials in real-world situations, such as in the field or at
security checkpoints.
■
EXPERIMENTAL SECTION
GC-MS Measurement. A mixture of chemical warfare
agent simulants was subjected to GC-MS analysis using an
Agilent Technologies 7890A instrument. Potential blister and
nerve agent simulants were identified by using a 5975C
detector (Agilent Technologies). The splitless mode was
utilized for the GC-MS analysis with helium as the carrier gas
at a flow rate of 3 mL/min. The column (DB-5MS, 0.32 mm ×
30 m, 0.25 μm film thickness) was heated to 40 °C for 1 min
before being heated further to 280 °C at a rate of 10 °C/min.
The injector, interface, and source temperatures were 250, 250,
and 230 °C, respectively. The instrument was set to an
electron energy of 70 eV, an emission current of 100 μA, and a
scanned mass range of m/z 27−500. Two types of simulant
mixtures were prepared: a combination of DES and DIMP,
which is a mixture of a blister and a nerve agent, and a
combination of DIMP and DMMP, which is a combination of
nerve agents. All samples were prepared by mixing 20 mL of
hexane with 25 μL of each simulant, except for DES (2 mL)
due to the limit of detection concentration.
NMR/IR Measurement. 1H NMR experiments were
performed at 7 T by using a Bruker Avance III 300 MHz
spectrometer. All NMR spectra were obtained at room
temperature using 30° pulses. Approximately 300 μL of each
sample was placed in NMR tubes containing CDCl3. The
solution was transferred to a 5 mm NMR tube and referenced
to internal CDCl3 (δ: 7.26 ppm).
The analyzed samples were evaluated by using a universal
attenuated total reflectance (UATR) attachment on an FT-IR
spectrometer (PerkinElmer Spectrum 100). The sample cell
was purged with nitrogen gas throughout data collection to
exclude carbon dioxide and water vapor. ATR spectra were
measured at a resolution of 4 cm−1 in the range of 4000−380
cm−1 fitted with a deuterated triglycine sulfate detector. The
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Figure 2. Identification of the blister agent simulant (DES) by comparing experimental NMR data and theoretical calculations after GC-MS
measurement.
Figure 3. Identification of the blister agent simulant (DES) by comparing experimental IR data and theoretical calculations after GC-MS
measurement.
UATR employed a diamond-coated zinc selenide internal
reflection element. The sample spectra were interpreted after
the spectra of both the empty cell and the ionic medium.
Theoretical Study. NMR Spectrum Prediction. Conformation-based 1H and 13C NMR chemical shift calculations
were performed as follows.34 In the first step of the calculation,
to extract conformational isomers from each structure, isomer
structures were generated from each structure within the
threshold of 4.0 kcal/mol relative energy using Discovery
Studio 2021. Each isomer was separated from the other
conformational isomers for further DFT calculations. DFT
calculations were performed using the Gaussian 16 software
package.37 The obtained conformers were used for subsequent
computations of the optimization and NMR chemical shifts
using the M06-2X/6-311+G(2d,p) and MPW1PW91/6311+G(2d,p) functional and base set combinations for the
chloroform solvent system. The SMD implicit solvent model
was used, and an ultrafine integration grid was applied. The
final 1H and 13C NMR chemical shifts were further tuned by
considering the influence of each conformer on the total
Boltzmann distribution and taking into account the relative
energies. Calibration of the calculated 1H and 13C chemical
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Table 1. GC-MS Library Qual/Similarity Prediction Results for Each Mixture
DES and DIMP
DES
DMMP and DIMP
DIMP
DMMP
DIMP
rank
library
qual/similarity (%)
library
qual/similarity (%)
library
qual/similarity (%)
library
qual/similarity (%)
1
2
EPS
DES
83
47
DIMP
MPA
86
83
DMMP
MPA
97
96
DIMP
MPA
90
90
Figure 4. Identification of the mixture of blister and nerve agent simulants by comparing experimental NMR data and theoretical calculations after
GC-MS measurement.
shifts was performed using a previously described standard
approach (scaling factors).38
IR Spectrum Prediction. DFT calculations were carried out
using Gaussian 16 software to optimize the structure of the
CWA simulants and determine their vibrational spectra using
the B3LYP and M06-2X methods.37 Both methods employed
the 6-311G+(d,p) basis set without symmetry constraints,
which has been reported to be the most reliable method for
predicting the vibrational spectra of CWAs.39 Wavenumbers
were corrected by using scale factors suitable for each method.
Pulay scaled quantum mechanical correction was used with the
FCART 7 program to correct the wavenumbers calculated
using the B3LYP method,40 whereas a correction factor of
0.9569, corresponding to the basis set used, was multiplied by
the wavenumbers calculated using the M06-2X method.41
critical points that could be ruled out from the list (Figure 2).
First, the number of signals from the experimental data was not
the same as that predicted for both 1H and 13C NMR. Second,
the highlighted chemical shifts were not shown in the 1H and
13
C NMR data. These two factors provided important reasons
for ruling out EPS, which was ranked first in the GC-MS
experiment. The experimental IR spectrum of DES was
compared with the calculated IR spectrum of EPS (Figure
3). Two distinct peaks were observed because of the structural
differences between the DES and EPS. The theoretical IR
spectrum of EPS exhibited C−C−C symmetric and asymmetric stretching at 885 and 1045 cm−1, which were absent in
the experimental IR spectrum of DES. This observation
strongly indicates that the sample subjected to NMR analysis
was not EPS. Consequently, EPS was excluded from the
material candidates.
We performed the same procedure (D-SIIM) for DIMP and
DMMP, which are nerve agent simulants, separately. DIMP
(90%) and DMMP (97%) were the first-ranked candidates.
Interestingly, the GC-MS library suggested methylphosphonic
acid (MPA) as the second-ranked candidate for both samples
(90 and 96%, respectively). 1H and 13C NMR experiments
were performed for both simulants, and conformation-based
NMR chemical predictions were performed for DIMP,
DMMP, and MPA. As the simulated data provided precise
chemical shifts, the comparison of the experimental 1H and 13C
chemical shifts to the theoretical values provided enough
information to confirm the presence of DIMP and DMMP in
the samples (deviation is less than 0.3 and 2 ppm for 1H and
13
C, respectively). These analyses successfully ruled out MPA
from the candidate materials (the same rationale as DES,
■
RESULTS AND DISCUSSION
After testing DES, the blistering agent (HD) simulant, the GCMS library predicted that the most probable and second most
probable material in solution was ethyl propyl sulfide (EPS)
(83%) and DES (47%), respectively. This result justifies the
need for other spectroscopic techniques to accurately
determine which compounds were present in the sample.
Thus, 1H and 13C NMR were performed on the DES sample
(Figure 2). As DES and EPS should have similar chemical
shifts and IR signals, we also performed theoretical NMR and
IR studies. In the NMR experiment and chemical shift
calculations, chemical shift predictions on DES showed quite
similar numbers to the real experiments, with very slight
deviations (0.2 ppm for 1H NMR and 3 ppm for 13C NMR).
The predicted chemical shifts of the EPS contained several
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Figure 5. Identification of the mixture of blister and nerve agent simulants by comparing experimental IR data and theoretical calculations after
GC-MS measurement.
Figures S1 and S2). Furthermore, the highlighted signals,
which could be used to exclude MPA, were different for each
case. In addition, a comparison of the IR spectra confirmed
that MPA was not present, as the slightly different chemical
structures of DMMP, DIMP, and MPA caused variations in the
shapes of their IR spectra. While DMMP, DIMP, and MPA all
contained P−CH3 and P�O bonds, the positions of the
stretching peaks for these bonds differed. Moreover, the
absence of the O−H stretching peak at 3626 cm−1, which is
present only in MPA, indicates that the sample does not
contain MPA (Figures S3 and S4). In summary, experimental
NMR and IR data, along with precise DFT-based prediction
data on the suggested chemicals from GC-MS, can provide
information regarding the identity of unknown substances in
samples in an integrated and unified manner.
To demonstrate the potential of the D-SIIM in more
complicated situations, mixtures of the CWA simulants were
analyzed using the D-SIIM. The first case involved a mixture of
a blister agent simulant (DES) and a nerve agent simulant
(DIMP), and the second case involved a mixture of two nerve
agent simulants (DMMP and DIMP). The first and second
candidates for the mixtures were the same as those of the
individual samples, and we performed the same D-SIIM for
both cases (Table 1).
For the highly ranked compounds after GC-MS, 1H and 13C
NMR chemical shifts were obtained, and their NMR
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experimental data were compared with the predicted chemical
shifts after conformation-based NMR prediction calculations.
These chemical shift comparisons can provide important
information to exclude some highly plausible substances
predicted to be in the mixtures by GC-MS. During analysis,
it was difficult to exclude other highly ranked molecules by
simply comparing the number of signals; however, highlighted
chemical shifts could be used to identify terrorist chemical
simulants in the sample, which were not shown in the
experimental data. Notably, these analyses can be performed
without extensive analysis and can be used to identify
unknown terrorist chemicals when mixtures are sampled in
an area where a chemical attack has occurred (Figure 4; the
results of the mixture of the nerve agents (DMMP and DIMP)
are shown in Figure S5).
The experimental IR spectra of the nerve agent mixtures
were compared with the precisely calculated values of DIMP,
DMMP, and MPA. Comparing the calculated IR values of
DIMP and DMMP with the experimental IR spectra of the
nerve agent mixtures, the peaks of the main functional groups
appeared at very similar positions (Figure S6). However, MPA,
which was predicted as a candidate material with a high
probability in GC-MS, was excluded from the potential
candidates based on the differences in the peak positions of
the main bonds (833, 853, 1284, and 3626 cm−1 of P−OH, P−
CH3, P�O, and O−H stretching, respectively), similar to the
observation in the identification of individual chemical
samples.
In the identification of the blister and nerve agent mixture,
EPS and MPA, which were predicted as candidates with a high
probability in GC-MS, could be excluded from the potential
candidates based on the difference in the peak positions of the
main bonds (885 and 1045 cm−1 of C−C−C stretching in EPS
and 833, 853, 1284, and 3626 cm−1 of P−OH, P−CH3, P�O,
and O−H stretching in MPA, respectively), similar to the
observation in the identification of the individual chemical
samples. Meanwhile, in the calculated and experimental IR
spectra of DES and DIMP, the peaks corresponding to the
main functional groups appeared at positions very similar to
those in the individual chemical samples (Figure 5). These
results indicate that for mixtures of hazardous chemicals (even
with the presence of other substances), experimental NMR and
IR data, along with precise DFT-based prediction data on the
suggested chemicals from GC-MS, can still provide information about the substances that are present in the sample.
■
Article
even without in-depth analysis. These findings have significant
practical implications, such as identifying unknown terrorist
chemicals from mixtures sampled in the field. Our study
represents the first demonstration of the potential of the DSIIM for detecting and identifying terrorist chemicals and has
several advantages over previous studies. D-SIIM can be
performed in a relatively short amount of time and does not
require highly specialized equipment. Furthermore, it can
identify multiple CWAs in a single sample, which is not
possible by using traditional detection methods.
In the future, D-SIIM can be developed to detect and
identify a wider range of potential terrorist chemicals, including
those that have not been studied previously. It can also be used
for the analysis of more complex samples in various settings,
such as forensic applications. In addition, the findings of this
study can contribute to the development of new and more
effective methods for combating terrorism.
■
ASSOCIATED CONTENT
sı Supporting Information
*
The Supporting Information is available free of charge at
https://pubs.acs.org/doi/10.1021/acs.analchem.3c03647.
A comparison of calculated and experimental NMR
spectra (Figures S1−S4) and IR spectra (Figures S5 and
S6), GC-MS analysis results (Figures S7 and S8),
calculated IR spectra (Figures S9−S13), and experimental (Figures S14−S18) and calculated (Figures
S19−S22) NMR spectra (PDF)
■
AUTHOR INFORMATION
Corresponding Author
Keunhong Jeong − Department of Physics and Chemistry,
Korea Military Academy, Seoul 01805, South Korea;
orcid.org/0000-0003-1485-7235; Email: doas1 mind@
kma.ac.kr, doas1 mind@berkeley.edu
Authors
Honghyun Kim − Department of Civil Engineering and
Environmental Sciences, Korea Military Academy, Seoul
01805, South Korea
Sein Min − Department of Chemistry, Seoul Women’s
University, Seoul 01797, South Korea
Young Wook Yoon − Department of Chemistry, Seoul
Women’s University, Seoul 01797, South Korea
Yoonjae Cho − Accident Coordination and Training Division,
National Institute of Chemical Safety, Daejeon 34114, South
Korea
Choon Hwa Park − Accident Coordination and Training
Division, National Institute of Chemical Safety, Daejeon
34114, South Korea
Tae In Ryu − Accident Coordination and Training Division,
National Institute of Chemical Safety, Daejeon 34114, South
Korea; orcid.org/0000-0002-6542-6796
Seung-Ryul Hwang − Accident Coordination and Training
Division, National Institute of Chemical Safety, Daejeon
34114, South Korea
Sung Keon Namgoong − Department of Chemistry, Seoul
Women’s University, Seoul 01797, South Korea
CONCLUSIONS
In this study, we successfully demonstrated the feasibility and
effectiveness of using D-SIIM to detect and identify potential
terrorist chemicals. Our study used simulant materials of a
blister agent (DES), nerve agents (DIMP and DMMP), and
mixtures of these simulants and compared their experimental
spectra to the predicted chemical shifts and IR spectra using
extensive theoretical calculations. Results showed that GC-MS
library prediction is not always reliable, and other spectroscopic techniques, such as NMR and IR, are necessary to
determine which compounds are present in the sample. We
demonstrated that by performing reliable theoretical studies on
NMR and IR, we could rule out highly ranked materials that
were not measured experimentally, such as EPS and MPA.
Conformation-based NMR chemical shift prediction and IR
spectral comparison provide critical information for identifying
substances in samples and excluding highly ranked molecules,
Complete contact information is available at:
https://pubs.acs.org/10.1021/acs.analchem.3c03647
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⊥
K.J. and H.K. contributed equally.
Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS
This research was funded by the National Institute of
Chemical Safety (NICS) of the Ministry of Environment
(MOE) of the Republic of Korea and supported by a National
Research Foundation of Korea (NRF) grant funded by the
Korean Government (MSIT) (No. 2020R1C1C1007888).
■
Article
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