scholarly journals Active Mode Remote Infrared Spectroscopy Detection of TNT and PETN on Aluminum Substrates

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
John R. Castro-Suarez ◽  
Leonardo C. Pacheco-Londoño ◽  
Joaquín Aparicio-Bolaño ◽  
Samuel P. Hernández-Rivera
Keyword(s):  
Infrared Spectroscopy ◽  
Energetic Materials ◽  
Angle Of Incidence ◽  
Least Squares Regression ◽  
Active Mode ◽  
Infrared Telescope ◽  
Infrared Spectrometer ◽  
Highly Energetic Materials ◽  
Aluminum Plates ◽  
Aluminum Substrates

Two standoff detection systems were assembled using an infrared telescope coupled to a Fourier transform infrared spectrometer, a cryocooled mercury-cadmium telluride detector, and a telescope-coupled midinfrared excitation source. Samples of the highly energetic materials (HEMs) 2,4,6-trinitrotoluene (TNT) and pentaerythritol tetranitrate (PETN) were deposited on aluminum plates and detected at several source-target distances by carrying out remote infrared spectroscopy (RIRS) measurements on the aluminum substrates in active mode. The samples tested were placed at 1–30 m for the RIRS detection experiments. The effect of the angle of incidence/collection of the IR beams on the vibrational band intensities and the signal-to-noise ratios (S/N) were investigated. Experiments were performed at ambient temperature. Surface concentrations from 50 to 400 μg/cm2 were studied. Partial least squares regression analysis was applied to the spectra obtained. Overall, RIRS detection in active mode was useful for quantifying the HEMs deposited on the aluminum plates with a high confidence level up to the target-collector distances of 1–25 m.

FT-IR Standoff Detection of Thermally Excited Emissions of Trinitrotoluene (TNT) Deposited on Aluminum Substrates

2013 ◽  
Vol 67 (2) ◽  
pp. 181-186 ◽  
Author(s):  
John R. Castro-Suarez ◽  
Leonardo C. Pacheco-Londoño ◽  
Miguel Vélez-Reyes ◽  
Max Diem ◽  
Thomas J. Tague ◽  
...  
Keyword(s):  
Energetic Materials ◽  
Solid Phase ◽  
Detection System ◽  
Target Surface ◽  
Least Squares Regression ◽  
Passive Mode ◽  
Standoff Detection ◽  
Highly Energetic Materials ◽  
Aluminum Plates ◽  
Aluminum Substrates

A standoff detection system was assembled by coupling a reflecting telescope to a Fourier transform infrared spectrometer equipped with a cryo-cooled mercury cadmium telluride detector and used for detection of solid-phase samples deposited on substrates. Samples of highly energetic materials were deposited on aluminum substrates and detected at several collector-target distances by performing passive-mode, remote, infrared detection measurements on the heated analytes. Aluminum plates were used as support material, and 2,4,6-Trinitrotoluene (TNT) was used as the target. For standoff detection experiments, the samples were placed at different distances (4 to 55 m). Several target surface temperatures were investigated. Partial least squares regression analysis was applied to the analysis of the intensities of the spectra obtained. Overall, standoff detection in passive mode was useful for quantifying TNT deposited on the aluminum plates with high confidence up to target–collector distances of 55 m.

scholarly journals Detection of Nitroaromatic and Peroxide Explosives in Air Using Infrared Spectroscopy: QCL and FTIR

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Leonardo C. Pacheco-Londoño ◽  
John R. Castro-Suarez ◽  
Samuel P. Hernández-Rivera
Keyword(s):  
Pattern Recognition ◽  
Infrared Spectroscopy ◽  
Gas Phase ◽  
Energetic Materials ◽  
Organic Peroxide ◽  
Triacetone Triperoxide ◽  
Quantum Cascade ◽  
Spectroscopic Information ◽  
Ft Ir ◽  
Highly Energetic Materials

A methodology for processing spectroscopic information using a chemometrics-based analysis was designed and implemented in the detection of highly energetic materials (HEMs) in the gas phase at trace levels. The presence of the nitroaromatic HEM 2,4-dinitrotoluene (2,4-DNT) and the cyclic organic peroxide triacetone triperoxide (TATP) in air was detected by chemometrics-enhanced vibrational spectroscopy. Several infrared experimental setups were tested using traditional heated sources (globar), modulated and nonmodulated FT-IR, and quantum cascade laser- (QCL-) based dispersive IR spectroscopy. The data obtained from the gas phase absorption experiments in the midinfrared (MIR) region were used for building the chemometrics models. Partial least-squares discriminant analysis (PLS-DA) was used to generate pattern recognition schemes for trace amounts of explosives in air. The QCL-based methodology exhibited a better capacity of discrimination for the detected presence of HEM in air compared to other methodologies.

scholarly journals Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Plant Ecology ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Abstract Background The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT’s full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000–550 cm−1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization—mDP, procyanidins:prodelphidins ratio—PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

Investigating the total antioxidant capacity of gluten-free grains with miniaturized near-infrared spectrometer

NIR news ◽  
2019 ◽  
Vol 30 (5-6) ◽  
pp. 35-38
Author(s):  
Verena Wiedemair ◽  
Christian Wolfgang Huck
Keyword(s):  
Antioxidant Capacity ◽  
Total Antioxidant Capacity ◽  
High Performance ◽  
Near Infrared ◽  
Least Squares Regression ◽  
Test Set ◽  
Total Antioxidant ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer ◽  
Infrared Instruments

The use of ever smaller near-infrared instruments is becoming more and more prevalent, since they are cheaper, more versatile and often advertised as high-performance spectrometer. The last claim is rarely verified by independent researchers, which is why the presented work evaluates the performance of three hand-held spectrometers in comparison to a benchtop instrument. Seventy-seven samples comprising buckwheat, millet and oat were investigated for their total antioxidant capacity using Folin–Ciocalteu and near-infrared spectroscopy. Partial least squares regression models were established using cross- and test set validation. Results showed that all instruments were able to predict total antioxidant capacity to some extent. The coefficients of determinations ranged from 0.823 to 0.951 for cross-validated and from 0.849 to 0.952 for test set validated models. Errors for cross-validated models ranged from 1.11 to 2.08 mgGAE/g and for test set validated models from 1.02 to 1.86 mgGAE/g.

Prediction of the CEC to clay ratio using mid-infrared spectroscopy

Soil Research ◽  
2012 ◽  
Vol 50 (1) ◽  
pp. 1 ◽  
Author(s):  
Philip M. Bloesch
Keyword(s):  
Infrared Spectroscopy ◽  
Mean Squared Error ◽  
Clay Mineralogy ◽  
Exchange Capacity ◽  
Diffraction Measurement ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy ◽  
Laboratory Determination ◽  
Validation Set

The ratio of cation exchange capacity to clay (CCR) has been used as an index of clay mineralogy in subsoils low in organic matter in place of the standard X-ray diffraction measurement. Laboratory determination of this ratio is time-consuming and expensive and involves two analyses. In this paper, the CCR has been successfully predicted from mid-infrared diffuse reflectance spectra using partial least-squares regression (PLSR) with a square-root transformation of the CCR values (R2 = 0.860; root mean squared error of prediction = 0.089; relative per cent deviation = 2.660 for an independent validation set). The most important wavelengths used in the PLSR calibration were identified. The prediction of CCR using mid-infrared spectroscopy provides a cheaper and faster alternative to laboratory determination.

Application of visible and near-infrared spectroscopy for evaluation of ewes milk with different feeds

2019 ◽  
Vol 59 (6) ◽  
pp. 1190 ◽  
Author(s):  
A. Bahri ◽  
S. Nawar ◽  
H. Selmi ◽  
M. Amraoui ◽  
H. Rouissi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Random Forest ◽  
Near Infrared Spectroscopy ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Principal Component ◽  
Least Squares Regression ◽  
Random Forest Regression ◽  
Milk Samples

Rapid measurement optical techniques have the advantage over traditional methods of being faster and non-destructive. In this work visible and near-infrared spectroscopy (vis-NIRS) was used to investigate differences between measured values of key milk properties (e.g. fat, protein and lactose) in 30 samples of ewes milk according to three feed systems; faba beans, field peas and control diet. A mobile fibre-optic vis-NIR spectrophotometer (350–2500 nm) was used to collect reflectance spectra from milk samples. Principal component analysis was used to explore differences between milk samples according to the feed supplied, and a partial least-squares regression and random forest regression were adopted to develop calibration models for the prediction of milk properties. Results of the principal component analysis showed clear separation between the three groups of milk samples according to the diet of the ewes throughout the lactation period. Milk fat, protein and lactose were predicted with good accuracy by means of partial least-squares regression (R2 = 0.70–0.83 and ratio of prediction deviation, which is the ratio of standard deviation to root mean square error of prediction = 1.85–2.44). However, the best prediction results were obtained with random forest regression models (R2 = 0.86–0.90; ratio of prediction deviation = 2.73–3.26). The adoption of the vis-NIRS coupled with multivariate modelling tools can be recommended for exploring to differences between milk samples according to different feed systems, and to predict key milk properties, based particularly on the random forest regression modelling technique.

Evaluation of the higher heating value, volatile matter, fixed carbon and ash content of ground bamboo using near infrared spectroscopy

2017 ◽  
Vol 25 (5) ◽  
pp. 301-310 ◽  
Author(s):  
Jetsada Posom ◽  
Panmanas Sirisomboon
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Model Development ◽  
Volatile Matter ◽  
Ash Content ◽  
Least Squares Regression ◽  
Fixed Carbon ◽  
Bomb Calorimetry ◽  
Heating Value

This research aimed to determine the higher heating value, volatile matter, fixed carbon and ash content of ground bamboo using Fourier transform near infrared spectroscopy as an alternative to bomb calorimetry and thermogravimetry. Bamboo culms used in this study had circumferences ranging from 16 to 40 cm. Model development was performed using partial least squares regression. The higher heating value, volatile matter, fixed carbon and ash content were predicted with coefficients of determination (r2) of 0.92, 0.82, 0.85 and 0.51; root mean square error of prediction (RMSEP) of 122 J g−1, 1.15%, 1.00% and 0.77%; ratio of the standard deviation to standard error of validation (RPD) of 3.66, 2.55, 2.62 and 1.44; and bias of 14.4 J g−1, −0.43%, 0.03% and −0.11%, respectively. This report shows that near infrared spectroscopy is quite successful in predicting the higher heating value, and is usable with screening for the determination of fixed carbon and volatile matter. For ash content, the method is not recommended. The models should be able to predict the properties of bamboo samples which are suitable for achieving higher efficiency for the biomass conversion process.

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