A novel method development and validation for determination of 2,4,6-Trinitrotoluene and its metabolites on LC-MS/MS

Aamir, Muhammad; Irum, Sobia; Siddiq, Amer; Batool, Hafiza Monaza; Ahmed, Nisar; Awais, Muhammad; Ali, Sadiq

doi:10.1016/j.ab.2021.114496

Cited by 8 publications

(3 citation statements)

References 17 publications

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“…Since residual TNT in water and soil is usually present at extremely low concentrations, it is crucial to develop a highly selective recognition and sensitive TNT detection sensors for both human and environmental security . Up until now, TNT can be detected by conventional methods such as mass ion migration spectroscopy, gas chromatography–mass spectrometry, , liquid chromatography–mass spectrometry, high-performance liquid chromatography, colorimetry, , etc. However, these methods often face problems such as complex sample preparation, time-consuming measurement, and difficulties in analyzing samples …”

Section: Introductionmentioning

confidence: 99%

Meso-Au/BN Nanosensor for Trinitrotoluene Based on Fluorescence Resonance Energy Transfer and Surface-Enhanced Raman Spectroscopy Mechanisms

Wang,

Xiang,

Ren

et al. 2024

ACS Appl. Nano Mater.

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It is a considerable challenge to develop surface-enhanced Raman spectroscopy sensors with high sensitivity but a lack of selective recognition performance for target species in the applied field. Here, a strategy for fabricating a meso-Au/BN nanoparticle (NP) sensor through a synthesized mesoporous Au NPs' surface modified by BN quantum dots (QDs) and 2-mercaptoethylamine (MEA) through electrostatic attraction and covalent bonding between a sulfur atom in the thiol group and an Au atom, respectively, was implemented to selectively recognize and sensitively detect 2,4,6-trinitrotoluene (TNT). TNT interacted with MEA on the meso-Au NP surface to form a TNT−MEA complex through the electrostatic affinity interaction between the electron-deficient nitro groups and the electron-rich amino group at the fluorescence-tagged sites, approaching the BN QDs on the meso-Au NPs' surface at spatial proximity, leading to the suppression of the fluorescence intensity of BN QDs via the fluorescence resonance energy transfer mechanism, forming the selective recognition of TNT. Additionally, the meso-Au/BN NP sensor enhanced the Raman signal of TNT by the localized surface plasmon resonance hotspots of the meso-Au NP surface, achieving highly sensitive detection of TNT. The limit of detection for TNT was 10 −9 mol•L −1 . Comparing TNT, 2,4-dinitrotoluene, 2,4,6-trinitrophenol, and 2,4-dinitrophenol, the meso-Au/BN NP sensor exhibited much more selective recognition and sensitive detection of TNT than other aromatic compounds. The method can be widely applied in the selective recognition and trace detection of biological molecules, metal ions, and organic pollutants.

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Section: Introductionmentioning

confidence: 99%

Meso-Au/BN Nanosensor for Trinitrotoluene Based on Fluorescence Resonance Energy Transfer and Surface-Enhanced Raman Spectroscopy Mechanisms

Wang,

Xiang,

Ren

et al. 2024

ACS Appl. Nano Mater.

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“…Water quality and resources scarcity are two problems facing the world today due to the geographical, anthropological and socioeconomic influences 1 . Accordingly, sustainable recovery and reuse of the wastewater resources have long been considered as the promising approaches to overcome these problems.…”

Section: Introductionmentioning

confidence: 99%

“…These compounds are a particular class of aromatic molecules with an at least a nitro group (–NO 2 ) at their benzene ring. It has been demonstrated that NACs have widely been distributed in the environment 10 , and 1,3,5-trinitrobenzene (TNB), 2,4,6-trinitrotoluene (TNT), trinitrophenol, tetryl nitramine, hexanitrobenzene are among the well-known NACs 1 .…”

Section: Introductionmentioning

confidence: 99%

Biological 2,4,6-trinitrotoluene removal by extended aeration activated sludge: optimization using artificial neural network

Karimi

Mohammadi

Rajabi

et al. 2023

Sci Rep

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Serious health issues can result from exposure to the nitrogenous pollutant like 2,4,6-trinitrotoluene (TNT), which is emitted into the environment by the munitions and military industries, as well as from TNT-contaminated wastewater. The TNT removal by extended aeration activated sludge (EAAS) was optimized in the current study using artificial neural network modeling. In order to achieve the best removal efficiency, 500 mg/L of chemical oxygen demand (COD), 4 and 6 h of hydraulic retention time (HRT), and 1–30 mg/L of TNT were used in this study. The kinetics of TNT removal by the EAAS system were described by the calculation of the kinetic coefficients K, Ks, Kd, max, MLSS, MLVSS, F/M, and SVI. Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithms (GA) were used to optimize the data obtained through TNT elimination. ANFIS approach was used to analyze and interpret the given data, and its accuracy was around 97.93%. The most effective removal efficiency was determined using the GA method. Under ideal circumstances (10 mg/L TNT concentration and 6 h), the TNT removal effectiveness of the EAAS system was 84.25%. Our findings demonstrated that the artificial neural network system (ANFIS)-based EAAS optimization could enhance the effectiveness of TNT removal. Additionally, it can be claimed that the enhanced EAAS system has the ability to extract wastewaters with larger concentrations of TNT as compared to earlier experiments.

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Selective determination of 2,4,6-Trinitrotoluene (TNT) with cysteamine in deep eutectic solvents

Şen

Bener²,

Aşçı³

et al. 2022

Journal of Molecular Liquids

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A novel method development and validation for determination of 2,4,6-Trinitrotoluene and its metabolites on LC-MS/MS

Cited by 8 publications

References 17 publications

Meso-Au/BN Nanosensor for Trinitrotoluene Based on Fluorescence Resonance Energy Transfer and Surface-Enhanced Raman Spectroscopy Mechanisms

Meso-Au/BN Nanosensor for Trinitrotoluene Based on Fluorescence Resonance Energy Transfer and Surface-Enhanced Raman Spectroscopy Mechanisms

Biological 2,4,6-trinitrotoluene removal by extended aeration activated sludge: optimization using artificial neural network

Selective determination of 2,4,6-Trinitrotoluene (TNT) with cysteamine in deep eutectic solvents

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