Selection of a piezoelectric sensor array for detecting volatile organic substances in water

Шуба, А. А.; Кучменко, Т. А.; Samoilova, E. I.; Bel'skikh, N. V.

doi:10.3103/s0027131416010156

Cited by 6 publications

(6 citation statements)

References 11 publications

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“…The relative standard deviations of sensor signals for the studied volatile compounds are presented in Table 2 . The limit of detection for the volatile compounds using the selected sensors was between 0.012 and 135 mg/m 3 , as estimated earlier [ 48 , 53 , 56 ].…”

Section: Methodssupporting

confidence: 58%

“…The choice of sensors for an array is influenced by their high sensitivity to various classes of volatile substances, including volatile biomarkers of diseases in the urine [ 14 , 15 , 16 ]. Films of 18C6, Tween were chosen for the detection of carboxylic and hydroxy acids [ 47 , 48 ], and MCNT, BCB, MR for ammonia and amines [ 49 , 50 , 51 ]. PEGSb was selected for detection of acids, alcohols, ketones [ 52 , 53 ], and TX-100 for nitrogen- and sulfur-containing compounds [ 54 , 55 ].…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, the resulting array should be effective for solving the problem. The mass sensitivities of selected sensors to some VOC vapors, which were obtained in earlier studies [ 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 ], are presented in Table 2 .…”

Section: Methodsmentioning

confidence: 99%

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Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Кучменко

Menzhulina

Шуба

2022

Sensors

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Currently, antibiotics are often prescribed to children without reason due to the inability to quickly establish the presence of a bacterial etiology of the disease. One way to obtain additional diagnostic information quickly is to study the volatile metabolome of biosamples using arrays of sensors. The goal of this work was to assess the possibility of using an array of chemical sensors with various sensitive coatings to determine the presence of a bacterial infection in children by analyzing the equilibrium gas phase (EGP) of urine samples. The EGP of 90 urine samples from children with and without a bacterial infection (urinary tract infection, soft tissue infection) was studied on the “MAG-8” device with seven piezoelectric sensors in a hospital. General urine analysis with sediment microscopy was performed using a Uriscan Pro analyzer and using an Olympus CX31 microscope. After surgical removal of the source of inflammation, the microbiological studies of the biomaterial were performed to determine the presence and type of the pathogen. The most informative output data of an array of sensors have been established for diagnosing bacterial pathology. Regression models were built to predict the presence of a bacterial infection in children with an error of no more than 15%. An indicator of infection is proposed to predict the presence of a bacterial infection in children with a high sensitivity of 96%.

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Section: Methodssupporting

confidence: 58%

Section: Methodsmentioning

confidence: 99%

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Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Кучменко

Menzhulina

Шуба

2022

Sensors

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“…The loading plot ( Figure 8 ) shows that the initial signals made the most considerable contribution to the model of the sensors ΔF max,i , and the signals from the first set of sensors were more significant than from the second set. Therefore, taking into account the loadings for the seven principal components of the PCA–LDA model (shown in Table 6 , Figure 8 ), the most significant for classification were the signals of sensors with modifiers of carboxylated carbon nanotubes, zirconium nitrate, hydroxyapatite, methyl orange, bromocresol green, Triton X-100, and polyethylene glycol and its ethers, which are highly sensitive to vapors of nitrogen- and oxygen-containing compounds according to our previous investigation of sorption features of VOCs on these sorbents [ 37 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ].…”

Section: Discussionmentioning

confidence: 99%

“…These sorbents were chosen among 50 phases due to them having hypersensitivity to various classes of highly volatile organic compounds (alcohols, aldehydes, acids, ketones, amines, and arenes) [ 36 , 37 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ], including volatile biomarkers of respiratory pathologies.…”

Section: Methodsmentioning

confidence: 99%

Portable Electronic Nose for Analyzing the Smell of Nasal Secretions in Calves: Toward Noninvasive Diagnosis of Infectious Bronchopneumonia

Кучменко

Шуба

Умарханов

et al. 2021

Veterinary Sciences

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The paper demonstrates a new approach to identify healthy calves (“healthy”) and naturally occurring infectious bronchopneumonia (“sick”) calves by analysis of the gaseous phase over nasal secretions using 16 piezoelectric sensors in two portable devices. Samples of nasal secretions were obtained from 50 red-motley Holstein calves aged 14–42 days. Calves were subjected to rectal temperature measurements, clinical score according to the Wisconsin respiratory scoring chart, thoracic auscultation, and radiography (Carestream DR, New York, USA). Of the 50 calves, we included samples from 40 (20 “healthy” and 20 “sick”) in the training sample. The remaining ten calves (five “healthy” and five “sick”) were included in the test sample. It was possible to divide calves into “healthy” and “sick” groups according to the output data of the sensor arrays (maximum sensor signals and calculated parameters Ai/j) using the principal component linear discriminant analysis (PCA–LDA) with an accuracy of 100%. The adequacy of the PCA–LDA model was verified on a test sample. It was found that data of sensors with films of carbon nanotubes, zirconium nitrate, hydroxyapatite, methyl orange, bromocresol green, and Triton X-100 had the most significance for dividing samples into groups. The differences in the composition of the gaseous phase over the samples of nasal secretions for such a classification could be explained by the appearance or change in the concentrations of ketones, alcohols, organic carboxylic acids, aldehydes, amines, including cyclic amines or those with a branched hydrocarbon chain.

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Application of piezoelectric e-noses for diagnostics of animal and human health

Кучменко¹,

Шуба²

2023

Nanotechnology-Based E-Noses

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Selection of a piezoelectric sensor array for detecting volatile organic substances in water

Cited by 6 publications

References 11 publications

Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Portable Electronic Nose for Analyzing the Smell of Nasal Secretions in Calves: Toward Noninvasive Diagnosis of Infectious Bronchopneumonia

Application of piezoelectric e-noses for diagnostics of animal and human health

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