Fast-response hydrogen sulfide gas sensor based on electrospinning Co3O4 nanofibers-modified CuO nanoflowers: Experimental and DFT calculation

Sensors and Actuators B Chemical, Год журнала: 2023, Номер 396, С. 134579 - 134579

Опубликована: Сен. 7, 2023

Язык: Английский

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Nanoparticles anchored strategy to develop 2D MoS2 and MoSe2 based room temperature chemiresistive gas sensors

Coordination Chemistry Reviews, Год журнала: 2024, Номер 503, С. 215657 - 215657

Опубликована: Янв. 9, 2024

Язык: Английский

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CuO/ZnO hollow nanocages derived from metal−organic frameworks for ultra-high and rapid response H2S gas sensor

Ceramics International, Год журнала: 2024, Номер 50(9), С. 15767 - 15779

Опубликована: Фев. 14, 2024

Язык: Английский

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Material design and mechanism interpretation of metal oxide nanofibers for improving gas sensitivity

Coordination Chemistry Reviews, Год журнала: 2025, Номер 531, С. 216492 - 216492

Опубликована: Фев. 10, 2025

Язык: Английский

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Nanostructured metal oxide heterojunctions for chemiresistive gas sensors

Journal of Materials Chemistry A, Год журнала: 2023, Номер 11(44), С. 23742 - 23771

Опубликована: Янв. 1, 2023

Metal oxides have been extensively used in environmental monitoring, breath analysis, and food quality assessment. This review summarizes the effects of nanoscale heterojunctions on enhancing gas-sensing performance metal oxide devices.

Язык: Английский

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Highly Efficient CuO-Anchored SnO₂ Nanofiber for Low-Concentration H₂S Gas Sensors

ACS Applied Engineering Materials, Год журнала: 2024, Номер 2(2), С. 431 - 442

Опубликована: Фев. 6, 2024

Metal oxide-based chemiresistive gas sensors are reliable for detecting low concentrations of hydrogen sulfide (H2S) gas, which pose significant harm to human health. This article highlights the improvement in H2S detection by using CuO-decorated SnO2 nanofibers, synthesized combining electrospinning and sputtering. The electrospun PVP/SnO2 fibers calcinated at 600 °C, reducing diameter from 498 220 nm, enhances crystallinity, favoring improved sensing. efficacy nanofibers was explored a temperature ranging 50 200 °C. CuO sputtered nanoparticles 30, 60, 90 s, respectively, on improve relative response, showing importance composite material toward catalytic abilities 60 s boost response 85.71% ppm °C─an 25% more than pristine nanofibers. showed an excellent adsorption/desorption property with recovery times 100 109 H2S. First-principles calculations indicate that O-adsorbed SnO2/CuO system has potential due its high adsorption energy −2.21 eV, charge transfer 0.65 e–, orbital interactions. Our findings conclude superiority industrial applications.

Язык: Английский

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Adsorption and detection analysis of metal clusters (Pt3, Rh3) modified WTe2 monolayers to dissolved gases (CO, CO2, H2, C2H2) in transformer oil: A density functional theory study

Colloids and Surfaces A Physicochemical and Engineering Aspects, Год журнала: 2024, Номер 700, С. 134670 - 134670

Опубликована: Июль 1, 2024

Язык: Английский

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Enhanced oxygen anions generation on Bi2S3/Sb2S3 heterostructure by visible light for trace H2S detection at room temperature

Journal of Hazardous Materials, Год журнала: 2024, Номер 476, С. 134932 - 134932

Опубликована: Июнь 15, 2024

Язык: Английский

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Metal recovery from industrial solid waste by ultrasonic-assisted hydrometallurgical leaching: a review

Environmental Chemistry Letters, Год журнала: 2024, Номер 22(4), С. 2055 - 2090

Опубликована: Май 6, 2024

Язык: Английский

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Ultrasensitive Online NO Sensor Based on a Distributed Parallel Self-Regulating Neural Network and Ultraviolet Differential Optical Absorption Spectroscopy for Exhaled Breath Diagnosis

ACS Sensors, Год журнала: 2024, Номер 9(3), С. 1499 - 1507

Опубликована: Фев. 21, 2024

The concentration of fractional exhaled nitric oxide (FeNO) is closely related to human respiratory inflammation, and the detection its plays a key role in aiding diagnosing inflammatory airway diseases. In this paper, we report gas sensor system based on distributed parallel self-regulating neural network (DPSRNN) model combined with ultraviolet differential optical absorption spectroscopy for detecting ppb-level FeNO concentrations. noise signals spectrum are eliminated by discrete wavelet transform. DPSRNN then built separated multipeak characteristic structure UV NO. Furthermore, each feature region, which given weights finally trained unified structure. final obtained indicate that region contributes different weight prediction. Compared regular convolutional structure, proposed has better performance considering effect absorptions breaking habit bringing as whole into training previous studies. Lab-based results show can stably achieve high-precision NO (2.59-750.66 ppb) mean absolute error 0.17 ppb measurement accuracy 0.84%, best result date. More interestingly, capable achieving online FeNO, confirmed breath analysis.

Язык: Английский

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