Comparative study of photocatalysis and gas sensing of ZnO/Ag nanocomposites synthesized by one- and two-step polymer-network gel processes

Liu, Y.; Zhang, Q.; Yuan, Huan; Luo, Kaiyi; Li, J.; Hu, Wenyu; Pan, Zhibin; Xu, Ming; Xu, Shuyan; Levchenko, Igor; Bazaka, Kateryna

doi:10.1016/j.jallcom.2021.158723

Cited by 84 publications

(26 citation statements)

References 58 publications

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“…The intrinsic UV emission originated from excitonic recombination of near-band edge (NBE) electrons (at conduction band bottom) and holes (at valence band top). 71 , 72 In Figure 5 b, commercial ZnO (green curve) displayed a sharp and narrow UV emission peak centered at 380 nm, through which we could calculate its band gap to be 3.26 eV, 20 , 73 very approaching the 3.37 eV of intrinsic ZnO. Correspondingly, the NBE emission peak of V O -rich ZnO (red curve) became weaker and broader, also showing a red shift to a larger wavelength of 393 nm, which corresponded to a band gap of 3.16 eV.…”

Section: Resultsmentioning

confidence: 99%

Visible Light-Induced Room-Temperature Formaldehyde Gas Sensor Based on Porous Three-Dimensional ZnO Nanorod Clusters with Rich Oxygen Vacancies

et al. 2022

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Oxygen vacancy (V O ) is a kind of primary point defect that extensively exists in semiconductor metal oxides (SMOs). Owing to some of its inherent qualities, an artificial manipulation of V O content in one material has evolved into a hot research field, which is deemed to be capable of modulating band structures and surface characteristics of SMOs. Specific to the gas-sensing area, V O engineering of sensing materials has become an effective means in enhancing sensor response and inducing light-enhanced sensing. In this work, a high-efficiency microwave hydrothermal treatment was utilized to prepare a V O -rich ZnO sample without additional reagents. The X-ray photoelectron spectroscopy test revealed a significant increase in V O proportion, which was from 9.21% in commercial ZnO to 36.27% in synthesized V O -rich ZnO possessing three-dimensional and air-permeable microstructures. The subsequent UV–vis–NIR absorption and photoluminescence spectroscopy indicated an extension absorption in the visible region and band gap reduction of V O -rich ZnO. It turned out that the V O -rich ZnO-based sensor exhibited a considerable response of 63% toward 1 ppm HCHO at room temperature (RT, 25 °C) under visible light irradiation. Particularly, the response/recovery time was only 32/20 s for 1 ppm HCHO and further shortened to 10/5 s for 10 ppm HCHO, which was an excellent performance and comparable to most sensors working at high temperatures. The results in this work strongly suggested the availability of V O engineering and also provided a meaningful candidate for researchers to develop high-performance RT sensors detecting volatile organic compounds.

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Section: Resultsmentioning

confidence: 99%

Visible Light-Induced Room-Temperature Formaldehyde Gas Sensor Based on Porous Three-Dimensional ZnO Nanorod Clusters with Rich Oxygen Vacancies

et al. 2022

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“…However, methods of synthesizing alloy nanoparticles can also be classified into physical, chemical, and biological approaches [ 27 , 28 ]. Different researches demonstrated Ag/ZnO NP synthesis physically and chemically such as sonochemical precipitation [ 29 – 31 ], radiolytic preparation [ 32 , 33 ], coprecipitation method [ 34 ], low-temperature synthesis [ 35 ], solvothermal synthesis [ 36 , 37 ], polymer-network gel process [ 38 ], and combustion synthesis [ 39 ]. These methodologies have been progressively more unlikely in terms of safety and noxiousness matters.…”

Section: The Followed Means Of Plant-derived Ag/zno Alloy Np Synthesismentioning

confidence: 99%

Plant-Based Bimetallic Silver-Zinc Oxide Nanoparticles: A Comprehensive Perspective of Synthesis, Biomedical Applications, and Future Trends

Ehsan

Waheed

Ullah

et al. 2022

BioMed Research International

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The universal emphasis on the study of green nanotechnology has led to biologically harmless uses of wide-ranged nanomaterials. Nanotechnology deals with the production of nanosized particles with regular morphology and properties. Various researches have been directed on nanomaterial synthesis by physical, chemical, and biological means. Understanding the safety of both environment and in vivo, a biogenic approach particularly plant-derived synthesis is the best strategy. Silver-zinc oxide nanoparticles are most effective. Moreover, these engineered nanomaterials via morphological modifications attain improved performance in antimicrobial, biomedical, environmental, and therapeutic applications. This article evaluates manufacturing strategies for silver-zinc oxide nanoparticles via plant-derived means along with highlighting their broad range of uses in bionanotechnology.

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“…Although PLLA has relatively satisfactory mechanical characteristics, its crystallization rate is slow. Hence, the fabrication of composites [ 9 ] based on PLLA with a better crystallization behavior has been suggested [ 10 , 11 , 12 ]. Chen et al synthesized several completely biodegradable PLLA-based composites by dispersing polyglycolide (PGA) fibers in the PLLA body [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Estimating the Relative Crystallinity of Biodegradable Polylactic Acid and Polyglycolide Polymer Composites by Machine Learning Methodologies

et al. 2022

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Biodegradable polymers have recently found significant applications in pharmaceutics processing and drug release/delivery. Composites based on poly (L-lactic acid) (PLLA) have been suggested to enhance the crystallization rate and relative crystallinity of pure PLLA polymers. Despite the large amount of experimental research that has taken place to date, the theoretical aspects of relative crystallinity have not been comprehensively investigated. Therefore, this research uses machine learning methods to estimate the relative crystallinity of biodegradable PLLA/PGA (polyglycolide) composites. Six different artificial intelligent classes were employed to estimate the relative crystallinity of PLLA/PGA polymer composites as a function of crystallization time, temperature, and PGA content. Cumulatively, 1510 machine learning topologies, including 200 multilayer perceptron neural networks, 200 cascade feedforward neural networks (CFFNN), 160 recurrent neural networks, 800 adaptive neuro-fuzzy inference systems, and 150 least-squares support vector regressions, were developed, and their prediction accuracy compared. The modeling results show that a single hidden layer CFFNN with 9 neurons is the most accurate method for estimating 431 experimentally measured datasets. This model predicts an experimental database with an average absolute percentage difference of 8.84%, root mean squared errors of 4.67%, and correlation coefficient (R2) of 0.999008. The modeling results and relevancy studies show that relative crystallinity increases based on the PGA content and crystallization time. Furthermore, the effect of temperature on relative crystallinity is too complex to be easily explained.

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Comparative study of photocatalysis and gas sensing of ZnO/Ag nanocomposites synthesized by one- and two-step polymer-network gel processes

Cited by 84 publications

References 58 publications

Visible Light-Induced Room-Temperature Formaldehyde Gas Sensor Based on Porous Three-Dimensional ZnO Nanorod Clusters with Rich Oxygen Vacancies

Visible Light-Induced Room-Temperature Formaldehyde Gas Sensor Based on Porous Three-Dimensional ZnO Nanorod Clusters with Rich Oxygen Vacancies

Plant-Based Bimetallic Silver-Zinc Oxide Nanoparticles: A Comprehensive Perspective of Synthesis, Biomedical Applications, and Future Trends

Estimating the Relative Crystallinity of Biodegradable Polylactic Acid and Polyglycolide Polymer Composites by Machine Learning Methodologies

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