Synthesis, defect characterization and photocatalytic degradation efficiency of Tb doped CuO nanoparticles

Devi, L. Vimala; Sellaiyan, S.; Selvalakshmi, T.; Zhang, Hongjun; Uedono, Akira; Sivaji, K.; Lee, Sejoon

doi:10.1016/j.apt.2017.09.013

Cited by 74 publications

(14 citation statements)

References 55 publications

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“…Insert Fig. 3 Foliar morphology is most commonly obtained for CuO by different synthesis methods, either by simple solution in low temperature agitation [34], by combustion of the solution [36], or by less conventional methods, such as microwave assisted hydrothermal [37] and sonochemical synthesis, as used in this work. According to Ringe et al [38],…”

Section: Resultsmentioning

confidence: 99%

Influence of pH on the morphology and photocatalytic activity of CuO obtained by the sonochemical method using different surfactants

Neto

Oliveira

Nascimento

et al. 2019

Ceramics International

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Section: Resultsmentioning

confidence: 99%

Influence of pH on the morphology and photocatalytic activity of CuO obtained by the sonochemical method using different surfactants

Neto

Oliveira

Nascimento

et al. 2019

Ceramics International

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“…Hence, the need for nonlinear modeling tool becomes essential. Doping of CuO semiconductor results into absorption range blue shift exhibition which influences the semiconductor energy gap due to defect formation in the crystal lattice where photons are scattered [29]. This physically justified relationship between CuO lattice parameters and the energy gap is well captured through the developed model in this work.…”

Section: Description Of Data Acquisition and Data Sourcementioning

confidence: 52%

“…Modeling of energy gap of doped CuO semiconductors was carried out using fifty-seven samples of the semiconductor as extracted from the literature [8,10,11,[29][30][31][32][33][34][35][36][37]. The lattice parameters of the semiconducting samples after dopant incorporation serve as the model inputs.…”

Section: Description Of Data Acquisition and Data Sourcementioning

confidence: 99%

Engineering the Energy Gap of Cupric Oxide Nanomaterial Using Extreme Learning Machine and Stepwise Regression Algorithms

Alqahtani

2021

Journal of Nanomaterials

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CuO is a narrow band gap semiconductor with distinct features that render it indispensable in many industrial and technological applications such as environmental friendly catalysts for organic pollutant removal, sensors, photovoltaic, solar cells, batteries, and storage media among others. Engineering of its energy gap becomes imperative and necessary for tailoring its light absorption capacity to a desired level required for a particular application. Elemental doping mechanisms with accompanied lattice distortion symmetry breaking effectively enhance the optical property of this semiconductor and serve as a major route through which material design is achieved. This work develops an extreme learning machine intelligent predictive (ELM-IP) model and stepwise regression (SWR) based model for estimating energy gap of a doped CuO semiconductor. The developed ELM-IP-Sin model which employs sine activation function performs better than the ELM-IP-Sig model (that utilizes sigmoid activation function) and SWR model with a percentage improvement of 14.15% and 50.05%, respectively, using root mean square error (RMSE) metric, while the developed ELM-IP-Sig model outperforms the SWR-based model. The developed models further investigate the dependence of CuO energy gap on iron and cobalt impurity incorporation, and the obtained results agree well with measured values. The outstanding performance of the developed models is highly meritorious in tailoring the light response capacity of CuO semiconductor for photocatalytic and optoelectronics applications at a reduced cost while the experimental stress is circumvented.

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“…Vimala devi et.al. reported the effect of annealing and doping on the structural and optical properties of monoclinic undoped and Tb doped CuO [13]. The doping indicates the formation of single-phase monoclinic structure and also confirmed that Fe ions successfully incorporated into CuO crystal lattice by occupying Cu ionic sites [14].…”

Section: Introductionmentioning

confidence: 92%

Structural and optical property studies on Fe doped CuO nanoparticles

M¹,

Vijayaraj²

2022

World J. Adv. Res. Rev.

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The Cupric oxide (CuO) nanostructures and Fe doped CuO nanomaterials are synthesized by microwave irradiation method. The effect of Fe doping on the crystal structure, band gap and optical properties of synthesized samples were characterized by using x-ray diffraction, ultraviolet-visible spectrometer, photoluminescence spectrometer and Fourier transform infrared spectrometer. X-ray diffraction study confirms the size of the particle in nanometer. The optical band gap calculated from UV–Vis absorption spectrum, reveals the change in band gap energy due to the presence of dopants. The photoluminescence spectrum suggests that Fe doped CuO nanoparticles may be used in optoelectronic devices. The functional group analysis carried out by Fourier transform infrared spectroscopy confirmed the substitution of Fe in the samples.

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Synthesis, defect characterization and photocatalytic degradation efficiency of Tb doped CuO nanoparticles

Cited by 74 publications

References 55 publications

Influence of pH on the morphology and photocatalytic activity of CuO obtained by the sonochemical method using different surfactants

Influence of pH on the morphology and photocatalytic activity of CuO obtained by the sonochemical method using different surfactants

Engineering the Energy Gap of Cupric Oxide Nanomaterial Using Extreme Learning Machine and Stepwise Regression Algorithms

Structural and optical property studies on Fe doped CuO nanoparticles

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