Photoluminescence and semiconducting behavior of Fe, Co, Ni and Cu implanted in heavy metal oxide glasses

Marzouk, M. A.; Abo-Naf, S. M.; Zayed, H. A.; Hassan, Nevien S.

doi:10.1016/j.jmrt.2015.11.003

Cited by 66 publications

(22 citation statements)

References 33 publications

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“…The high R 2 can be attributed to the very small size of the dataset. The results of ANNs gave satisfactory prediction performance with an R 2 of 0.84 using Tanh activation function in a previous study [ 15 ] employing a large dataset in case of combined glasses. The binary glass prediction to possess more accuracy than other glass refractive index prediction.…”

Section: Resultsmentioning

confidence: 67%

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Density of Bismuth Boro Zinc Glasses Using Machine Learning Techniques

Ahmed

Rajiya

Samee

et al. 2022

J Inorg Organomet Polym

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Machine learning techniques have been employed to predict the glass densities of xBi 2 O 3 –(70 − x)B 2 O 3 –20Li 2 O–5Sb 2 O 3 –5ZnO glasses using a data set of 2000 various B 2 O 3 rich glasses using their chemical composition and ionic radius. The experimental density of present glasses strongly depends on Bi 2 O 3 content which is increasing with bismuth content. The increasing density in bismuth doped glasses because the BO 3 are converted into BO 4 units, and besides BO 3 units are less heavy than the BO 4 units. The FTIR studies also confirm that the intensity of B–O–B bond decreasing with increasing Bi 2 O 3 content which suggested that B–O–B bond in bond ring isolated to BO 3 units transformed into BO 4 units. In Raman Spectra the stretching vibrations of BO 4 units shifting towards higher wavelengths with increasing Bi 2 O 3 content. This shifting conforms that there is a structural changes in the glass-matrix and borate units converting from BO 3 to BO 4 units. The prepared glasses along with B 2 O 3 rich glass data set train on various AI model such as gradient descent, Random Forest regression and Neural Networks to predict present density of glasses. Among the various models RF regression analysis model is successfully acceptable for the glass data with the highest R 2 value 0.983 which end result conform that the predicted and experimental values correlated. ANNs stood the effective technique in prediction of glass density with the optimum performance resulting with Tanh as the activation function (R 2 = 0.950). The minimum cost 0.018 obtained in the case of gradient decent function which also shows the better performance of regression model.

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Section: Resultsmentioning

confidence: 67%

“…To understand the elastic behavior of the glasses by using composition of the network like ceramic-materials were utilized to understand the glass pattern [ 14 ]. Several ML-models to measure the density precisely through composition-based parameters such as packing fraction and ionic radii to get least error were also reported [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Density of Bismuth Boro Zinc Glasses Using Machine Learning Techniques

Ahmed

Rajiya

Samee

et al. 2022

J Inorg Organomet Polym

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“…NPs have an absorption band at 343 nm in aqueous media (Figure 4). This peak is due to the absorption characteristic of d-shell electrons of Fe and Ni elements (Marzauk et al, 2016). The results show that NiFe 2 O 4 NPs absorbed light in the visible region due to the small energy bandgap (Rahmayeni et al, 2016).…”

Section: Resultsmentioning

confidence: 99%

Genotoxic analysis of nickel–iron oxide in Drosophila

Nas

Çolak

2020

Toxicol Ind Health

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It is known that nickel–iron oxide nanocomposite (NiFe2O4NP) is used in many important areas such as modern industry, biomedical applications, magnetic resonance imaging, construction of sensors, targeted drug treatment, and photoelectric devices in our life. In this study, we have carried out a genotoxic evaluation of NiFe2O4NP (30 nm) in Drosophila melanogaster by using the wing somatic mutation and recombination assay. For this purpose, third instar larvae carrying the recessive genes ( flr3) and multiple wing hairs ( mwh) in their third chromosomes were used. The larvae were fed at concentrations ranging from 25 µg/mL to 200 µg/mL. The genotoxic effects of NiFe2O4NPs were evaluated according to mutant trichomes resulting from genetic changes (mitotic recombination, deletion, point mutation, nondisjunction) on development of the wing imaginal discs. Mutant clone evaluations were performed based on small single spots, large single spots, and twin spots classifications. The results showed that significant increases were observed in the frequency of all spots, indicating that the highest concentration of nanoparticles was able to induce genotoxic activity in the wing spot assay of D. melanogaster.

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“…The intense and broad absorption bands at 619 nm for Co1, 707 nm for Co2 and 747 nm for Co5 in the sample spectra indicate the presence of the cobalt ions in tetrahedral or octahedral coordinations [31].…”

Section: Dr Uv-vis Spectroscopymentioning

confidence: 88%

“…4). Identification of the crystalline phases was performed by comparison to data from literature and those from the JCPDS data base [30,31]. The diffraction peaks at 2θ = 37, 46 and 67° might be attributed to gamma-alumina, while the ones at 2θ = 32, 37 and 60° confirm the presence of Co 3 O 4 .…”

Section: Energy Dispersive X-ray Analysis (Edax)mentioning

confidence: 99%

Synthesis, Characterization and Use of Supported Co/gama-Al2O3 for the Removal of Reactive Blue 19 from Aqueous Solutions

Larion¹,

Mureşan²,

Radu³

et al. 2018

Rev. Chim.

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In this study, systematic adsorption tests were carried out using Co/gama-Al2O3 adsorbents of different compositions for removal of Reactive Blue 19 dye from aqueous solutions. The adsorbent was characterized by scanning electron microscopy, X-Ray powder diffraction, diffuse reflectance UV-visible spectroscopy and EDX analysis. The influences of several parameters such as pH, adsorbent concentration, adsorption time and dye concentration on the adsorption capacity of g-Al2O3 and Co/g-Al2O3 were investigated. The obtained results indicate that the adsorption is strongly dependent on the solution pH. The maximum adsorption capacity of the Reactive blue 19 dye onto Co/gama-Al2O3 takes place at around pH 2. The adsorption process is fast in the first minutes (95% from the amount of dye being removed after 6 minutes).

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Photoluminescence and semiconducting behavior of Fe, Co, Ni and Cu implanted in heavy metal oxide glasses

Cited by 66 publications

References 33 publications

Density of Bismuth Boro Zinc Glasses Using Machine Learning Techniques

Density of Bismuth Boro Zinc Glasses Using Machine Learning Techniques

Genotoxic analysis of nickel–iron oxide in Drosophila

Synthesis, Characterization and Use of Supported Co/gama-Al2O3 for the Removal of Reactive Blue 19 from Aqueous Solutions

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