The present work reports the synthesis, characterization, photoluminescence and photocatalytic activity of Eu^(3+)(1 mol%-11 mol%) doped and Li^+(0.5 mol%-5 mol%) co-doped Bi_2 O_3 nanophosphors(NPs) by sonochemical m...The present work reports the synthesis, characterization, photoluminescence and photocatalytic activity of Eu^(3+)(1 mol%-11 mol%) doped and Li^+(0.5 mol%-5 mol%) co-doped Bi_2 O_3 nanophosphors(NPs) by sonochemical method. The average particle size was estimated using powder X-ray diffraction(PXRD)and transmission electron microscopy(TEM) and is found to be in the range of 30-35 nm. The scanning electron microscopy(SEM) images were highly dependent on sonication time and concentration of epigallocatechin gallate(EGCG) bio-surfactant. The energy gap of doped and co-doped Bi_2 O_3 nanophosphors was estimated using Kubelka-Munk(K-M) function and is found to be in the range of2.9-3.08 eV. The effect of Li+ co-doping on luminescence of optimized Bi_2 O_3:Eu^(3+) was studied and is found about more than 3 fold enhancement of emission intensity. Judd-Ofelt parameters(Ω_2, Ω_4 and Ω_6).transition probabilities(A_T), quantum efficiency(η), luminescence lifetime(τ_(rad)), color chromaticity coordinates(CIE) and correlated color temperature(CCT) values were estimated from the emission spectra and are discussed in detail. The estimated CIE chromaticity co-ordinates are very close to the NTSC(National Television Standard Committee) standard value of red emission. The synthesized NPs show excellent photocatalytic activity of acid red-88 under UV-light irradiation, which can degrade 98.1% in60 min. The decreasing electron-hole pair recombination rate with quick electron transfer ability is predominantly ascribed to the balance between crystallite size, morphology, band gap, defects, surface area, etc. These results show a light for the use of sonochemical route of Bi_2 O_3:Eu^(3+):Li^+ in solid state display and photocatalytic applications.展开更多
Increase in the use of internet of things owned devices is one of the reasonsforincreasednetworktraffic.Whileconnectingthesmartdeviceswith publicly available network many kinds of phishing attacks are able to enter in...Increase in the use of internet of things owned devices is one of the reasonsforincreasednetworktraffic.Whileconnectingthesmartdeviceswith publicly available network many kinds of phishing attacks are able to enter into the mobile devices and corrupt the existing system.The Phishing is the slow and resilient attack stacking techniques probe the users.The proposed model is focused on detecting phishing attacks in internet of things enabled devices through a robust algorithm called Novel Watch and Trap Algorithm(NWAT).Though Predictive mapping,Predictive Validation and Predictive analysis mechanism is developed.For the test purpose Canadian Institute of cyber security(CIC)dataset is used for creating a robust prediction model.This attack generates a resilience corruption works that slowly gathers the credential information from the mobiles.The proposed Predictive analysis model(PAM)enabled NWAT algorithm is used to predict the phishing probes in the form of suspicious process happening in the IoT networks.The prediction system considers the peer-to-peer communication window open for the established communication,the suspicious process and its pattern is identified by the new approach.The proposed model is validated by finding thepredictionaccuracy,Precision,recallsF1score,errorrate,Mathew’sCorre-lationCoefficient(MCC)andBalancedDetectionRate(BDR).Thepresented approach is comparatively analyzed with the state-of-the-art approach of existing system related to various types of Phishing probes.展开更多
基金supported by VGST,Govt.of Karnataka,India(VGST/K-FIST-L1/2016-17/GRD-360)
文摘The present work reports the synthesis, characterization, photoluminescence and photocatalytic activity of Eu^(3+)(1 mol%-11 mol%) doped and Li^+(0.5 mol%-5 mol%) co-doped Bi_2 O_3 nanophosphors(NPs) by sonochemical method. The average particle size was estimated using powder X-ray diffraction(PXRD)and transmission electron microscopy(TEM) and is found to be in the range of 30-35 nm. The scanning electron microscopy(SEM) images were highly dependent on sonication time and concentration of epigallocatechin gallate(EGCG) bio-surfactant. The energy gap of doped and co-doped Bi_2 O_3 nanophosphors was estimated using Kubelka-Munk(K-M) function and is found to be in the range of2.9-3.08 eV. The effect of Li+ co-doping on luminescence of optimized Bi_2 O_3:Eu^(3+) was studied and is found about more than 3 fold enhancement of emission intensity. Judd-Ofelt parameters(Ω_2, Ω_4 and Ω_6).transition probabilities(A_T), quantum efficiency(η), luminescence lifetime(τ_(rad)), color chromaticity coordinates(CIE) and correlated color temperature(CCT) values were estimated from the emission spectra and are discussed in detail. The estimated CIE chromaticity co-ordinates are very close to the NTSC(National Television Standard Committee) standard value of red emission. The synthesized NPs show excellent photocatalytic activity of acid red-88 under UV-light irradiation, which can degrade 98.1% in60 min. The decreasing electron-hole pair recombination rate with quick electron transfer ability is predominantly ascribed to the balance between crystallite size, morphology, band gap, defects, surface area, etc. These results show a light for the use of sonochemical route of Bi_2 O_3:Eu^(3+):Li^+ in solid state display and photocatalytic applications.
文摘Increase in the use of internet of things owned devices is one of the reasonsforincreasednetworktraffic.Whileconnectingthesmartdeviceswith publicly available network many kinds of phishing attacks are able to enter into the mobile devices and corrupt the existing system.The Phishing is the slow and resilient attack stacking techniques probe the users.The proposed model is focused on detecting phishing attacks in internet of things enabled devices through a robust algorithm called Novel Watch and Trap Algorithm(NWAT).Though Predictive mapping,Predictive Validation and Predictive analysis mechanism is developed.For the test purpose Canadian Institute of cyber security(CIC)dataset is used for creating a robust prediction model.This attack generates a resilience corruption works that slowly gathers the credential information from the mobiles.The proposed Predictive analysis model(PAM)enabled NWAT algorithm is used to predict the phishing probes in the form of suspicious process happening in the IoT networks.The prediction system considers the peer-to-peer communication window open for the established communication,the suspicious process and its pattern is identified by the new approach.The proposed model is validated by finding thepredictionaccuracy,Precision,recallsF1score,errorrate,Mathew’sCorre-lationCoefficient(MCC)andBalancedDetectionRate(BDR).Thepresented approach is comparatively analyzed with the state-of-the-art approach of existing system related to various types of Phishing probes.
