Nanostructured photodetectors have garnered great attention due to their enriched electronic and optical properties. In this work, we aim to fabricate a high-performance CeO2/Si photodetector by growing a CeO2 nanostructure film on a silicon substrate using the pulsed laser deposition (PLD) technique at different laser energy densities. The impact of laser energy density and the number of pulses on the morphological, optical, and electrical properties was studied. Field emission scanning electron microscopy (FESEM) results show that the CeO2 film has a spherical grain morphology with an average grain size ranging from 33 to 54 nm, depending on the laser energy density. The film deposited at various numbers of laser pulses also has spherical grains with an average grain size ranging from 39 to 54 nm, depending on the number of pulses. The optical properties of the CeO2 film showed that the optical energy gap of the films decreased from 3.5 to 3 eV as the laser energy density increased from 63.66 to 101.86 J/cm2. The photoluminescence (PL) spectra of the nanostructured CeO2 film reveal that the main emission peaks were observed at 682 nm when excited at 450 nm. The effect of laser energy density on the electrical properties, including carrier concentration, mobility, and current-voltage characteristics under dark and illuminated conditions, was investigated. The CeO2/Si photodetector fabricated at 63.66 J/cm2 showed the highest responsivity of 0.69 A/W at 450 nm, detectivity as high as 1.5 × 1010 Jones at 450 nm, and an external quantum efficiency of 92% when biased to 5 V. The photodynamic response time was measured
APDBN Rashid, Review of International Geographical Education Online (RIGEO), 2021
The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.
The impregnation method is used in test sample preparation, using molding by pressure presses.
All samples were exposure to (Co60) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.
The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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