Semiconductor-based photocatalytic processes are widely applied as ecofriendly technology for degrading organic pollutants. Establishing photocatalytic heterojunctions with Z-type photocarriers transfer pathways is projected to be a superb strategy to enhance photocatalytic behavior. In this paper, novel and stable (0D/2D) heterojunctions of CoS-embedded boron-doped g-C3N4 (CoS/BCN) with a high rate of charges transfer/separation were assembled for degradation of malachite green dye (MG). The CoS/BCN photocatalyst achieves a photodegradation efficiency of 96.9 % within 1 h of LED illumination, which is 2.5 and 1.4-fold enhancement compared with bare g-C3N4 and BCN, respectively. Besides, the results of species-trapping trials exhibited that •O2 and at a lower degree, photogenerated holes were mainly in charge of the boosted performance. In light of the above results of the trapping experiments, the charge transfer mechanism was discussed, and the Z-form heterojunction between BCN and CoS was taken as the reason for enhancing the photocatalytic efficiency. The stability of the CoS/BCN hybrid was also checked, showing excellent photostability performance after five degradation rounds.
The corrosion behavior of low carbon steel in washing water of crude oil solution has been studied potentiostatically at five temperatures in the range (30–70)°C .The corrosion potential shifted to more negative values with increasing temperature and the corrosion current density increased with increasing temperature. Folic acid had on inhibiting effect on the corrosion of low carbon steel in washing water at a concentration (5× 10-4-- 5× 10-3 ) mol/dm3 over the temperature range (30–70)°C. Values of the protection efficiency were calculated from the corrosion current density .From the general results for this study, it can be seen that thermodynamic and kinetic function were also calculated (?G, ?S, ?H and Ea )
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreA field study was conducted at the college of Agriculture, Baghdad University-Jadiriyah to investigate the effect of adding potassium fertilizer and organic nutrient (Reef Amirich) on the population density of two sucking pests of cucumber, cotton whitefly, Bemisia tabaci and onion thrips, Thrips tabaci during the spring season/2016. Results indicated that potassium sulphate (50, 100 and 150 kg/ha) and organic nutrient (0.8 and 1.6ml/l) reduced both the population density of B. tabaci and T. tabaci nymphs depending on the fertilizer level of the user, the treatment 150 kg/ha for the potassium fertilizer and 1.6 ml/L for organic nutrient was the highest among others when minimized density of nymphs by 1.62 nymphs of B. tabaci/disk leaf and 0
... Show MoreThis research aimed to predict the permanent deformation (rutting) in conventional and rubberized asphalt mixes under repeated load conditions using the Finite Element Method (FEM). A three-dimensional (3D) model was developed to simulate the Wheel Track Testing (WTT) loading. The study was conducted using the Abaqus/Standard finite element software. The pavement slab was simulated using a nonlinear creep (time-hardening) model at 40°C. The responses of the viscoplastic model under the influence of the trapezoidal amplitude of moving wheel loadings were determined for different speeds and numbers of cycles. The results indicated that a wheel speed increase from 0.5Km/h to 1.0Km/h decreased the rut depth by about 22% and 24% in conv
... Show MoreThis paper studies the combination of fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. This optimizes the accuracy of the dynamic response and by providing higher level of damping, basically minimizes the wanted stiffness of the structure while at the same time optimizing the achievement.
The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximu
... Show MoreReducing a structure’s self-weight is the main goal and a major challenge for most civil constructions, especially in tall buildings and earthquake-affected buildings. One of the most adopted techniques to reduce the self-weight of concrete structures is applying voids in certain positions through the structure, just like a voided slab or BubbleDeck slab. This research aims to study, experimentally and theoretically, the structural behavior of BubbleDeck reinforced concrete slabs under the effect of harmonic load. Tow-way BubbleDeck slab of 2500mm×2500m×200mm dimensions and uniformly distributed bubbles of 120mm diameter and 160mm spacing c/c was tested experimentally under the effect of harmonic load. Numerical analysis was als
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