Arwa Abdelhay

Adsorption of copper ions from water by different types of natural seed materials

AbstractDifferent plant seeds of okra, pumpkin, grape, and squash available locally were used as adsorbents for the removal of copper ions from their aqueous solutions. Batch sorption experiments were carried out to investigate the seeds’ capability to remove copper ions. Grape seeds showed higher uptake compared with other adsorbents. Experimental results for grape seeds showed that an increase in the initial pH, temperature, or initial adsorbate concentration influenced copper uptake positively. However, copper ion uptake decreased with increasing adsorbent concentration. The optimum pH range for metals removal was 3–4. Addition of sodium or potassium salts to the metal solution resulted in greater metal removal. The copper equilibrium was attained after 3 h contact time. The uptake of Cu+2 were found to be reliable on both the Freundlich and Langmuir isotherms. The results of work will urge the public to use these tested seeds in their diet for possible removal of heavy metals that contaminate either f...

Kinetic and thermodynamic study of phosphate removal from water by adsorption onto (Arundo donax) reeds

The adsorption of phosphate ion onto natural reed (Arundo donax) was studied in this work. The effect of phosphate initial concentration, adsorbent dose, pH, temperature, and salt addition on adsorption uptake was investigated. The results showed that the adsorption uptake is directly proportional to the phosphate ion initial concentration and inversely proportional to the adsorbents dose and temperature. A maximum adsorption capacity of 16.2 mg/g was observed at neutral pH. The addition of sodium and potassium chlorides has decreased the adsorption uptake. The adsorption isotherms agree better with the Langmuir model. The negative values of (ΔG) and (ΔH) obtained from the thermodynamic study, indicted that the adsorption process is spontaneous and exothermic. The experimental adsorption data were analyzed using three kinetic models: pseudo-first order, pseudo-second order, and intra-particle diffusion model. The pseudo-second-order model presented the best fit with a determination coefficient (R2) higher than 0.99 and a minimum normalized standard deviation.

Adsorption-Based Model for Single-Wall Carbon Nanotube Response to NO2 Gas

In this work, the response of single-wall carbon nanotube as a resistive NO2 sensor was investigated. A model was developed based on the Freundlich adsorption isotherm and a multi-exponential function was used to describe the relationship between the sensor response and the gas concentration. The model predicts both static and dynamic responses in a closed sampling system. In addition, the model considers the effect of different variables such as the operating temperature, NO2 concentration in air and the two phases (adsorption and desorption) of response. The developed model is in good accordance with the experimental data. This model could be used to design new environmental detection devices and interpret experimental data by providing some insight into the sensor behaviour during the transient phase.

Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree

This paper presents an accurate nonlinear classification method that can help physicians diagnose seizure in electroencephalographic (EEG) signal characterized by a disturbance in temporal and spectral content. This is accomplished by applying four steps. First, different EEG signals containing healthy, ictal and seizure-free (inter-ictal) activities are decomposed by empirical mode decomposition method. The instantaneous amplitudes and frequencies of resulted bands (intrinsic mode functions, IMF) are then tracked by the direct quadrature method (DQ). In contrast to other approaches, DQ cancels the effect of amplitude modulation on frequency calculation. The dissociation between instantaneous amplitude and frequency information is therefore fully achieved to avoid features confusion. Afterwards, the Shannon entropy values of both sets of instantaneous values (amplitudes and frequencies)—related to every IMF—are calculated. Finally, the obtained entropy values are classified by random forest tree. The proposed procedure yields 100% accuracy for (healthy)/(ictal) and 98.3–99.7% for (healthy)/(ictal)/(interictal) classification problems. The suggested method is hence robust, accurate, fast, user-friendly, data driven with open access interpretability.

Veratric acid removal from water by electrochemical oxidation on BDD anode

The efficiency of boron doped diamond (BDD) in the electrochemical treatment of synthetically contaminated water with veratric acid (VA), one kind of polyphenolic type compounds, is investigated in this work. A BDD electrode was practically fabricated using hot filament chemical vapor deposition (HFCVD). Later on, the BDD electrode was implemented as an anode in a batch electrolytic reactor. The effect of operating factors such as the initial concentration of VA, NaCl addition, and supporting electrolyte type (H2SO4, H3PO4 and Na2SO4) was studied. The chemical oxygen demand (COD) measurements were conducted to study the VA electrolysis kinetics. The experimental data suggested that sodium sulfate was the best supporting electrolyte as the COD removal reached a percentage of 100% using 1 mmol/dm3 as VA concentration. The kinetics of the COD decay of the VA electrolysis were found to obey the pseudo-first order model. Remarkably, the electrolysis process is significantly speeded up once chloride is added to the reaction. The complete COD removal was achieved in 60 minutes of treatment.

Anodic oxidation of slaughterhouse wastewater on boron-doped diamond: process variables effect

A non-sacrificial boron-doped diamond electrode was prepared in the laboratory and used as a novel anode for electrochemical oxidation of poultry slaughterhouse wastewater. This wastewater poses environmental threats as it is characterized by a high content of recalcitrant organics. The influence of several process variables, applied current density, initial pH, supporting electrolyte nature, and concentration of electrocoagulant, on chemical oxygen demand (COD) removal, color removal, and turbidity removal was investigated. Results showed that raising the applied current density to 3.83 mA/cm2 has a positive effect on COD removal, color removal, and turbidity removal. These parameters increased to 100%, 90%, and 80% respectively. A low pH of 5 favored oxidants generation and consequently increased the COD removal percentage to reach 100%. Complete removal of COD had occurred in the presence of NaCl (1%) as supporting electrolyte. Na2SO4 demonstrated lower efficiency than NaCl in terms of COD removal. The COD decay kinetics follows the pseudo-first-order reaction. The simultaneous use of Na2SO4 and FeCl3 decreased the turbidity in wastewater by 98% due to electrocoagulation.

Non-Linear Modeling of the Dynamic Response of Single-Wall Carbon Nanotube SWNT Composites to NO2 Gas in Air

The objective of this study is to develop a mathematical model, which can describe the response of a single-wall carbon nanotube (SWNT) as a resistive NO2 sensor, based on the acquired experimental data. The obtained non-linear regression attempts to simulate and predict the sensor response taking into account the effect of different variables such as NO2 concentration and operating temperature. The results show that the developed mathematical equation expresses the sensor response as a function of time, gas concentration, and temperature with an R-squared value ranging between 0.65 and 0.97.