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Adsorption of bimetal from aqueous solution on plum seed activated carbon synthesized by pyrocarbonic acid microwave method
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Abstract<sec><title>BACKGROUND

This article presents the simultaneous adsorption of bimetal Cu2+ and Zn2+ from an aqueous solution using activated carbon synthesized from a plum seed precursor by sulfuric acid and microwave activation: plum seeds chemically activated by 45% (w/w) sulfuric acid with 2:1 ratio for 4 h, then carbonized for 2 h at 700 °C and the product obtained activated in a microwave oven for 20 min at 700 W for final of activation. Plum seeds and activated carbon produced were characterized in terms of their physical and chemical composition using Brunauer–Emmett–Teller measurements, field emission scanning electron microscopy and Fourier transform infrared spectroscopy. The effects of absorption time, bimetal solution pH, bimetal concentration and dosage of activated carbon on the capacity of adsorption and removal efficiency were studied with Design‐Expert software using response surface methodology with the I‐optimal method for experimental data analysis.

RESULTS

The results showed that the statistical analysis of Cu2+ and Zn2+ removal efficiency followed the quadratic models generated by Design‐Expert software with significant P value (P < 0.0001) and the optimum values of removal efficiencies were 99.9268% for Cu2+ and 99.34% for Zn2+ at an adsorption time of 4.98 h, pH of 7.94, bimetal concentration of 38.467 mg L−1 and adsorbent dose of 1485.294 mg (100 mL)−1. The equilibrium adsorption data were analyzed by Langmuir and Freundlich isotherm models and there was a significant agreement in the results with the Freundlich model with R2 = 0.9841 for Cu2+ and R2 = 0.9927 for Zn2+. Likewise, the data were found to fit with a pseudo‐second‐order model with R2 = 0.9989 for Cu2+ and R2 = 0.9948 for Zn2+ as compared to a pseudo‐first‐order model.

CONCLUSION

Activated carbon synthesized from plum seeds with chemical and microwave activation could be effectively used as an adsorbent for bimetal Cu2+ and Zn2+ in aqueous solution. © 2024 Society of Chemical Industry (SCI).

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Biogenic selenium nanoparticles by probiotics streptococcus salivarius and effect on oprM gene expression from Pseudomonas aeruginosa
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Delamination Detection in Glass-Fibre Reinforced Polymer (GFRP) Using Microwave Time Domain Reflectometry
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Wed May 06 2015
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16th Conference In Natural Science And Mathematics
Efficient digital Image filtering method based on fuzzy algorithm
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Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

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Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Enhancing the human resources quality by adopting an adventure learning method in their development
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The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

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Spectrophotometric Analytical method for Determination the Drug Compound Salbutamol by using Prussian blue Complex
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This research aims to develop new spectrophotometric analytical method to determine drug compound Salbutamol by reaction it with ferric chloride in presence potassium ferricyanide in acid median to formation of Prussian blue complex to determine it by uv-vis spectrophotmetric at wavelengths rang(700-750)nm . Study the optimal experimental condition for determination drug and found the follows: 1- Volume of(10M) H2SO4 to determine of drug is 1.5 ml . 2- Volume and concentration of K3Fe(CN)6 is 1.5 ml ,0.2% . 3- Volume and concentration of FeCl3 is 2.5ml , 0.2%. 4- Temperature has been found 80 . 5- Reaction time is 15 minute . 6- Order of addition is (drug + K3Fe(CN)6+ FeCl3 + acid) . Concentration rang (0.025-5 ppm) , limit detecti

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interaction of L-Threonine in aqueous THFA and in mixed aqueous solutions at 298.15 K
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