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Modeling and optimization of biodiesel from high free‐fatty‐acid chicken fat by non‐catalytic esterification and mussel‐shell‐catalyzed transesterification
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Abstract<sec><title>BACKGROUND

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcination process at different calcination times of (1‐5) h and temperatures of (700‐900) °C. The catalyst was characterized using BET, SEM, EDX, XRD, and FTIR.

RESULTS

In the transesterification reaction, the best values of the studied parameters were: 21:1 methanol: oil molar ratio, 12 wt% catalyst loading, 5 h reaction time, and 63°C reaction temperature, which gave 96.2% methyl esters content. For catalyst synthesis, it was found that the optimum calcination conditions were 900 °C and 3 h, which resulted in a specific surface area of 10.5 m2/g and a large pore volume of 0.0033 cm3/g.

CONCLUSION

A calcium oxide catalyst was successfully prepared from mussel shells. This catalyst was used to transesterify the chicken fat into biodiesel. The prepared catalyst exhibited a high active surface area and a pore volume, confirming that the CaO catalyst produced from waste mussel shells worked effectively, steadily, and affordably to produce renewable biodiesel. The best working conditions for the transesterification reaction were determined using the central Composite Design method (CCD). © 2023 Society of Chemical Industry.

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Sun Oct 01 2023
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A novel data offloading scheme for QoS optimization in 5G based internet of medical things
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The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

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Sun Apr 29 2012
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Journal Of Karbala University
Optimization Quantitative Determination of Cimetidine in Pharmaceutical Preparations via Bromothymol Blue Using Central Composite Design
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Sun Oct 01 2017
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Optimization of Surface Roughness for Al-alloy in Electro-chemical Machining (ECM) using Taguchi Method
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Electro-chemical Machining is  significant  process to remove metal with using  anodic dissolution. Electro-chemical machining use to removed metal workpiece from (7025) aluminum alloy using Potassium chloride (KCl) solution .The tool used was made from copper. In this present the optimize processes input parameter use are( current, gap and electrolyte concentration) and surface roughness (Ra) as output .The experiments on electro-chemical machining with use current (30, 50, 70)A, gap (1.00, 1.25, 1.50) mm and electrolyte concentration (100, 200, 300) (g/L).  The method (ANOVA) was used to limited the large influence factors affected on surface roughness and found the current was the large influence f

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Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
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Theoretical and Experimental Study of Nanofiltration and Reverse Osmosis Membranes for Removal of Heavy Metals from Wastewater
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The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) membrane for heavy metal removal from wastewater and study the factors affecting the performance of these two membranes: feed concentrations for heavy metal ions, pressure, and flow rate. The experimental results showed, heavy metals concentration in permeate increase with raise in feed concentrations, decline with increase in flow rate. The raise of pressure, heavy metals concentration decreases for RO membrane, but for NF membrane the concentration decrease and then at high pressure increase. The rejection percentage for chromium in NF and RO is 99.7% and 99.9%, for copper is 98.4% and 99.3%, for zinc is 97.9% and 99.5%, for nickel is 97.2% and

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Synthesis and Characterization of New Metal Complexes of &#945;-Aminonitriles Derived from P- Toluidine and Aromatic Aldehydes
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