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Number of results: 4
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Abstract

Tires play an important role in the automobile industry. However, their disposal when worn out has adverse effects on the environment. The main aim of this study was to prepare activated carbon from waste tire pyrolysis char by impregnating KOH onto pyrolytic char. Adsorption studies on lead onto chemically activated carbon were carried out using response surface methodology. The effect of process parameters such as temperature (°C), adsorbent dosage (g/100 ml), pH, contact time (minutes) and initial lead concentration (mg/l) on the adsorption capacity were investigated. It was found out that the adsorption capacity increased with an increase in adsorbent dosage, contact time, pH, and decreased with an increase in lead concentration and temperature. Optimization of the process variables was done using a numerical optimization method. Fourier Transform Infrared Spectra (FTIR) analysis, X-ray Diffraction (XRD), Thermogravimetric analysis (TGA) and scanning electron microscope were used to characterize the pyrolytic carbon char before and after activation. The numerical optimization analysis results showed that the maximum adsorption capacity of

93.176 mg/g was obtained at adsorbent dosage of 0.97 g/100 ml, pH 7, contact time of 115.27 min, initial metal concentration of 100 mg/and temperature of 25°C. FTIR and TGA analysis showed the presence of oxygen containing functional groups on the surface of the activated carbon produced and that the weight loss during the activation step was negligible.

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Authors and Affiliations

Hilary Rutto
Tumisang Seidigeng
Lucky Malise
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Abstract

Optimal parameters setting of injection moulding (IM) machine critically effects productivity, quality, and cost production of end products in manufacturing industries. Previously, trial and error method were the most common method for the production engineers to meet the optimal process injection moulding parameter setting. Inappropriate injection moulding machine parameter settings can lead to poor production and quality of a product. Therefore, this study was purposefully carried out to overcome those uncertainty. This paper presents a statistical technique on the optimization of injection moulding process parameters through central composite design (CCD). In this study, an understanding of the injection moulding process and consequently its optimization is carried out by CCD based on three parameters (melt temperature, packing pressure, and cooling time) which influence the shrinkage and tensile strength of rice husk (RH) reinforced low density polyethylene (LDPE) composites. Statistical results and analysis are used to provide better interpretation of the experiment. The models are form from analysis of variance (ANOVA) method and the model passed the tests for normality and independence assumptions.
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Authors and Affiliations

Haliza Jaya
1 2
ORCID: ORCID
Nik Noriman Zulkepli
1 2
ORCID: ORCID
Mohd Firdaus Omar
1 2
ORCID: ORCID
Shayfull Zamree Abd Rahim
1 3
ORCID: ORCID
Marcin Nabiałek
4
ORCID: ORCID
Kinga Jeż
4
ORCID: ORCID
Mohd Mustafa Al Bakri Abdullah
1 2
ORCID: ORCID

  1. Universiti Malaysia Perlis, Centre of Excellence Geopolymer and Green Technology (CeGeoGTech), 02600 Arau, Perlis, Malaysia
  2. Universiti Malaysia Perlis (UniMAP), Faculty of Chemical Engineering Technology, Kompleks Pengajian Jejawi 2, 02600 Arau, Perlis, Malaysia
  3. Universiti Malaysia Perlis (UniMAP), Faculty of Mechanical Engineering Technology, Kampus Alam Pauh Putra, 02600 Arau, Perlis, Malaysia
  4. Częstochowa University of Technology, Department of Physics, 42-200 Częstochowa, Poland

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