Carbonization and CO<Subscript>2</Subscript> activation of scrap tires: Optimization of specific surface area by the Taguchi method

This research demonstrates the production of activated carbon from scrap tires via physical activation with carbon dioxide. A newly constructed apparatus was utilized for uninterrupted carbonization and activation processes. Taguchi experimental design (L16) was applied to conduct the experiments at different levels by altering six operating parameters. Carbonization temperature (550–700 °C), activation temperature (800–950 °C), process duration (30–120 min), CO₂ flow rate (400 and 600 cc/min) and heating rate (5 and 10 °C/min) were the variables examined in this study. The effect of parameters on the specific surface area (SSA) of activated carbon was studied, and the influential parameters were identified employing analysis of variance (ANOVA). The optimum conditions for maximum SSA were: carbonization temperature=650 °C, carbonization time=60 min, heating rate=5 °C/min, activation temperature= 900 °C, activation time=60 min and CO₂ flow rate=400 cc/min. The most effective parameter was activation temperature with an estimated impact of 49%. The activated carbon produced under optimum conditions was characterized by pore and surface structure analysis, iodine adsorption test, ash content, scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The process yield for optimized activated carbon was 13.2% with the following properties: specific surface area=437 m²/g, total pore volume=0.353 cc/g, iodine number=404.7 mg/g and ash content=13.9% along with an amorphous structure and a lot of oxygen functional groups. These properties are comparable to those of commercial activated carbons.     

Causal inference for time series analysis: problems,methods and evaluation

Knowledge and Information Systems - Time series data are a collection of chronological observations which are generated by several domains such as medical and financial fields. Over the years,...     

Gap-based estimation: choosing the smoothing parameters for probabilistic and general regression neural networks

Probabilistic neural networks (PNN) and general regression neural networks (GRNN) represent knowledge by simple but interpretable models that approximate the optimal classifier or predictor in the sense of expected value of the accuracy. These models require the specification of an important smoothing parameter, which is usually chosen by cross-validation or clustering. In this article, we demonstrate the problems with the cross-validation and clustering approaches to specify the smoothing parameter, discuss the relationship between this parameter and some of the data statistics, and attempt to develop a fast approach to determine the optimal value of this parameter. Finally, through experimentation, we show that our approach, referred to as a gap-based estimation approach, is superior in speed to the compared approaches, including support vector machine, and yields good and stable accuracy.     

Conversion of Poly(Ethylene Terephthalate) Waste into Activated Carbon: Chemical Activation and Characterization

Due to its high carbon content, low impurities, low cost and easy availability, poly(ethylene terephthalate) (PET) waste is considered as a suitable precursor for the production of activated carbon. The chemical activation of PET wastes using different chemical agents such as H₃PO₄, H₂SO₄, ZnCl₂, and KOH was investigated. KOH‐ and ZnCl₂‐activated PET were found to be the best choices for the adsorption of small and large molecules. The capacities of the adsorbents towards I₂, methylene blue, N₂, CH₄, and CO₂ followed the order KOH‐PET >H₃PO₄‐PET > ZnCl₂‐PET > H₂SO₄‐PET; however, in the molasses uptake and selective adsorption of CO₂ compared to CH₄, ZnCl₂‐PET performed better than the other adsorbents.     

An automated approach for planning mass tactical airborne operations

This paper develops an automated approach to plan for mass tactical airborne operations. This proposed tool enables the user to properly load aircraft according to the mission and user specifications, so that the minimum amount of time is required to seize all assigned objectives. The methodology is based on a hybrid approach in which the first portion is a mathematical model that provides the optimal manifest under “perfect conditions”. This mathematical model is represented by a transportation network, and can be optimized using a transportation algorithm. The optimum solution from the mathematical model is input to a simulation model that introduces the inherent variability induced by wind conditions, drift, aircraft location and speed, and delays between jumper exit times. The simulation returns the expected, best, and worst arrival times to the assigned objectives. This hybrid approach allows a large problem to be solved efficiently with a great deal of time saving.     

Gold recovery from loaded activated carbon using different solvents

The adsorption of gold complexes onto the activated carbon is the basis of modern techniques for gold recovery. The next step is the recovery of adsorbed gold from activated carbon with an efficient eluant. The objective of this study was to investigate an improved process for recovering gold from activated carbon. The process involves contact of gold laden activated carbon with a strong base at ambient temperatures followed by elution with an aqueous solution containing an organic solvent. Results showed that aqueous solutions of organic solvents, preferably aqueous solution of acetone or acetonitrile could be effectively used in the recovery of gold from loaded activated carbon which compared favorably with Zadra and AARL methods.     

Optimization of parameters for competitive adsorption of heavy metal ions (Pb+2, Ni+2, Cd+2) onto activated carbon

This study investigates optimization of various competitive adsorption parameters for removal of Cd(II), Ni(II) and Pb(II) from aqueous solutions by commercial activated carbon (AC) using the Taguchi method. Adsorption parameters such as initial metal concentration of each metal ion (C_0,i ), initial pH (pH₀), adsorbent dosage (m) and contact time (t) in batch technique were studied to observe their effects on the total adsorption capacity of metals onto activated carbon (q _tot ). The adsorbent dosage has been found to be the most significant parameter. Interactions between C_0,Cd ×C_0,Ni , C_0,Cd ×C_0,Pb and C_0,Ni ×C_0,Pb have been considered for simultaneous metal ions adsorption. The optimum condition for adsorption of metal ions were obtained with C_0,i =100 mg L^?1, pH₀=7, m=2 g L^?1 and t=80 min. Finally, experimental results showed that a multi-staged adsorptive treatment would be necessary to reach the minimal discharge standards of metal ions in the effluent.     

An approach for optimizing multiresponse simulation models

This paper describes a new procedure for optimizing multi-response simulation models. This method is based on the gradient projection technique and the use of a value function.