The research and development of biomass-based activated carbon (AC) has attracted much attention from researchers due to the abundant resource of biomass, including corncob waste. The urgency to find alternative and innovative applications for simple, inexpensive carbon material can be obtained by synthesizing the corncob waste which is abundant renewable resource and suitable for carbon properties. The use of chemical agent during activation process is of important to produce the desired AC, including high surface area and excellent electrical conductivity. Among the various chemical agents, KOH and ZnCl2 have been widely applied for synthesizing AC. This study aims to find out the characteristics of corncob-originated activated carbon (CAC) using these two chemical agents. Step by step of activating carbon from corncob will be determined briefly. Corncob was dried and chopped. Then it was carbonized. After that, the carbon result was soaked in each chemical agent solution, KOH and ZnCl2, in different molarity for carbon chemical activation. For physical activation, impregnated carbon was carbonized again in high temperature under inert gas atmosphere until AC was obtained. We employed scanning electron microscopy (SEM), X-Ray diffraction (XRD), and Raman Spectroscopy measurement to characterize the CAC samples. The results showed that the application of KOH and ZnCl2 at a different optimized process parameters exhibited the different results of surface morphology, structures, and crystallyte size. The crystallite size of the activated carbon using different chemical activating agents with varied concentrations is diverse enough. The XRD data revealed the average crystallite size of carbon with KOH as the activator is ∼45 nm in three different conditions. However, in the case of ZnCl2 as the activating agent, it shows the average size of ∼65 nm. This number is significantly higher than the activated carbon impregnated with KOH . Visual observation of SEM images gives an impression on the carbon pore where CACK12 posess the highest pores among those analytes. The synthesized corncob activated carbon can be used in many functional application such as energy storage materials, agriculture, and adsorbents in industrial and environmental sectors.
A neural network-direct inverse control (NN-DIC) has been simulated to automatically control the power level of nuclear reactors. This method has been tested on an Indonesian pool type multipurpose reactor, namely, Reaktor Serba Guna-GA Siwabessy (RSG-GAS). The result confirmed that this method still cannot minimize errors and shorten the learning process time. A new method is therefore needed which will improve the performance of the DIC. The objective of this study is to develop a particle swarm optimization-based direct inverse control (PSO-DIC) to overcome the weaknesses of the NN-DIC. In the proposed PSO-DIC, the PSO algorithm is integrated into the DIC technique to train the weights of the DIC controller. This integration is able to accelerate the learning process. To improve the performance of the system identification, a backpropagation (BP) algorithm is introduced into the PSO algorithm. To show the feasibility and effectiveness of this proposed PSO-DIC technique, a case study on power level control of RSG-GAS is performed. The simulation results confirm that the PSO-DIC has better performance than NN-DIC. The new developed PSO-DIC has smaller steady-state error and less overshoot and oscillation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.