scholarly journals Environmental Informatics and Soft Computing Paradigm: Processing of Cocos Nucifera Shell Derived Activated Carbon for Treatment of Distillery Spent Wash—A Solution to Environmental Issue

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
N. B. Raut ◽  
Dinesh Kumar Saini ◽  
G. B. Shinde
Keyword(s):  
Activated Carbon ◽  
Soft Computing ◽  
Low Cost ◽  
Cocos Nucifera ◽  
Operating Parameter ◽  
Pollution Monitoring ◽  
Coconut Shell ◽  
Spent Wash ◽  
Distillery Spent Wash ◽  
Soft Computing Techniques

Soft computing techniques are very much needed to design the environmental related systems these days. Soft computing (SC) is a set of computational methods that attempt to determine satisfactory approximate solutions to find a model for real-world problems. Techniques such as artificial neural networks, fuzzy logic, and genetic algorithms can be used in solving complex environmental problems. Self-organizing feature map (SOFM) model is proposed in monitoring and collecting of the data that are real time and static datasets acquired through pollution monitoring sensors and stations in the distilleries. In the environmental monitoring systems the ultimate requirement is to establish controls for the sensor based data acquisition systems and needs interactive and dynamic reporting services. SOFM techniques are used for data analysis and processing. The processed data is used for control system which even feeds to the treatment systems. Cocos nucifera activated carbon commonly known as coconut shell activated carbon (CSC) was utilized for the treatment of distillery spent wash. Batch and column studies were done to investigate the kinetics and effect of operating parameter on the rate of adsorption. Since the quantum of spent water generated from the sugar industry allied distillery units is huge, this low cost adsorbent is found to be an attractive economic option. Equilibrium adsorption date was generated to plot Langmuir and Tempkin adsorption isotherm. The investigation reveals that though with lower adsorption capacities CSC seems to be technically feasible solution for treating sugar distillery spent. Efforts are made in this paper to build informatics for derived activated carbon for solving the problem of treatment of distillery spent wash. Capsule. Coconut shell derived activated carbon was synthesized, characterized, and successfully employed as a low cost adsorbent for treatment of distillery spent wash.

scholarly journals Effect of Chemical Treatment on Production of Activated Carbon from Cocos nucifera L. (Coconut) Shell by Microwave Irradiation Method

2021 ◽  
Vol 4 (2) ◽  
pp. 112-116
Author(s):  
Nor Amiera Syahida Arsyad ◽  
Mohammad Khairul Azhar Abdul Razab ◽  
An’amt Mohamed Noor ◽  
Mohd Hazim Mohamad Amini ◽  
Nik Nurul Anis Nik Yusoff ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Microwave Irradiation ◽  
Phosphoric Acid ◽  
Sodium Hydroxide ◽  
Zinc Chloride ◽  
Low Cost ◽  
Cocos Nucifera ◽  
Coconut Shell ◽  
High Porosity ◽  
Microwave Irradiation Method

In recent years, activated carbon has attracted attention among researchers due to its special properties such as high porosity, highly adsorption and low cost. In this research, activated carbon has been successfully produced from the coconut shell by using the microwave irradiation method where zinc chloride (ZnCl2), phosphoric acid (H3PO4) and sodium hydroxide (NaOH) were implemented as the activating agents. The results showed that phosphoric acid has the most significant effect on the synthesized activated carbon properties. The optimum parameter for the power of microwave irradiation used was 380 W, impregnation ratio of activating agent to char was 3:1 for phosphoric acid, 2:1 for sodium hydroxide, and for 1:1 zinc chloride while concentration of each activating agents was 0.5 M with 10 minutes of activation time. All samples then were characterized by using, Moisture meter, FTIR-ATR, XRD and TGA in order to determine the functional groups, composition and element and weight loss of the activated carbon. This research could benefit the environment by recycling the agriculture waste into a new useful material as well as to keep the environment safe from pollution.

scholarly journals Preparation, Characterization and Utilization of Coconut Adsorbents as a Filter Media for Wastewater Treatment

2020 ◽  
pp. 129-138
Author(s):  
S. Kaviya ◽  
R. M. Jayabalakrishnan ◽  
M. Maheswari ◽  
S. Selvakumar
Keyword(s):  
Wastewater Treatment ◽  
Activated Carbon ◽  
Surface Area ◽  
Low Cost ◽  
Coconut Shell ◽  
Morphological Properties ◽  
Filter Media ◽  
Wastewater Treatment Process ◽  
Coir Fibre ◽  
Experimental Findings

The present study investigates the characterization of different coconut based low cost adsorbents like coconut shell biochar, zinc chloride impregnated coconut shell activated carbon, coir fibre and coir geotextile and their suitability characteristics as a filter bed in different wastewater treatment process. The characterization study helps to investigate their physical, chemical and morphological properties like proximate and ultimate analysis, iodine number, decolorizing power, SEM, Surface area using BET, Particle size and Zeta potential. The experiment results showed that among the different adsorbents activated carbon has high fixed carbon content (82.99 percent), more surface area (590.8 m2 g-1), low ash content (1.31 percent) with a decolorizing power of 240-300 mg g-1. The coir fibre and coir geotextile having neutral pH with negative surface charge easily adsorbs the positive cations from aqueous solutions at highest apparent density. The experimental findings suggest that the activated adsorbent which shows better results as an effective filter media for adsorption of organic compounds and pollutants from wastewater.

Exploration of Soft Computing Approaches in Itemset Mining

2016 ◽  
pp. 1830-1856
Author(s):  
Jyothi Pillai ◽  
O. P. Vyas
Keyword(s):  
Data Mining ◽  
Soft Computing ◽  
Low Cost ◽  
Itemset Mining ◽  
Huge Data ◽  
Large Databases ◽  
Soft Computing Techniques ◽  
Good Learning ◽  
Priority Criterion ◽  
Rare Itemsets

Data Mining is largely known to extract knowledge from large databases in an attempt to discover existing trends and newer patterns. While data mining refers to information extraction, soft computing is more inclined to information processing. Using Soft Computing, the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth for achieving tractability, robustness, and low-cost solutions can be revealed. For effective knowledge discovery from large databases, both Soft Computing and Data Mining can be merged. Soft computing techniques are Fuzzy Logic (FL), Neural Network (NN), Genetic Algorithm (GA), Rough Set (RS), etc. For handling different types of uncertainty in huge data, FL and RS are highly suitable. NNs are a nonparametric, robust technique and provide good learning and generalization capabilities in data-rich environments. GAs provide efficient search algorithms for selecting a model, from mixed-media data, based on some priority criterion. In one of its realms, Association Rule Mining (ARM) and Itemset mining have been a focus of research in data mining for a decade, including finding most frequent item sets and corresponding association rules and extracting rare itemsets including temporal and fuzzy concepts in discovered patterns. The objective of this chapter is to explore the usage of Soft Computing approaches in itemset utility mining, both frequent and rare itemsets. In addition, a literature review of applications of soft computing techniques in temporal mining is described.

Exploration of Soft Computing Approaches in Itemset Mining

2014 ◽  
pp. 270-296
Author(s):  
Jyothi Pillai ◽  
O. P. Vyas
Keyword(s):  
Data Mining ◽  
Soft Computing ◽  
Low Cost ◽  
Itemset Mining ◽  
Huge Data ◽  
Large Databases ◽  
Soft Computing Techniques ◽  
Good Learning ◽  
Priority Criterion ◽  
Rare Itemsets

Data Mining is largely known to extract knowledge from large databases in an attempt to discover existing trends and newer patterns. While data mining refers to information extraction, soft computing is more inclined to information processing. Using Soft Computing, the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth for achieving tractability, robustness, and low-cost solutions can be revealed. For effective knowledge discovery from large databases, both Soft Computing and Data Mining can be merged. Soft computing techniques are Fuzzy Logic (FL), Neural Network (NN), Genetic Algorithm (GA), Rough Set (RS), etc. For handling different types of uncertainty in huge data, FL and RS are highly suitable. NNs are a nonparametric, robust technique and provide good learning and generalization capabilities in data-rich environments. GAs provide efficient search algorithms for selecting a model, from mixed-media data, based on some priority criterion. In one of its realms, Association Rule Mining (ARM) and Itemset mining have been a focus of research in data mining for a decade, including finding most frequent item sets and corresponding association rules and extracting rare itemsets including temporal and fuzzy concepts in discovered patterns. The objective of this chapter is to explore the usage of Soft Computing approaches in itemset utility mining, both frequent and rare itemsets. In addition, a literature review of applications of soft computing techniques in temporal mining is described.

Enhancing Sustainable Recycle Solid Waste to Porous Activated Carbon for Methane Uptake

2014 ◽  
Vol 705 ◽  
pp. 19-23
Author(s):  
Noor Shawal Nasri ◽  
Ramlan Noorshaheeda ◽  
Usman Dadum Hamza ◽  
Jibril Mohammed ◽  
Murtala Musa Ahmed ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Activated Carbons ◽  
Low Cost ◽  
Palm Kernel ◽  
Methane Adsorption ◽  
Coconut Shell ◽  
Palm Kernel Shell ◽  
Freundlich Isotherms ◽  
Palm Shell ◽  
Methane Uptake

Potential agro wastes (i.e palm kernel shell and coconut shell) for producing low cost activated carbon (AC) was investigated. In this study, the activated carbon was produced by carbonization, chemical impregnation with KOH and microwave irradiation. The pyrolysis was carried out at 700 °C in an inert environment for 2 h. Microwave activation was carried out at 400W for 6 minutes. Characteristics of the material were investigated using Fourier transform infrared spectroscopy (FT-IR) analysis and scanning electrode microscopy (SEM). Methane adsorption equilibrium data on the activated carbons produced were obtained using static volumetric method. Microwave palm shell activated carbon (MPAC) and microwave coconut shell activated carbon (MCAC) recorded highest methane uptake of 2.489 and 1.929 mmol/g at 3 bar, 30°C. The adsorption data were correlated with Langmuir and Freundlich isotherms. The results shows that microwave activated carbon from palm shell and coconut shell have good methane adsorption characteristics.

scholarly journals Characteristics of activated carbon from coconut shell (Cocos nucifera) through chemical activation process

2021 ◽  
Vol 733 (1) ◽  
pp. 012134
Author(s):  
M Lutfi ◽  
Hanafi ◽  
B Susilo ◽  
J Prasetyo ◽  
Sandra ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Cocos Nucifera ◽  
Chemical Activation ◽  
Coconut Shell ◽  
Activation Process

Novel Low-Cost Activated Carbon from Coconut Shell and its Adsorptive Characteristics for Carbon Dioxide

2013 ◽  
Vol 594-595 ◽  
pp. 240-244
Author(s):  
Nor Adilla Rashidi ◽  
Suzana Yusup ◽  
Azry Borhan
Keyword(s):  
Carbon Dioxide ◽  
Activated Carbon ◽  
Adsorption Capacity ◽  
Gas Adsorption ◽  
Low Cost ◽  
Operating Cost ◽  
Combustion Process ◽  
Coconut Shell ◽  
Physical Activation ◽  
Activation Process

The objective of this research is to synthesize the microporous activated carbon and test its applicability for CO2gas capture. In this study, coconut shell-based and commercial activated carbon is used as the solid adsorbent. Based on the findings, it shows that the gas adsorption capacity is correlated to the total surface area of the materials. In addition, reduction in the adsorption capacity with respect to temperature proves that the physisorption process is dominant. Higher carbon dioxide (CO2) adsorption capacity in comparison to nitrogen (N2) capacity contributes to higher CO2/N2selectivity, and confirms its applicability in the post-combustion process. Utilization of abundance agricultural wastes and one-step physical activation process is attractive as it promotes a cleaner pathway for activated carbon production, and simultaneously, reduces the total operating cost.

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