Study on the Effect of Fly Ash in Geopolymer Cement

The utilization of by-product and solid waste of the industry in attempt as a replacement for the ordinary Portland cement (OPC) have been rapidly researched and investigated in recent years. The resultant product, also known as geopolymer cement, proves to be of significantly better than the OPC in various aspects. The quest for finding a replacement binder was mainly triggered by the great consumption of raw materials and disturbingly high emmision of CO2 in the production of OPC. Hence, the use of fly ash in geopolymer cement is duely investigated to find a more efficient binder in the casing annulus. Fly ash based geopolymer are environment friendly and are expected to solve many problems of disposing these by-products of coal at various landfills in the World. Fly ash is also much more resistant than OPC against chemical or acidic reaction and fire, have longer durability, higher pumpability and cost effective. This paper will present the work carried out to study the effect of fly ash in geopolymer cement. Fly ash is rich in alumina and silica, thus when dissolved in alkaline solution form an aluminosilicate gel that binds the elements together to form a good geopolymer cement. Fly ash is mixed with the alkaline solution, preferably NaOH, and Na2SiO3 solution to form a geopolymer paste, before which several tests done to investigate its advantages. Fly ash based geopolymer cement is an excellent alternative to OPC, with proven advantages

Study on the Effect of Fly Ash in Geopolymer Cement

The utilization of by-product and solid waste of the industry in attempt as a replacement for the ordinary Portland cement (OPC) have been rapidly researched and investigated in recent years. The resultant product, also known as geopolymer cement, proves to be of significantly better than the OPC in various aspects. The quest for finding a replacement binder was mainly triggered by the great consumption of raw materials and disturbingly high emmision of CO2 in the production of OPC. Hence, the use of fly ash in geopolymer cement is duely investigated to find a more efficient binder in the casing annulus. Fly ash based geopolymer are environment friendly and are expected to solve many problems of disposing these by-products of coal at various landfills in the World. Fly ash is also much more resistant than OPC against chemical or acidic reaction and fire, have longer durability, higher pumpability and cost effective. This paper will present the work carried out to study the effect of fly ash in geopolymer cement. Fly ash is rich in alumina and silica, thus when dissolved in alkaline solution form an aluminosilicate gel that binds the elements together to form a good geopolymer cement. Fly ash is mixed with the alkaline solution, preferably NaOH, and Na2SiO3 solution to form a geopolymer paste, before which several tests done to investigate its advantages. Fly ash based geopolymer cement is an excellent alternative to OPC, with proven advantages

Preliminary Studies on the fluctuation of the biomass of sizefractionated zooplankton in sea grass bed of Pulau Tinggi, Malaysia

Zooplanktons biomass was extensively studied in the sea grass bed of Pulau Tinggi, Malaysia for six months. In 2015, sampling months were April, June, October, whereas in 2016, April, June, August were the sampling months. A cone shaped plankton net was used with 0.30 m mouth, 1.00 m length and 100 μm mesh size. The fractionation of zooplankton size was carried out in to >2000 μm (large), 501-2000 μm (medium) and <500 μm (small). Zooplankton was classified as copepods, larvaceans, chaetognaths, cnidarians, ctenophores, decapods and polychaetes. Copepods were categorized as Calanoida, Poecilostomatoida, Cyclopoida and Harpacticoida but identified as a total of 54 species, 26 genera and 19 families. We conclude that among the biomass of 3 size fractions; medium (36%) was dominant followed by large and small (32% each) throughout the study period

Integrated bio-search approaches with multi-objective algorithms for optimization and classification problem

Optimal selection of features is very difficult and crucial to achieve, particularly for the task of classification. It is due to the traditional method of selecting features that function independently and generated the collection of irrelevant features, which therefore affects the quality of the accuracy of the classification. The goal of this paper is to leverage the potential of bio-inspired search algorithms, together with wrapper, in optimizing multi-objective algorithms, namely ENORA and NSGA-II to generate an optimal set of features. The main steps are to idealize the combination of ENORA and NSGA-II with suitable bio-search algorithms where multiple subset generation has been implemented. The next step is to validate the optimum feature set by conducting a subset evaluation. Eight (8) comparison datasets of various sizes have been deliberately selected to be checked. Results shown that the ideal combination of multi-objective algorithms, namely ENORA and NSGA-II, with the selected bio-inspired search algorithm is promising to achieve a better optimal solution (i.e. a best features with higher classification accuracy) for the selected datasets. This discovery implies that the ability of bio-inspired wrapper/filtered system algorithms will boost the efficiency of ENORA and NSGA-II for the task of selecting and classifying features

Optimization of attribute selection model using bio-inspired algorithms

Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. Hence, reducing the consistency of the accuracy rate. The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. This is achieved in two stages; 1) create attribute selection models by combining search method and feature selection algorithms, and 2) determine an optimized attribute set by employing bio-inspired algorithms.Classification performance of the produced attribute set is analyzed based on accuracy and number of selected attributes. Experimental results conducted on six (6) public real datasets reveal that the feature selection model with the implementation of bio-inspired search algorithm consistently performs good classification (i.e higher accuracy with fewer numbers of attributes) on the selected data set. Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction

Comparison of low-molecular-weight organic acids and ethylenediaminetetraacetic acid to enhance phytoextraction of heavy metals by maize

We compared acetic, ascorbic, and oxalic acids with ethylenediaminetetraacetic acid (EDTA) to enhance phytoextraction of nickel (Ni), manganese (Mn), zinc (Zn), copper (Cu), cadmium (Cd), and lead (Pb) by maize. Except ascorbic acid, acids significantly (P < 0.05) decreased shoot dry weight with maximum (5.60 g pot-1) recorded with ascorbic acid and minimum with oxalic acid (4.06 g pot-1). Maximum ammonium bicarbonate-diethylenetriaminepenta acetic acid (AB-DTPA)-extractable nickel (19.94 mg kg-1) was recorded with EDTA and it was minimum (10.57 mg kg-1) with oxalic acid. The EDTA significantly (P < 0.05) increased AB-DTPA-extractable lead while other acids decreased it. Except acetic acid, other acids significantly (P < 0.05) increased Ni and Zn concentration in shoots with maximum Ni (9.22 mg kg-1) and Zn (37.40 mg kg-1) with EDTA

Antimycobacterial, antimicrobial, and biocompatibility properties of para-aminosalicylic acid with zinc layered hydroxide and Zn/Al layered double hydroxide nanocomposites

The treatment of tuberculosis by chemotherapy is complicated due to multiple drug prescriptions, long treatment duration, and adverse side effects. We report here for the first time an in vitro therapeutic effect of nanocomposites based on para-aminosalicylic acid with zinc layered hydroxide (PAS-ZLH) and zinc-aluminum layered double hydroxides (PAS-Zn/Al LDH), against mycobacteria, Gram-positive bacteria, and Gram-negative bacteria. The nanocomposites demonstrated good antimycobacterial activity and were found to be effective in killing Gram-positive and Gram-negative bacteria. A biocompatibility study revealed good biocompatibility of the PAS-ZLH nanocomposites against normal human MRC-5 lung cells. The para-aminosalicylic acid loading was quantified with high-performance liquid chromatography analysis. In summary, the present preliminary in vitro studies are highly encouraging for further in vivo studies of PAS-ZLH and PAS-Zn/Al LDH nanocomposites to treat tuberculosis