In this study, coconut husk cellulose was employed as a cost-effective and environmentally friendly adsorbent to eliminate methylene blue (MB) dye from aqueous solutions. The successful development of response surface methodology paired with a central composite design (RSM-CCD) enabled the optimization and modelling of the adsorption process. The study investigated the individual and combined effects of three variables (pH, contact time, and initial MB dye concentration) on the adsorption of MB dye onto coconut husk cellulose. The developed RSM-CCD model exhibited a remarkable degree of precision in predicting the removal efficiency of MB dye within the specified experimental parameters. This was demonstrated by the strong regression parameters, with an R2 value of 99.79% and an adjusted R2 value of 99.6%. The study depicted that the optimal parameters for attaining a 98.8827% removal of MB dye using coconut husk cellulose were as follows: an initial MB dye concentration of 30 mg∙L−1, contact time of 120 minutes, and pH 7 at a fixed adsorbent dose of 0.5 g. The Freundlich isotherm model provided the most satisfactory description of the equilibrium adsorption isotherms, suggesting that MB dye adsorption onto coconut husk cellulose occurs on a heterogeneous surface. The experimental results demonstrated a strong agreement with the pseudo-second-order kinetics model, indicating that the number of active sites present on the cellulose adsorbent predominantly influences the adsorption process of MB dye. Additionally, the adsorbent made from coconut husk cellulose exhibited the potential to be reused, as it retained its efficiency for a maximum of three cycles of adsorption of MB dye. The results of this study show that coconut husk cellulose has the potential to be an effective and sustainable adsorbent for removing MB dye from aqueous solutions.
The most significant invention made in recent years to serve various applications is software.Developing a faultless software system requires the soft-ware system design to be resilient.To make the software design more efficient,it is essential to assess the reusability of the components used.This paper proposes a software reusability prediction model named Flexible Random Fit(FRF)based on aging resilience for a Service Net(SN)software system.The reusability predic-tion model is developed based on a multilevel optimization technique based on software characteristics such as cohesion,coupling,and complexity.Metrics are obtained from the SN software system,which is then subjected to min-max nor-malization to avoid any saturation during the learning process.The feature extrac-tion process is made more feasible by enriching the data quality via outlier detection.The reusability of the classes is estimated based on a tool called Soft Audit.Software reusability can be predicted more effectively based on the pro-posed FRF-ANN(Flexible Random Fit-Artificial Neural Network)algorithm.Performance evaluation shows that the proposed algorithm outperforms all the other techniques,thus ensuring the optimization of software reusability based on aging resilient.The model is then tested using constraint-based testing techni-ques to make sure that it is perfect at optimizing and making predictions.
Access to fresh water,its availability,and its quality are a global challenge to humanity,largely due to human activities in the environment.Thus,global water security has been jeopardized,requiring urgent remediation to safeguard our very existence.Hence,a novel and facilely engineered zirconium and polyethylenimine adsorbent based on tiger nut residue (TNR) was prepared,and its adsorptive capabilities towards a model dyestuff and nutrient were invested through a batch adsorption method.The developed adsorbent,zirconium-polyethylenimine-engineered tiger nut residue (TNR@PEI–Zr) was characterised by scanning electron microscopy,Fourier-transform infrared spectroscopy,X-ray diffraction analysis,and X-ray photoelectron spectroscopy to understand its morphology and surface chemistry and predict its adsorption mechanism.TNR@PEI–Zr had a p H point of zero charge (pH_(zpc)) of 6.7.The introduction of salts inhibited the removal efficiency of Alizarin red (AR) and phosphate (PO_(4)^(3–)) in the order of HCO_(3)^(-)>SO_(4)^(2–)>Cl^(-).Increasing temperatures (293–313 K) favoured the adsorption process at pH 3.The Langmuir model suited the adsorption processes of both AR and PO_(4)^(3–),implying homogenous and monolayer removal of pollutants with a maximal capacity of 537.8 mg·g^(-1)and 100.5 mg·g^(-1)at a dose of 0.01 g,respectively.The rate-determining steps of AR and PO_(4)^(3–)followed a pseudo-secondorder kinetic model and were thermodynamically spontaneous with an increase in randomness at the solid-solution interface.The adsorbent’s recyclability was notable and outperformed most adsorbents in terms of removal efficiency.TNR@PEI–Zr was found to be stable,and its use in practical wastewater decontamination was effective,ecologically acceptable and free of secondary pollution problems.
Alexander Nti KaniEvans DoviAaron Albert AryeeRunping HanZhaohui LiLingbo Qu
A water-stable bimetallic Fe/Zrmetal-organic framework[UiO-66(Fe/Zr)]for exceptional decontamination of arsenic in water was fabricated through a facile one-step strategy.The batch adsorption experiments revealed the excellent performances with ultrafast adsorption kinetics due to the synergistic effects of two functional centers and large surface area(498.33 m^(2)/g).The absorption capacity of UiO-66(Fe/Zr)for arsenate[As(V)]and arsenite[As(III)]reached as high as 204.1 mg/g and 101.7 mg/g,respectively.Langmuir model was suitable to describe the adsorption behaviors of arsenic on UiO-66(Fe/Zr).The fast kinetics(adsorption equilibrium in 30min,10mg/L As)and pseudo-second-ordermodel implied the strong chemisorption between arsenic ions and UiO-66(Fe/Zr),which was further confirmed by DFT theoretical calculations.The results of FT-IR,XPS analysis and TCLP test demonstrated that arsenic was immobilized on the surface of UiO-66(Fe/Zr)through Fe/Zr-O-As bonds,and the leaching rates of the adsorbed As(III)and As(V)from the spent adsorbent were only 5.6%and 1.4%,respectively.UiO-66(Fe/Zr)can be regenerated for five cycles without obvious removal efficiency decrease.The original arsenic(1.0mg/L)in lake and tapwater was effectively removed in 2.0 hr[99.0%of As(III)and 99.8%of As(V)].The bimetallic UiO-66(Fe/Zr)has great potentials in water deep purification of arsenic with fast kinetics and high capacity.
Adopting organic phase change materials(PCMs) for the management of electronic devices is restricted by low thermal conductivity. In this paper, the composite PCMs are established by freeze-drying and vacuum impregnation. Herein, polyethylene glycol(PEG) is induced as heat storage materials, boron nitride(BN) is embedded as filler stacking in an orderly fashion on the foam walls to improve thermal conductivity and sodium alginate(SA) is formed as supporting material to keep the shape of the composite stable. X-ray diffractometry, scanning electron microscopy-energy dispersive spectrometer, thermal gravimetric analysis, thermal conductivity meter, differential scanning calorimeter, and Fourier transform infrared were used to characterize the samples and thermal cycles were employed to measure the shape stability. The results exhibit the BN@SA/PEG composite PCMs have good chemical compatibility, stable morphology, and thermal stability. Due to the high porosity of foam, PEG endows the composite PCMs with high latent heat(149.11 and 141.59 J·g^(-1)). Simultaneously, BN@SA/PEG shows an excellent heat performance with high thermal conductivity(0.99 W·m^(-1)·K^(-1)), reusability, and shape stability, contributing the composite PCMs to application in the energy storage field. This study provides a strategy to manufacture flexible, long-serving, and shape-stable PCMs via introducing BN@SA foam as a storage framework, and these PCMs have great potential in thermal management in the electronic field.
