Highly efficient removal of mercury(II) ions (Hg(II)) from water has been reported by employing polymer-brush-functionalized magnetic nanoparticles (MNPs). Surface-initiated conventional radical polymerization (SI-cRP) was used to grow poly(2-aminoethyl methacrylate hydrochloride) (poly-AEMA·HCl) polymer chains on magnetite nanoparticles (Fe3O4), followed by the transformation of pendant amino groups into dithiocarbamate (DTC) groups, which showed high chelating affinity toward Hg(II) ions. This polymer-brush-based DTC-functionalized MNP (MNPs-polyAEMA·DTC) platform showed the complete removal of Hg(II) from aqueous solutions. The Hg(II) ion removal capacity and efficiency of MNPs-polyAEMA·DTC were compared with its monolayer analogue, which was derived from the direct transformation of amino groups of (3-aminopropyl) triethoxysilane (APTES)-functionalized MNPs (MNPs-APTES) to DTC functional groups (MNPs-DTC). The surface chemical modifications and higher chelating functional group density, in the case of MNPs-polyAEMA·DTC, were ascertained by transmission electron microscopy (TEM), thermogravimetric analysis (TGA), physical property measurement system (PPMS), attenuated total reflectance infrared (ATR-IR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). The Hg(II) ion removal capacity and efficiency of monolayer and polymer-brush-based DTC-functionalized MNPs (MNPs-DTC and MNPs-polyAEMA·DTC, respectively) were evaluated and compared by studying the effect of various factors on the percentage removal of Hg(II) such as adsorbent amount, temperature, and contact time. Furthermore, the adsorption behavior of MNPs-DTC and MNPs-polyAEMA·DTC was analyzed by applying Langmuir and Freundlich adsorption isotherm models. In addition, the adsorption thermodynamics, as well as the adsorption kinetics, were also evaluated in detail. The higher surface functional group density of MNPs-polyAEMA·DTC led to superior remediation characteristics toward Hg(II) ions than its monolayer analogue.

Water pollution due to increase in population and high rates of wastewater generation have become serious concerns since the last few decades. Heavy metals are amongst the main wastewater pollutants due to their ability to persist in the environment. Materials and techniques are being investigated for the treatment of heavy metals in wastewater. Cellulose is one of the materials gaining attention due to its excellent physical, chemical, and mechanical properties. Cellulose-based materials are being widely studied for the adsorption of heavy metals. This overview highlights research efforts to enhance the role of cellulose in wastewater treatment through cellulose-based materials. It also discusses the effects of cellulose modifications such as cellulose gels, cellulose composites, cellulose derivatives, functionalized cellulose, and nanocrystalline cellulose on the capacity of heavy metals adsorption.

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Water Pollution through heavy metals is the concerned issue as many industries like tanning, steel production and electroplating are the major contributors. Various toxic Heavy metals are a matter of concern as they have severe environmental and health effects. Most commonly, conventional methods are using to remove these heavy metals like precipitation, ion exchange, which are not economical and have disposal issues. Adsorption of heavy metals by different low-cost adsorbents seems to be the best option in wastewater treatment. Many agricultural by-products proved to be suitable as low-cost adsorbents for removing heavy metals efficiently in a minimum time. Lignin residues that involves both agricultural and wood residues and sometimes separated out from black liquor through precipitation have adsorption capacity and affinity comparable to other natural adsorbents. However, lignin as bio adsorbents have the advantage of less cost and gives efficient adsorption results. This study is a review of the recent literature on the use of natural lignin residues for heavy metals adsorption under different experimental scenarios.

Refactoring is a technique to make a computer program more readable and maintainable. A bad smell is an indication of some setback in the code, which requires refactoring to deal with. Many tools are available for detection and removal of these code smells. These tools vary greatly in detection methodologies and acquire different competencies. In this work, we studied different code smell detection tools minutely and try to comprehend our analysis by forming a comparative of their features and working scenario. We also extracted some suggestions on the bases of variations found in the results of both detection tools.