Hung Minh Nguyen , Huy Quoc Do , Hau Bui Doan Tran , Huy Hoang Ngoc Nguyen , Thy Tan Tam Nguyen , Tuyet Thi Pham , Tuyet-Mai Tran-Thuy , Long Quang Nguyen , Dung Van Nguyen
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引用次数: 0
Abstract
Herein, magnetic activated carbon (MAC) was prepared via one-pot pyrolysis of FeCl3- and ZnCl2-loaded fallen saman leaves (FSLs). As a result, different metal-based nanoparticles (Fe(0), FeO, Fe3O4, and ZnO) were identified and evenly distributed within the activated carbon (AC) framework. MAC had a high SBET of 479 m2/g, a large Vtotal of 0.30 cm3/g, and a MS of 3.71 emu/g for magnetic separation. For application, 0.100 g/L MAC activated 2.00 mM persulfate (PS) at initial pH 3.0 to rapidly eliminate 96.5 ± 0.4 % of 50 ppm acid red 18 (AR18) within 60 min. Furthermore, quenching experiments indicated that the MAC+PS system might produce both reactive sulfate (SO4•−) and hydroxyl (•OH) radicals during AR18 treatment. Summarily, the findings highlighted the potential of multifunctional FSL-derived MAC due to its magnetic separability and effective PS activation ability towards AR18 degradation.
期刊介绍:
Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.