Sustainable and Affordable Composites Built Using Microstructures Performing Better than Nanostructures for Arsenic Removal

Sritama Mukherjee, Avula Anil Kumar, Chennu Sudhakar, Ramesh Kumar, Tripti Ahuja, Biswajit Mondal, Pillalamarri Srikrishnarka, Ligy Philip, Thalappil Pradeep*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

17 Citations (Scopus)

Abstract

Arsenicosis was recognized over 104 years ago. Elevated arsenic (As) concentrations in water is faced by about 200 million people worldwide and has become one of the biggest challenges in the context of water purification. Providing sustainable and affordable solutions to tackle this menace is a need of the hour. Adsorption on advanced materials is increasingly being recognized as a potential solution. Here, we report various functionalized microcellulose-reinforced 2-line ferrihydrite composites which show outstanding As(III) and As(V) adsorption capacities. Green synthesis of the composite yields granular media with high mechanical strength which show faster adsorption kinetics in a wide pH range, irrespective of the presence of other interfering ions in water. The composites and their interaction with As(III) and As(V) were studied by XRD, HRTEM, SEM, XPS, Raman, TG, and IR spectroscopy. Performance of the media in the form of cartridge reaffirms its utility for point-of-use water purification. We show that cellulose microstructures are more efficient than corresponding nanostructures for the purpose of arsenic remediation. We have also performed an evaluation of several sustainability metrics to understand the "greenness" of the composite and its manufacturing process.

Original languageEnglish
Pages (from-to)3222-3233
Number of pages12
JournalACS Sustainable Chemistry and Engineering
Volume7
Issue number3
DOIs
Publication statusPublished - 4 Feb 2019
MoE publication typeA1 Journal article-refereed

Keywords

  • Adsorption
  • Arsenic
  • Cellulose
  • Ferrihydrite
  • Nanocomposite
  • Sustainability metrics

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