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A polylactic acid-carbon nanofiber-based electro-conductive sensing material and paper-based colorimetric sensor for detection of nitrates.

Authors :
Rai P
Mehrotra S
Gautam K
Verma R
Anbumani S
Patnaik S
Priya S
Sharma SK
Source :
Analytical methods : advancing methods and applications [Anal Methods] 2024 May 16; Vol. 16 (19), pp. 3131-3141. Date of Electronic Publication: 2024 May 16.
Publication Year :
2024

Abstract

Plastics are ubiquitous in today's lifestyle, and their indiscriminate use has led to the accumulation of plastic waste in landfills and oceans. The waste accumulates and breaks into micro-particles that enter the food chain, causing severe threats to human health, wildlife, and the ecosystem. Environment-friendly and bio-based degradable materials offer a sustainable alternative to the vastly used synthetic materials. Here, a polylactic acid and carbon nanofiber-based membrane and a paper-based colorimetric sensor have been developed. The membrane had a surface area of 3.02 m <superscript>2</superscript> g <superscript>-1</superscript> and a pore size of 18.77 nm. The pores were evenly distributed with a pore volume of 0.0137 cm <superscript>3</superscript> g <superscript>-1</superscript> . The membrane was evaluated in accordance with OECD guidelines and was found to be safe for tested aquatic and terrestrial models. The activated PLA-CNF membrane was further used as a bio-based electrode for the electrochemical detection of nitrates (NO <subscript>3</subscript> <superscript>-</superscript> ) in water samples with a detection limit of 0.046 ppm and sensitivity of 1.69 × 10 <superscript>-4</superscript> A ppm <superscript>-1</superscript> mm <superscript>-2</superscript> , whereas the developed paper-based colorimetric sensor had a detection limit of 156 ppm for NO <subscript>3</subscript> <superscript>-</superscript> . This study presents an environment-friendly, low-carbon footprint disposable material for sensing applications as a sustainable alternative to plastics.

Details

Language :
English
ISSN :
1759-9679
Volume :
16
Issue :
19
Database :
MEDLINE
Journal :
Analytical methods : advancing methods and applications
Publication Type :
Academic Journal
Accession number :
38712986
Full Text :
https://doi.org/10.1039/d3ay02069j