4.7 Article

Selective colorimetric detection of dissolved ammonia in water via modified Berthelot's reaction on porous paper

期刊

SENSORS AND ACTUATORS B-CHEMICAL
卷 256, 期 -, 页码 167-175

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2017.10.069

关键词

Dissolved ammonia sensor; Colorimetric sensor; Berthelot's method; Paper-based sensor

资金

  1. Korea Ministry of Environment (MOE)
  2. Korea Environmental Industry & Technology Institute (KEITI) [ARQ201506039004] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Continuous monitoring and rapid on-site determination of toxic ammonia in various aqueous systems are important for maintaining water quality and preserving the environment. Though several methods such as flow-based spectrophotometry are currently utilized for this purpose, there is still need for more selective ammonia determination. We present a new detection route for quantifying NH3 in water samples by means of the evaporation of dissolved ammonia into headspace, followed by selective detection using a colorimetric sensor. Gaseous NH3 detection is attained by the selective formation of blue indophenol dye through modified Berthelot's reaction on porous paper. To optimize the sensing layer in terms of uniform and intense coloration, the water-soluble powder reagents were homogeneously dispersed in nonpolar cyclohexane and then deposited by a vacuum-assisted filtration on the paper substrate. The formation of indophenol blue was activated under highly humidified conditions through selective chemical reactions between solid-state Berthelot's reagents and NH3. The colorimetric response of the low-cost paper sensors was saturated within 10 min, and color change was observed by the naked eye for an ammonia solution of 10 mg/L. Furthermore, the response magnitude was not affected by addition of 0.1 wt% polar organic solvents (ethanol, acetone, dimethylformamide or acetic acid) or inorganic salts (NaCl, KCl, MgSO4 or CaSO4), suggesting a good detection cross-selectivity. (C) 2017 Elsevier B.V. All rights reserved.

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