Issue 7, 2023

Beyond Karl Fischer titration: a monolithic quantum cascade sensor for monitoring residual water concentration in solvents

Abstract

Quality control of liquids is an important part of analytical chemistry. The gold standard for measuring residual water in organic solvents and pharmaceutical applications is Karl Fischer titration. It has a high sensitivity, selectivity and accuracy. The downsides are a time-consuming offline analysis, together with the need for toxic reagents producing waste, and it suffers from poor inter-laboratory reproducibility. In this work, we present a high-performance lab-on-a-chip sensor exploiting mid-IR spectroscopy for liquid sensing. It is operating at 6.1 μm wavelength and is suitable for robust and flexible real-time in situ analysis of the residual water concentration in isopropyl alcohol. This is demonstrated in two experiments. A custom-made 60 μL flow cell is employed to measure only minute amounts of analyte in an inline configuration. In a second approach, the whole sensor is immersed into the analyte to demonstrate sensitive and rapid in situ operation on the millisecond time scale. This is confirmed by the ability for time resolved single water-droplet monitoring, while they are mixed into the liquid sample. We obtain a limit of detection between 120 ppm and 150 ppm with a concentration coverage spanning three orders of magnitude from 1.2 × 10−2%vol to 25%vol for the flow cell and 1.5 × 10−2%vol to 19%vol in the in situ configuration, respectively.

Graphical abstract: Beyond Karl Fischer titration: a monolithic quantum cascade sensor for monitoring residual water concentration in solvents

Supplementary files

Article information

Article type
Paper
Submitted
02 Aug 2022
Accepted
10 Feb 2023
First published
13 Feb 2023
This article is Open Access
Creative Commons BY license

Lab Chip, 2023,23, 1816-1824

Beyond Karl Fischer titration: a monolithic quantum cascade sensor for monitoring residual water concentration in solvents

F. Pilat, B. Schwarz, B. Baumgartner, D. Ristanić, H. Detz, A. M. Andrews, B. Lendl, G. Strasser and B. Hinkov, Lab Chip, 2023, 23, 1816 DOI: 10.1039/D2LC00724J

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