Dataset Information

Highly selective detection of methanol over ethanol by a handheld gas sensor.

ABSTRACT: Methanol poisoning causes blindness, organ failure or even death when recognized too late. Currently, there is no methanol detector for quick diagnosis by breath analysis or for screening of laced beverages. Typically, chemical sensors cannot distinguish methanol from the much higher ethanol background. Here, we present an inexpensive and handheld sensor for highly selective methanol detection. It consists of a separation column (Tenax) separating methanol from interferants like ethanol, acetone or hydrogen, as in gas chromatography, and a chemoresistive gas sensor (Pd-doped SnO2 nanoparticles) to quantify the methanol concentration. This way, methanol is measured within 2?min from 1 to 1000 ppm without interference of much higher ethanol levels (up to 62,000 ppm). As a proof-of-concept, we reliably measure methanol concentrations in spiked breath samples and liquor. This could enable the realization of highly selective sensors in emerging applications such as breath analysis or air quality monitoring.

SUBMITTER: van den Broek J

PROVIDER: S-EPMC6746816 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Highly selective detection of methanol over ethanol by a handheld gas sensor.

van den Broek J J Abegg S S Pratsinis S E SE Güntner A T AT

Nature communications 20190916 1

Methanol poisoning causes blindness, organ failure or even death when recognized too late. Currently, there is no methanol detector for quick diagnosis by breath analysis or for screening of laced beverages. Typically, chemical sensors cannot distinguish methanol from the much higher ethanol background. Here, we present an inexpensive and handheld sensor for highly selective methanol detection. It consists of a separation column (Tenax) separating methanol from interferants like ethanol, acetone ...[more]

PMID: 31527675

Similar Datasets

Project description:Methanol, a simple polar solvent, has been widely identified as an attractive carbon source to produce chemicals and fuels in bioprocesses. Specifically, to achieve recombinant protein production from methylotrophic yeasts, such as Pichia pastoris, this organic solvent can be used as a sole carbon source for growth and maintenance as well as an inducer for protein expression. However, if methanol feeding is not controlled well in such a fermentation process, accumulation of the solvent in the growth media will have a detrimental effect on the cells. Hence, monitoring the levels of methanol in these fermentation processes is a crucial step to ensure a healthy culture and maximum protein production. There are various techniques elaborated in the literature for monitoring methanol in cell cultures, but often, they appear to be expensive methods that are less affordable for many laboratories. This is because, in addition to the sophisticated equipment that is required for the analysis, the complexity of the samples retrieved from the bioprocesses necessitates laborious processing steps often involving expensive tools. In this study, a fast, simple, and sensitive method is developed to process biological samples by using the salting-out-assisted liquid-liquid extraction technique to quantify the concentration of methanol and ethanol using gas chromatography. On comparing the combinations of widely available salts and solvents, it was noticed that salting out using potassium carbonate followed by the liquid-liquid extraction of the analyte using ethyl acetate showed the best recovery. Followed by this, a validation test for the developed method was performed, which resulted in good peak resolution, linearity, and limit of detection for the quantitation of methanol and ethanol. By further assessing the tested combination, it was confirmed that its application could be extended to other matrices. Such an approach facilitates the possibility to monitor and control the methanol levels in fermentation and aids in bioprocess optimization.

Dataset Information

Highly selective detection of methanol over ethanol by a handheld gas sensor.

Publications

Highly selective detection of methanol over ethanol by a handheld gas sensor.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets