Issue 14, 2020

Quantitative UHPSFC-MS analysis of elemental sulfur in mineral oil via derivatisation with triphenylphosphine: application to corrosive sulfur-related power transformer failure

Abstract

An ultrahigh-performance supercritical fluid chromatography–mass spectrometry (UHPSFC-MS) method has been developed as a rapid and reliable analytical method for the detection and quantification of elemental sulfur in mineral transformer oil. The method described in this paper is based on the selective reaction of elemental sulfur with triphenylphosphine (TPP). The derivatisation of elemental sulfur requires minimal sample preparation and resulted in the formation of a single compound, namely triphenylphosphine sulfide (TPPS). This derivative is quantified from the complex oil composition using electrospray ionisation-mass spectrometry (ESI-MS) in selected ion monitoring (SIM) mode, and the reported UHPSFC-MS method allows detection and quantification of the derivative at ppb levels. As sulfur contamination in mineral transformer oil has been linked to costly failures of oil/paper-based power transformers due to corrosion, the analytical approach is demonstrated through its application to mineral oil samples from in service and decommisioned power transformers. The method is ideal as a routine test or to confirm the presence of elemental sulfur in samples where corrosion has occurred.

Graphical abstract: Quantitative UHPSFC-MS analysis of elemental sulfur in mineral oil via derivatisation with triphenylphosphine: application to corrosive sulfur-related power transformer failure

Article information

Article type
Communication
Submitted
27 Mar 2020
Accepted
12 Jun 2020
First published
18 Jun 2020
This article is Open Access
Creative Commons BY license

Analyst, 2020,145, 4782-4786

Quantitative UHPSFC-MS analysis of elemental sulfur in mineral oil via derivatisation with triphenylphosphine: application to corrosive sulfur-related power transformer failure

S. B. Garcia, J. Herniman, P. Birkin, J. Pilgrim, P. Lewin, G. Wilson, G. J. Langley and R. C. D. Brown, Analyst, 2020, 145, 4782 DOI: 10.1039/D0AN00602E

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