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Spectrophotometry

Rapid Synergistic Cloud Point Extraction (RS-CPE) with Partial Least Squares (PLS) for the Simultaneous Determination of Chlorophenols (CPs) in Environmental Water Samples Using a Microplate Assay (MPA)

, , , , , , & show all
Pages 1719-1733 | Received 30 Dec 2019, Accepted 14 Jan 2020, Published online: 30 Jan 2020
 

Abstract

A sensitive method termed rapid synergistic cloud point extraction (RS-CPE) combined with partial least squares (PLS) was developed for the extraction and simultaneous determination of trace amounts of phenol and three detrimental chlorophenols (CPs) via a microplate assay (MPA). In this study, n-pentanol was used as a novel synergistic inducer and the linear nonionic surfactant Tergitol 15-S-7 was used as an extractant. The whole process of RS-CPE was accomplished in a few minutes without the need for the time-consuming water- or ice-bath steps used in traditional cloud point extraction. An automated and high-throughput assay using a 96-well plate allowed for the simultaneous processing of multiple samples with low sample volume requirements (approximately 200 µL). However, synchronized determination of several CPs using MPA method was problematic because of spectral interferences. Fortunately, a multivariate calibration method using PLS was applied to circumvent these limitations. Under the optimum conditions, the linear dynamic concentration ranges were from 0.5 to 15 µg/mL for 2-chlorophenol and 0.5 to 20 µg/mL for the other analytes. The detection limit range was from 0.275 to 0.419 µg/mL. The enrichment factor was up to 15.4 fold. The developed methodology was successfully applied to quantitative analysis of phenol and three CPs in water samples with recoveries from 90.0% to 109%.

Acknowledgments

In addition, we thank Gabrielle David, from Liwen Bianji, Edanz Group China (www.liwenbianji.cn/ac), for editing the English text of a draft of this article.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.

Additional information

Funding

This work was supported by the Science and Technology Infrastructure Development Program of Guangdong, China (grant numbers 2014A040401085 and 2016A020226019) and the Student Innovation Training Program of China of Guangdong Province, China (grant numbers 201710573037).

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