Rapid Analysis and Time Interval Deconvolution ... - ACS Publications

Oct 17, 2016 - VUV Analytics, Inc., Cedar Park, Texas 78613, United States ... Department of Chemistry and Biochemistry, The University of Texas at Ar...
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Rapid Analysis and Time Interval Deconvolution for Comprehensive Fuel Compound Group Classification and Speciation using Gas Chromatography – Vacuum Ultraviolet Spectroscopy Phillip Walsh, Manuel Garbalena, and Kevin A. Schug Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b03226 • Publication Date (Web): 17 Oct 2016 Downloaded from http://pubs.acs.org on October 18, 2016

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Analytical Chemistry

Rapid Analysis and Time Interval Deconvolution for Comprehensive Fuel Compound Group Classification and Speciation using Gas Chromatography – Vacuum Ultraviolet Spectroscopy Phillip Walsh1, Manuel Garbalena2, and Kevin A. Schug3* 1

VUV Analytics, Inc., Cedar Park, TX

2

McKee Laboratory, Valero Energy Corporation, Sunray, TX

3

Department of Chemistry and Biochemistry, The University of Texas at Arlington, Arlington TX

*Correspondence to: 700 Planetarium Pl.; Box 19065; Arlington TX 76019-0065; (ph) 817-272-3541; (fax) 817-2723808; (email) [email protected] ABSTRACT: A time interval deconvolution (TID) method was devised to integrate a gas chromatography – vacuum ultraviolet (GC-VUV) data set in order to provide bulk characterization and speciation of finished gasoline samples. The method was demonstrated using a commercially available standard and tested on a series of ASTM gasoline proficiency samples. Very good correlation (R2 ~0.97 – 0.99) between GC-VUV and measurements using various ASTM methods was achieved. A key advantage of the TID method applied to GC-VUV datasets is that a large number of coelution events can be tolerated, resulting in significantly easier and faster separations, approximately 30 minutes in the case of gasoline. Methods for determining relative response factors, VUV reference libraries, and generalization to other types of complex samples are also discussed.

Introduction The composition of intermediate and finished petroleum products is critical to their performance and value. Analysis is required to optimize the conversion of raw petroleum into different high value products, to assess the potential impact of emissions from combusted fuels, and to answer questions of geological precursor-product relationships and conversion mechanisms.1 Petroleum products and fuels are highly complex but are composed of remarkably few different compound classes. As such, a multitude of analysis methods are needed to support separation and speciation. PIONA analysis is a term given to the broad-scale classification, based on relative mass or weight content of nparaffins (linear saturated hydrocarbons), iso-paraffins (branched-chain saturated hydrocarbons), olefins (unsaturated hydrocarbons), naphthenes (cyclic saturated hydrocarbons), and aromatics, of fuels based on the use of a variety of separation techniques. The presence of oxygenates, such as alcohols and ethers, are also commonly assessed in fuels, such as gasoline.2,3 Table 1 lists several key ASTM methods that are associated with various determinations from gasoline. Most of the methods only determine a subset of the quantities of interest. The two more comprehensive methods, ASTM D6730 and ASTM D6839, are both capable of a PIONA class breakdown and varying degrees of speciation.4,5 However, these methods tend to be quite involved in terms of instrumentation

(D6839) and/or setup (D6839, D6730). Since they rely on flame ionization detection (FID), precise control of separation conditions and retention times is required for classification or speciation. The method described in ASTM D6730 requires significant setup time due to the need to “tune” a pre-column in order to enhance certain key separations. For the method governed by ASTM D6839, several separation columns, traps, and valves are combined to isolate and determine specific classes of hydrocarbons. Beyond their complexity, the disadvantages of the more comprehensive analysis techniques are that they require long analysis times, usually between one to three hours, they can be limited to hydrocarbons with boiling points below 200 oC, and their precision can be less than desirable.6,7 As a means to supplant older and less efficient technologies, researchers have turned to comprehensive two-dimensional gas chromatography (GCxGC),8,9 including GCxGC-TOFMS,10,11 but this too can be relatively complicated, reducing its suitability for production control applications. Recently, a vacuum ultraviolet (VUV) detector has been introduced for gas chromatography (GC).12 The VUV detector can rapidly (up to 100 Hz) acquire gas phase absorption spectra from 120 – 240 nm where all molecules absorb and have a unique signature. GC-VUV excels where GC-mass spectrometry (MS) has problems, namely in the differentiation of some isomeric species and measurement of small or labile compounds. These capabilities have been shown previously in applications for aromatic

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Analytical Chemistry

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hydrocarbons,12 fatty acids,13,14 pesticides,15 and permanent gases.16 Importantly, absorption events stem from the quantized excitation of bonded (σ, π) and non-bonded (n) electrons. Classes of molecules with similar structure have similar spectral signatures, but individual compounds can still be clearly differentiated. Thus, the VUV detector provides significant capabilities for both speciation and classification of molecules in mixtures that have been at least partially resolved by GC or GCxGC.17,18 Table 1. Selection of ASTM methods used for the determination of gasoline chemical components and compound classes of interest. Mass % or Volume % of … Paraffins Isoparaffins Naphthenes Olefins Aromatics Total Saturates Oxygenates Benzene Toluene Ethyl Benzene Xylenes

ASTM Method(s)

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fins (approximate concentration range of 7.7 % - 15.2 % weight), 35 isoparaffins (0.4 % - 5.6 % weight), 38 aromatics (0.2 % - 7.2 % weight), 30 naphthenes (0.6 % - 5.8 % weight), and 25 olefins (1.0 % - 8.0 % weight), which served as background reference samples, and one 139component combined PIONA standard containing a mixture of the five PIONA classes (individual components