An accurate and easy procedure to obtain isothermal Kováts retention indices in gas chromatography

Isothermal Kováts retention indices may be used in GC for identification purposes, but they are also useful in characterisation of stationary phases and for studying structural and physico-chemical properties of both the analyte and the stationary phase. They are currently reported as whole numbers with an accuracy of one index unit for non-polar stationary phases. The method recommended for their calculation uses a linear regression model, although non-linear models have also been applied with good results. In both cases, a computer programme and the retention times of a series of n-alkanes that elute correctly and resolved from the other compounds are needed, conditions which cannot always be fulfilled. However, it is possible to calculate retention indices with an accuracy of 0.1 retention index units (0.2 units for packed columns) with the help of only three n-alkanes using just a pocket calculator or a computer spreadsheet. The main requirement is that at least one of the n-alkanes has a retention index differing by no more than one hundred retention index units from that of the analyte being investigated. Examples are given for different stationary phases.     

Standardized high-performance liquid chromatography of 182 mycotoxins and other fungal metabolites based on alkylphenone retention indices and UV-VIS spectra (diode array detection)

A general standardized method for the analysis of mycotoxins and other fungal secondary metabolites has been developed, based on high-performance liquid chromatography (HPLC) with an alkylphenone retention index and photodiode-array detection combined with thin-layer chromatography (TLC) in two different eluents. Each fungal secondary metabolite is characterized by its bracketed alkylphenone retention time index, its UV-VIS absorption maxima and its retardation factors relative to griseofulvin in two TLC eluents. This system is effective for the comparison of chemotaxonomic data in different laboratories and for a precise identification of fungi based on organic solvent extracts of fungal cultures. All important groups of mycotoxins and other fungal secondary metabolites could be detected in the HPLC system described and data are listed for 182 metabolites. The fungal secondary metabolites separated and characterized include aflatoxin B1, B2, G1 and G2, ochratoxin A, citrinin, penicillin acid, viomellein, penitrem A, patulin, sterigmatocystin, alternariol, tenuazonic acid, trichothecenes, roquefortines, fusarin C, zearalenone, PR-toxin, citreoviridin, viridicatumtoxin, verruculogen, rugulosin, cyclopiazonic acid, penicillin G and many other alkaloids, polyketides and terpenes.     

Live retention database for identification of compounds in capillary gas chromatographic analysis --Principle and structure

A live retention database for compound identification in isothermal and any step temperature programmed capillary gas chromatography has been developed. The database utilizes the Kovats retention indices of compounds on a given stationary phase and the retention time of n-alkanes measured at isothermal conditions on the column to be used, together with the programming parameters. Identification is performed by search operation that compares the calculated results with the retention values of unknown peaks. Cross-reference of the search results of different operating conditions is performed automatically by the database in order to increase the reliability of the identification. The error of the database conversion is ≤± 0.5 index unit, or ≤± 1% on retention time. This paper describes the principle and the structure of the database in detail. The experimental results for different calsses of compounds tested at divers operating conditions will be presented in Part Ⅱ.     

同系物保留指数作为脂肪酸气相色谱定性参数的优越性考察

在气相色谱分析中,通常采用相对保留值和Kovats保留指数作为化学物质的定性参数。相对保留值在使用中受到参考标准不一致的限制而难于推广,况且柱温对相对保留值的影响很大,其重现性还受到待鉴定物与参考标准保留值差距大小的影响。只有在待鉴定物与参考标准的保留值差距不大时,相对保留值才可靠。     

The use of predicted boiling points for the identification of halobenzenes and substituted phenols in capillary gas chromatography

Quantitative correlations between physicochemical parameters and structure of various solutes and their gas chromatographic behavior were investigated in order to predict the retention values. The identification of unknown samples in gas chromatographic routine analysis of environmental samples is enhanced by the use of these correlations in conjuction with other chromatographic methods and with mass spectrometry. The boiling points of many compounds are easily found in literature and therefore their correlation with retention values obtained in isothermal or programmed temperature analysis permit restriction of the choice of names of unknown compound to within a narrow range. The correlation between the boiling points and the retention times of chloro- and bromo-benzenes and of some chloro- and nitro- substituted phenols was investigated on non-polar capillary columns and permitted the tentative identification of many compounds belonging to these homologous series.     

Radioimpurity identification by retention index in tritium labeling

Retention indexes (RI's) on SE-30 and Carbowax 20M columns are characteristic and can be used for identification purposes. A method for predicting RI on the basis of the number of atoms and contributions from substituents and functional groups is discussed. This method establishes a structure retention index relationship (SRIR), capable of relating structure to RI and is useful for suggesting structure to match with radioactive peaks. Examples of labeled side products tentatively identified in this manner are given.     

Prediction of programmed-temperature retention values of naphthas by artificial neural networks

It is proposed for the first time a method of prediction of the programmed-temperature retention times of components of naphthas in capillary gas chromatography using artificial neural networks. People are used to predict the programmed-temperature retention time using many formulas such as the integral formula, which requires that four parameters must be determined by calculation or experiments. However the results obtained by the formula are not so good to meet the demand of industry. In order to predict retention time accurately and conveniently, artificial neural networks using five-fold cross-validation and leave-20%-out methods have been applied. Only two parameters: density and isothermal retention index were used as input vectors. The average RMS error for predicted values of five different networks was 0.18, whereas the RMS error of predictions by the integral formula was 0.69. Obviously, the predictions by neural networks were much better than predictions by the formula, and neural networks need fewer parameters than the formula. So neural networks can successfully and conveniently solve the problem of predictions of programmed-temperature retention times, and provide useful data for analysis of naphthas in petrochemical industry.     

Prediction of Programmed-temperature Retention Values of Naphthas by Artificial Neural Networks

Abstract

It is proposed for the first time a method of prediction of the programmed-temperature retention times of components of naphthas in capillary gas chromatography using artificial neural networks. People are used to predict the programmed-temperature retention time using many formulas such as the integral formula, which requires that four parameters must be determined by calculation or experiments. However the results obtained by the formula are not so good to meet the demand of industry. In order to predict retention time accurately and conveniently, artificial neural networks using five-fold cross-validation and leave-20%-out methods have been applied. Only two parameters: density and isothermal retention index were used as input vectors. The average RMS error for predicted values of five different networks was 0.18, whereas the RMS error of predictions by the integral formula was 0.69. Obviously, the predictions by neural networks were much better than predictions by the formula, and neural networks need fewer parameters than the formula. So neural networks can successfully and conveniently solve the problem of predictions of programmed-temperature retention times, and provide useful data for analysis of naphthas in petrochemical industry.     

Retention index values of hydrocarbons on open-tubular columns coated with methylsilicone liquid phases

Summary The influence of temperature and liquid phase film thickness of open-tubular (capillary) columns on the retention index values of hydrocarbons on methylsilicone liquid phases is discussed. Data obtained on methylsilicones and squalane are compared. Retention index values of 43 hydrocarbons between 40 and 70 °C on OV-101 liquid phase are listed.     

Gas chromatographic peak identification for polybrominated diphenyl ethers under different temperature programs

A method has been developed for gas chromatographic peak recognition of polybrominated diphenyl ethers (PBDEs) under different temperature programs. On the basis of an identification database of retention parameters (A, B values) of gas chromatography and retention times of the selected internal standards, the retention times of BDEs can be accurately estimated. In comparison with the experimental retention values, the predicted retention times have been proved to be very accurate. In addition, owing to only a part of BDE analytical standards are available, using 40 BDEs as a training set, the quantitative relationship between retention parameters of BDEs and molecular connectivity indexes has been found. The correlation coefficients are greater than 0.997. The A, B values of all the remaining 169 BDE congeners have been predicted.     

Retention Characteristics of Peptides in RP-LC: Peptide Retention Prediction

A review of recent results of the use of chromatographic retention data in peptide identification and in the development of procedures for peptide retention prediction is presented. In recent years, reversed phase LC (RP-LC) has become an important tool in the separation of peptides in MS analysis. A challenging problem in a further expansion of RP-LC applications is the use of already available retention information for the identification purposes simultaneously with MS–MS identification. This overview focuses on the retention characteristics suggested in LC. We will discuss the application of the retention index concept in LC, which is widely used in GC to characterize retention of organic compounds. The use of retention indices as retention characteristics of analytes in LC was first suggested at the end of 1970s, however the application of retention indices is still somewhat rare today. There are several reasons for this. One is the relatively high sensitivity and variability of retention indices to the change of parameters of chromatographic systems. Another is the chemical restrictions in the search of the universal set of reference compounds suitable for retention scaling. Several methods were suggested for the prediction of the retention times of peptides. A frequently used approach is based on the additivity scheme and calculation of the elution time through the summation of retention coefficients of amino acids constituting the peptide. Such an approach allows fairly accurate predictions of the retention time of peptides made up of not more then 15–20 amino acid residues. Additional correction factors were suggested to improve predictions including corrections for the peptide length, peptide hydrophobicity, sequence of amino acids, etc. Suggested procedures are discussed in detail. Application of predicted retention times in the identification of peptides is considered. Current status of LC retention data collections is presented.     

iMatch: a retention index tool for analysis of gas chromatography-mass spectrometry data

A method was developed to employ National Institute of Standards and Technology (NIST) 2008 retention index database information for molecular retention matching via constructing a set of empirical distribution functions (DFs) of the absolute retention index deviation to its mean value. The effects of different experimental parameters on the molecules' retention indices were first assessed. The column class, the column type, and the data type have significant effects on the retention index values acquired on capillary columns. However, the normal alkane retention index (I(norm)) with the ramp condition is similar to the linear retention index (I(T)), while the I(norm) with the isothermal condition is similar to the Kováts retention index (I). As for the I(norm) with the complex condition, these data should be treated as an additional group, because the mean I(norm) value of the polar column is significantly different from the I(T). Based on this analysis, nine DFs were generated from the grouped retention index data. The DF information was further implemented into a software program called iMatch. The performance of iMatch was evaluated using experimental data of a mixture of standards and metabolite extract of rat plasma with spiked-in standards. About 19% of the molecules identified by ChromaTOF were filtered out by iMatch from the identification list of electron ionization (EI) mass spectral matching, while all of the spiked-in standards were preserved. The analysis results demonstrate that using the retention index values, via constructing a set of DFs, can improve the spectral matching-based identifications by reducing a significant portion of false-positives.     

Collection of analytical data for benzodiazepines and benzophenones

On April 1st, 1986, amendments were made to Schedule 2 to the Misuse of Drugs Act 1971 such that 33 benzodiazepines became controlled as Class C drugs in the U.K. An analytical database has been prepared to aid the detection and identification of controlled benzodiazepines. Chromatographic properties have been measured including gas chromatography (GC) retention index values, high-performance liquid chromatography (HPLC) capacity factors and thin-layer chromatography (TLC) RF x 100 values. UV spectroscopic and mass spectrometric (MS) data have also been recorded. Analytical data (GC, TLC and MS) are also presented for benzophenones which were produced by acid hydrolysis of the parent benzodiazepines.     

非等间隔PCBs保留指数体系在光解行为研究中的应用

利用Ｃｈｕ等已建立的多氯联苯（ＰＣＢｓ）非等间隔保留指数体系,由文献中的相对保留时间计算出全部２０９种ＰＣＢｓ同类物（Ｃｏｎｇｅｎｅｒ）的保留指数（ＩＰＣＢ）。利用ＩＰＣＢ结合ＧＣ－ＭＳ对ＰＣＢ８７、ＰＣＢ１３８和ＰＣＢ１６９三种同类物的光解产物进行了定性分析,发现其光解产物主要为低氯代联苯。实验结果证明,非等间隔保留指数体系ＩＰＣＢ在ＰＣＢｓ同类物的定性分析中具有准确、实用、快捷、方便等优点。     

Retention indices in comprehensive two-dimensional gas chromatography

The identification of compounds by using gas chromatography (GC) in samples with significant complexity comprising a range of isomeric species, where characterization is based on peak retention times and mass spectra, generates uncertainty for the analyst. This leads to identification errors. The most reliable way to confirm the identification of each compound is based on authentic standard co-injection, which in several cases is economically prohibitive, and often unachievable in the time available for analysis. Retention index procedures are important tools to minimize misidentification of compounds in conventional chromatography. The introduction of comprehensive two-dimensional GC (GC × GC) for analysis of complex samples was a decisive step to increase the analytical capacity of chromatographic techniques. For many samples, the chromatographic resolution increase leads to quantitative expansion in the number of peaks identified, compared with conventional GC analysis. Notwithstanding this improved resolution, limitations still persist in correct peak identification, which suggests the use of retention indices may assist in supporting component identification in this important technique. In this work, approaches to use of the retention index in GC × GC are discussed, based on an evaluation of the literature in this area. Interpretation of effective chain length data for fatty acid methyl esters in the first and second dimensions is presented.     

GC/MS中保留指数和保留温度回归分析应用于单萜烯结构确认

GC／MS定性分析中,由于同分异构体的质谱图相似,常常出现结构鉴定错误．同分异构体化合物的保留行为具有较大地差别,采用文献保留指数和保留温度测定值回归分析方法对2篇已发表论文进行了研究,发现了对单萜烯类同分异构体结构鉴定中存在的错误,并提出可能的正确结构．文献保留指数和保留温度测定值回归分析方法可以简化GC／MS色谱峰的定性分析过程,提高定性分析的准确性,在样品定性分析中具很强的使用价值．     

A New Topologica Index X & Its Application in QSRR

For a long time, a lot of research studies have already been done to predict the chromatographic retention index values, among them, the methodology called quantitative structure-retention relationship (QSRR) is one of the widespread way permit generation of useful equations or models for the prediction of retention index for molecules. QSRR investigations in the past two decades have made significant progress and numerous papers on this topic have been published.     

Use of literature values of temperature programmed retention indexes in qualitative analysis by isothermal gas chromatography

Numerous reports have appeared on the determination of temperature programmed retention indexes in gas chromatography and although chromatographic variables should be completely consistent with published data if such indexes are to be of use, the reproduction of such rigorous parameters is quite difficult. This report presents an approximate method for using published values of temperature programmed retention indexes in isothermal chromatography. In general, the temperature dependence of the isothermal retention indexes of a number of compounds can be expressed as a series of oblique lines on a plot with retention index as the abscissa and temperature as the ordinate; the elution order of the compounds at a given, isothermal, temperature is then indicated by the points at which the compounds' oblique lines cut the horizontal line corresponding to the temperature of interest. In linear temperature programmed chromatography, the horizontal line representing isothermal operation becomes, to a first approximation, a sloping line with a gradient corresponding to the programming rate: this has been verified experimentally and may be valid over a wide range of temperatures. This line can be used to predict isothermal retention indexes for use in qualitative analysis.