Monte-carlo simulation of gas chromatographic separation for the prediction of retention times and peak half widths

Summary A new method for prediction of gas chromatographic retention times and peak half widths is based on the renewal theory. The only requirements are the heats of vaporization of the compounds to be separated and one calibration measurement. With this data, retention times and peak half widths can be predicted for isothermal as well as temperature-programmed gas chromatography. For the separation of non-polar substances on non-polar stationary phases the prediction error for retention times is approx. 1–2%. First simulations of polar molecules and polar stationary phases indicate that this method is also applicable in these cases but some extension will be required.     

Prediction of Peptide Retention in RP-LC

The retention of small peptides can be predicted by summing the hydrophobic contribution to retention of each amino acid of peptides. But the retention time of peptides larger than 10–15 residues are less than that predicted by summing the retention coefficients of each constitutive residue. A new prediction model, considering the effects of the peptide length and contact area of each amino acid with the stationary phase for larger peptides was proposed. The model was validated by 136 peptides identified by nano-flow 2-D-LC-ESI-MS-MS platform and other retention data observed from literature. The high degree of correlation between the observed and predicted retention time by using the new model is not only good evidence for the accuracy of our predictive method, but supports the supposition that the peptide length and contact area of each amino acid with stationary phase are important factors affecting peptide retention time for larger peptide. In addition it is found that the range of peptide length is wider, the accuracy of prediction is better. The ratio coefficient of surface area of non-polar, polar and charged amino residues contacting with the stationary phase were all calculated to be less than one. Revised: 30 June and 11 August 2005     

Description of retention characteristics of calixarene-bonded stationary phases in dependence of the methanol content in the mobile phase

Calixarene-bonded stationary phases in HPLC are known to support additional interactions compared to conventional alkyl-bonded phases (π–π interactions, complex-building interactions). Thus it cannot be presumed that the same mechanisms of retention apply and that retention can be predicted in similar ways. Here 31 solutes of highly various molecular structures have been analysed at different mobile phase compositions (0–98% (v/v) methanol) in order to characterise the chromatographic behaviour of the novel stationary phases and to test the applicability of established models predicting retention factors. The influence of a change of the methanol content is discussed for non-polar, polar and ionic solutes and differences of their behaviour on the differing column types are shown. Additionally estimates about underlying retention mechanisms are given.     

Theoretical interpretation of the retention indices of alkylbenzenes

Summary The correlation between retention data of alkylbenzenes in GLC (measured on the stationary phase OV-101) and contribution of the Gibbs solvation energy are investigated in order to determine the dominant factor controlling retention. The retention in GLC can be predicted with help of our thermodynamic retention model.     

Behavior of lanthanides in countercurrent chromatography using dihexyl-N,N-diethylcarbamoyl methylene phosphonate as stationary phase

Counter-current chromatography is a real liquid-liquid chromatography. The retention volume of the solute can be calculated from the batch distribution ratio in organic separations. In the separations of metal ion, there are several complex and dissociation reactions involved in the two phases, and the retention volume cannot be always predicted from the batch distribution ratio. A mass transfer model is proposed in this paper and an expression of V(R) is derived. The retention volume of metal ion is determined not only by the batch distribution ratio but also by the mechanism of the extraction reaction. When 25% dihexyl-N,N-diethylcarbamoyl methylenephosphonate in cyclohexane is used as stationary phase and 2.91 mol/l HNO3 as mobile phase, the dynamic distribution ratios obtained from the chromatogram are not equal to but proportional to the batch distribution coefficients. These results are in agreement with the theoretical expression.     

Prediction of gas chromatographic peak width in capillary columns at different temperatures, carrier gas flows, column lengths, inside diameters and carbon numbers

Width factor (wf), relative band broadening (br) and retention factor are linearly correlated as ln wf = Inbr + ln k [Chromatographia (2002) 56, 99 -103]. The k and br are thermodynamic and kinetic energy parameters, and expanded to cover volumetric flow of carrier gas, temperature, phase ratio (beta) and carbon number (z). For columns of the same stationary phase and beta value but of different lengths, width at base (wb) can be predicted with the same numerical values of the constants. The average absolute differences between predicted and experimental wb for BP-1 columns of 30, 20 and 10 m are 1.27%, 1.21% and 1.37%, respectively. In predicting Wb of n-alkanes eluted from columns of the same stationary phase but of different ID, only the differences of ln beta are required for adjustment of one of the numerical values. The average absolute differences between Wb(cal) and Wb(exp) values for columns of 0.53, 0.32, 0.22 and 0.15 mm ID are 2.06, 3.67, 3.82 and 3.47%, respectively.     

肽段反相色谱保留时间预测算法及其在蛋白质鉴定中的应用

液相色谱-质谱(LC-MS)联用是当今规模化蛋白质鉴定的主流技术。肽段在反相液相色谱(RPLC)中的保留时间主要是由肽段的理化性质和LC条件(固定相、流动相)决定的。可以通过分析肽段的理化性质,并量化它们对肽段色谱行为的影响来预测保留时间。预测结果可以用于帮助提高蛋白质鉴定的数量和可信度,也可用于肽段的翻译后修饰等研究。现在已有的保留时间预测算法主要有保留系数法和机器学习法两大类,得到的预测保留时间与实际保留时间相关系数可达到0.93。随着色谱和质谱技术的不断发展,肽段色谱行为的稳定性和重现性越来越好,保留时间预测结果也越来越准确。预测肽段保留时间将成为提高蛋白质鉴定结果的重要技术手段之一。     

Methodology for porting retention prediction data from old to new columns and from conventional-scale to miniaturised ion chromatography systems

Several procedures are available for simulating and optimising separations in ion chromatography (IC), based on the application of retention models to an extensive database of analyte retention times on a wide range of columns. These procedures are subject to errors arising from batch-to-batch variability in the synthesis of stationary phases, or when using a column having a different diameter to that used when the database was acquired originally. Approaches are described in which the retention database can be recalibrated to accommodate changes in the stationary phase (ion-exchange selectivity coefficient and ion-exchange capacity) or in the column diameter which lead to changes in phase ratio. The entire database can be recalibrated for all analytes on a particular column by performing three isocratic separations with two analyte ions. The retention data so obtained are then used to derive a "porting" equation which is employed to generate the required simulated separation. Accurate prediction of retention times is demonstrated for both anions and cations on 2mm and 0.4mm diameter columns under elution conditions which consist of up to five sequential isocratic or linear gradient elution steps. The proposed approach gives average errors in retention time prediction of less than 3% and the correlation coefficient was 0.9849 between predicted and observed retention times for 344 data points comprising 33 anionic or cationic analytes, 5 column internal diameters and 8 complex elution profiles.     

Model for predicting comprehensive two-dimensional gas chromatography retention times

A model for approximating the relative retention of solutes in comprehensive two-dimensional gas chromatography (GCxGC) is presented. The model uses retention data from standard single-column temperature-programmed separations. The one-dimensional retention times are first converted into retention indices and then these indices are combined in a simple manner to generate a retention diagram. A retention diagram is an approximation of the two-dimensional chromatogram that has retention order and spacing in both dimensions similar to that found in the experimental chromatogram. If required, the retention diagram can be scaled to more closely resemble the two-dimensional chromatogram. The model has been tested by using retention time data from single-column gas chromatography-mass spectrometry and valve-based GCxGC. A total of 139 volatile organic compounds (VOCs) were examined. Approximately half of the VOCs had a single functional group and a linear alkyl chain (i.e., compounds with the structure Z-(CH(2))(n)-H). The retention diagrams had primary retention orders that were in excellent agreement with the GCxGC chromatograms. The relative secondary retention order for compounds with similar structures was also accurately predicted by the retention diagram. However, the relative secondary retention for compounds with dissimilar structures, such as acyclic alcohols and multi-substituted alkylbenzenes, were less accurately modeled. This study demonstrates how readily available single-column retention time data can be used to provide an a priori estimate of the relative retention of solutes in a GCxGC chromatogram. Such a capability is useful for screening possible combinations of stationary phases.     

Predicting retention data by target factor analysis and multiple regression analysis

Target factor analysis is used to predict gas-chromatographic retention indices from a training-set data matrix for 13 solutes and 15 stationary phases. In the target-combination approach, sets of data vectors are target-tested in combination and the resulting coefficients for the best model are used for prediction. Retention indices for 42 solutes and 24 stationary phases are predicted to better than 1% even with a three-factor model. In the target free-float approach, values for missing retention indices on target test vectors are predicted. Predictions from sets of target-test data selected by chemical intuition are compared to those obtained from sets of target-test data selected by using models from the combination step. The target-combination approach and multiple-regression approach are overall of similar utility for predicting new data.     

一个描述液相色谱体系中溶质进样量与保留值关系的方程

通过考虑溶质和溶剂在液相色谱体系中的相互作用,从理论上给出了一个描述溶质在液相色谱体系中进样量与保留值之间关系的方程。由方程可以证明,当进样量趋于零时,溶质的保留值为一定值,当进样量无限大时,溶质的保留值趋于零,且随着进样量的增加,溶质的保留值必然减小。通过方程的线性形式,可以获得两个描述色谱体系特征的重要参数：一个是溶质与固定相相互作用的平衡常数Ｋ,另一个是假想的分布在固定相表面上的活性点总数。     

Contribution of Steric Repulsion to Retention on an Octadecylsiloxane-Bonded Silica Stationary Phase in Reversed-Phase Liquid Chromatography

Plots of the retention factor against mobile phase composition were used to organize a varied group of solutes into three categories according to their retention mechanism on an octadecylsilioxane-bonded silica stationary phase, Ascentis ^TM C18, with acetonitrile-water and methanol-water mobile phase compositions containing 10–70% (v/v) organic solvent. The solutes in category 1 could be fit to a general retention model, Eq. (1), and exhibited normal retention behavior for the full composition range. The solutes in category 2 exhibited normal retention behavior at high organic solvent compositions with a discontinuity at low organic solvent mobile phase compositions. The solutes in category 3 exhibited a pronounced step or plateau in the middle region of the retention plots with a retention mechanism similar to category 1 at mobile phase compositions after the discontinuity and a different retention mechanism before the discontinuity. Selecting solutes and appropriate composition ranges from the three categories where a single retention mechanism was operative allowed modeling of the experimental retention factors using the solvation parameter model. These models were then used to predict retention factors for solutes excluded from the models. The overwhelming number of residual values, here defined as the difference between experimental and model predicted retention factors for the excluded solutes, could be explained by contributions from steric repulsion. The latter defined as the inability of solutes to fully insert themselves into the solvated stationary phase because of their size or conformation. Steric repulsion resulted in a systematic reduction in retention compared with predicted values for the fully inserted solute. The bonding density of the stationary phase; the type and composition of the mobile phase; and the size, conformation, type and number of functional groups on the solute are shown to affect the contribution of steric repulsion to the retention mechanism.     

糖类化合物亲水作用色谱保留行为评价

以糖类化合物为研究对象,系统评价了其在亲水模式下的色谱保留行为。分别考察了流动相、固定相和缓冲盐等对糖类化合物保留的影响,建立了糖类化合物在亲水模式下的保留方程。结果表明,糖类化合物随着流动相中乙腈比例的降低,保留时间减小;随着缓冲盐浓度的增加,保留时间增加;同时,糖类化合物的保留行为还会受到有机溶剂种类和固定相类型的影响;其保留行为可使用顶替吸附-液相相互作用模型定量描述。将该模型进一步用于实际样品中糖类化合物保留行为的预测,获得了较好的实验结果,预测保留时间与实测保留时间的相对误差小于0.3%。对糖类化合物亲水模式下的保留行为进行了系统的评价和定量描述,该研究结果将有助于糖类化合物亲水作用色谱分离方法的发展。     

Insights into the retention mechanism on an octadecylsiloxane-bonded silica stationary phase (HyPURITY C18) in reversed-phase liquid chromatography

Plots of the retention factor against mobile phase composition were used to organize a varied group of solutes into three categories according to their retention mechanism on an octadecylsiloxane-bonded silica stationary phase HyPURITY C18 with methanol-water and acetonitrile-water mobile phase compositions containing 10-70% (v/v) organic solvent. The solutes in category 1 could be fit to a general retention model, Eq. (2), and exhibited normal retention behavior for the full composition range. The solutes in category 2 exhibited normal retention behavior at high organic solvent composition with a discontinuity at low organic solvent compositions. The solutes in category 3 exhibited a pronounced step or plateau in the middle region of the retention plots with a retention mechanism similar to category 1 solutes at mobile phase compositions after the discontinuity and a different retention mechanism before the discontinuity. Selecting solutes and appropriate composition ranges from the three categories where a single retention mechanism was operative allowed modeling of the experimental retention factors using the solvation parameter model. These models were then used to predict retention factors for solutes not included in the models. The overwhelming number of residual values [log k (experimental) - log k (model predicted)] were negative and could be explained by contributions from steric repulsion, defined as the inability of the solute to insert itself fully into the stationary phase because of its bulkiness (i.e., volume and/or shape). Steric repulsion is shown to strongly depend on the mobile phase composition and was more significant for mobile phases with a low volume fraction of organic solvent in general and for mobile phases containing methanol rather than acetonitrile. For mobile phases containing less than about 20 % (v/v) organic solvent the mobile phase was unable to completely wet the stationary phase resulting in a significant change in the phase ratio and for acetonitrile (but less so methanol) changes in the solvation environment indicated by a discontinuity in the system maps.     

静态GM（0,6）灰色模型在预测气相色谱保留指数上的应用

本文从麦克雷诺（ＭｃＲｅｙｎｏｌｄｓ）相常数法出发推导了五种标准物质与任意溶质ｉ的色谱保留指数之间的关系符合灰色ＧＭ（０，６）模型，对它们进行了灰色建模。获得了很高的模型精度，并根据模型式预测了涂有不同固定液色谱柱中的溶质ｉ的保留指数。通过预测值与文献值的比较，得到了良好的预测精度。