保留指数是表征化合物在气相色谱中的保留的值。在实践中,通常认为保留指数仅取决于分子的结构和固定相的类型,但这种近似是不正确的。这项研究致力于研究线性温度编程模式下保留指数对色谱柱加热速率的依赖性,使用大量和多样化的数据集。在NIST20数据库中,大多数数据记录都在此模式下记录。对于基于聚(5%-二苯基-95%-二甲基)硅氧烷(5%-苯基-PDMS)的固定相,加热速率为10-15K/min的记录比例很高。在实践中,很少使用如此高的加热速率,并且使用此类数据可能会导致错误。搜索了从同一主要来源获取的多组记录,记录相同的化合物和相同的固定相,但加热速率不同。对于这些群体中的每一个,值D,保留指数对加热速率的依赖性的角系数(斜率),已计算。此值可以取正值和负值。对于极性固定相,观察到D值的最高值和最大变化,但由于其更大的实际意义,对5%-苯基-PDMS进行了进一步的考虑。对于这些固定阶段,对于芳香族和多芳香族分子观察到最高的D值;含氧化合物,相反,表现出较低的D值。对于许多三甲基甲硅烷基衍生物观察到负D值。选择756个分子的D值的数据集并在线发布。D和保留指数之间几乎没有相关性,亲脂性因子logP,和分子量。与周期数显著相关,可旋转债券的数量,并观察到芳族原子数。构建了将分子描述符与D值定量相关的线性方程。许多循环和卤素原子被证明对D值有积极的贡献,而许多氧原子和受内部旋转影响的键则有负面影响。与分子的构象刚性相关的值的强烈影响和极性的弱影响使我们可以假设熵因子对D值具有关键影响。在这项研究中,推导并提出了一个简单的估计D值的经验线性方程。比较了几种预测D的机器学习方法。通过梯度提升和随机森林显示最佳结果。然而,随机森林本身在预测保留指数时没有达到很高的准确性。
Retention indices are values that characterize the retention of a compound in gas chromatography. In practice, retention indices are often assumed to depend only on the structure of the molecule and the type of the stationary phase, but this approximation is incorrect. This
study is devoted to studying the dependence of retention indices on the column heating rate in the linear temperature programming mode, using a large and diverse data set. In the NIST 20 database, most data records are recorded in this mode. For stationary phases based on poly(5%-diphenyl-95%-dimethyl)siloxane (5%-phenyl-PDMS), there is a high proportion of records with heating rates of 10-15 K/min. In practice, such a high heating rate is rarely used and the use of such data may cause errors. A search was made for groups of records that were taken from the same primary source, recorded for the same compound and the same stationary phase, but differing in a heating rate. For each of these groups, the value D, the angular coefficient (slope) of the dependence of the retention index on the heating rate, was calculated. This value can take both positive and negative values. The highest values and the greatest variation of D values are observed for polar stationary phases, but further consideration was performed for 5%-phenyl-PDMS due to its greater practical significance. For these stationary phases, the highest D values are observed for aromatic and polyaromatic molecules; oxygen-containing compounds, on the contrary, exhibit lower D values. Negative D values are observed for many trimethylsilyl derivatives. A data set of D values for 756 molecules was selected and published online. There is almost no correlation between D and the retention index, lipophilicity factor logP, and molecular weight. Significant correlations with the number of cycles, the number of rotatable bonds, and the number of aromatic atoms were observed. Linear equations quantitatively relating the molecular descriptors to the D value were constructed. A number of cycles and halogen atoms were shown to contribute positively to the D value, while a number of oxygen atoms and bonds subject to internal rotation contributed negatively. The strong influence of the values related to the conformational rigidity of molecules and the weak influence of polarity allow us to suppose that the entropic factor has a key influence on the D value. A simple empirical linear equation for estimating the value of D is derived and presented in this
study. Several machine learning methods for predicting D are compared. The best results are shown by gradient boosting and a random forest. However, the random forest does not achieve high accuracy in predicting the retention indices themselves.