Modeling hydrogen solubility in alcohols using machine learning models and equations of state was written by Mohammadi, Mohammad-Reza;Hadavimoghaddam, Fahimeh;Atashrouz, Saeid;Abedi, Ali;Hemmati-Sarapardeh, Abdolhossein;Mohaddespour, Ahmad. And the article was included in Journal of Molecular Liquids in 2022.HPLC of Formula: 111-77-3 This article mentions the following:
Knowledge of hydrogen (H2) solubility in alcs. is important for designing and performing various processes in chem. plants. Accurate predictions of H2 solubility in alcs. can affect the quality and applications of pharmaceuticals, perfume, cosmetics, flavor, and many others. In this work, deep echo state network (DeepESN), extreme gradient boosting (XGBoost), extreme learning machine (ELM), and multivariate adaptive regression splines (MARS) as four advanced machine learning models were utilized for predicting the H2 solubility in alcs. To this end, a complete set of H2 solubility data (673 exptl. data points) for 26 different alcs. or alc.-containing solvents is gathered over a wide range of operating pressure (0.101-110.3 MPa) and temperature (213.15-524.9 K). The XGBoost model was obtained as the best model for estimation H2 solubility in alcs. based on graphical and statistical analyses having a root mean square error of 0.0022 and coefficient of determination of 0.9946. Four well-known equations of state (EOSs) were also utilized to estimate H2 solubility in alcs., among which Redlich-Kwong EOS had the best performance. However, the accuracy of machine learning models was much higher than the EOSs. Based on sensitivity anal., pressure, temperature, and mol. weight of alcs. have the highest impact on the solubility of H2 in alcs., resp. Eventually, the Leverage approach was utilized to recognize the applicability domain of the XGBoost model and probable outlier data, the results of which show that this model has high credit for estimating the solubility of H2 in alcs. The outcome of this study can help to design the hydrogenation process in chem. plants, and the XGBoost model can act as an efficient predictor for predicting H2 solubility in alcs. In the experiment, the researchers used many compounds, for example, 2-(2-Methoxyethoxy)ethanol (cas: 111-77-3HPLC of Formula: 111-77-3).
2-(2-Methoxyethoxy)ethanol (cas: 111-77-3) belongs to ethers. Ether is less polar than esters, alcohols or amines because of the oxygen atom that is unable to participate in hydrogen bonding due to the presence of bulky alkyl groups on both sides of the oxygen atom. Ethers feature bent C–O–C linkages. In dimethyl ether, the bond angle is 111° and C–O distances are 141 pm. The barrier to rotation about the C–O bonds is low. The bonding of oxygen in ethers, alcohols, and water is similar. In the language of valence bond theory, the hybridization at oxygen is sp3.HPLC of Formula: 111-77-3
Referemce:
Ether – Wikipedia,
Ether | (C2H5)2O – PubChem