Estimation of Heat Capacity of 143 Pure Ionic Liquids Using Artificial Neural Network was written by Azadfar, Roohollah;Shaabanzadeh, Masoud;Hashemi-Moghaddam, Hamid;Nafchi, Abdorreza Mohammadi. And the article was included in International Journal of Thermophysics in 2022.Computed Properties of C11H20F6N2O4S2 This article mentions the following:
Based on artificial neural network (ANN), a new model is presented to estimate the heat capacity of pure ionic liquids A database for the heat capacity of ionic liquids created by extracting exptl. data from literature covering the period from 1971 to 2021 is reported. With the presented approach, heat capacity is calculated and evaluated by source data bank for 7059 data points of 143 ionic liquids The accuracies of new ANN model are evaluated by comparing with the most commonly used correlations in the literatures, and the results reveal that the proposed network provides more accurate results than other literature correlations considered in this work. The average absolute percentage deviation from the new model is only 1.14%. In the experiment, the researchers used many compounds, for example, 1-Methyl-1-propylpiperidin-1-ium bis((trifluoromethyl)sulfonyl)amide (cas: 608140-12-1Computed Properties of C11H20F6N2O4S2).
1-Methyl-1-propylpiperidin-1-ium bis((trifluoromethyl)sulfonyl)amide (cas: 608140-12-1) belongs to piperidine derivatives. The piperidine structural motif is present in numerous natural alkaloids. These include piperine, which gives black pepper its spicy taste. Industrially, piperidine is produced by the hydrogenation of pyridine, usually over a molybdenum disulfide catalyst. Pyridine can also be reduced to piperidine via a modified Birch reduction using sodium in ethanol.Computed Properties of C11H20F6N2O4S2
Referemce:
Piperidine – Wikipedia,
Piperidine | C5H11N – PubChem