Chiu, Po-Hao; Yang, Yan-Lin; Tsao, Heng-Kwong; Sheng, Yu-Jane published an article in 2021. The article was titled 《Deep learning for predictions of hydrolysis rates and conditional molecular design of esters》, and you may find the article in Journal of the Taiwan Institute of Chemical Engineers.COA of Formula: C5H6O2 The information in the text is summarized as follows:
The hydrolysis rate of an ester is essential for the choice of materials in sustainable and eco-friendly applications. In this work, the autoencoder (AE) model has been constructed to predict the hydrolysis rate by inputting SMILES and partial charges. Moreover, the conditional autoencoder (CAE) model has been developed to design chem. structures of esters that possess hydrolysis rates close to the desired value. By implementing the SMILES enumeration technique and the attention mechanism, our AE model exhibits significantly better performance than SPARC based on the root mean square error. For six biodegradable esters that have no exptl. rate constants, the predictions of our AE model are in agreement with those based on the activation energies calculated from Dmol3. To design an ester satisfying the desired conditions, our CAE model demonstrates its capability of providing the best candidates of esters and their rate constants based on structural similarity and the least difference of hydrolysis rates. The derived structures are similar to the desired structure and their rate constants are close to the targeted value. The results came from multiple reactions, including the reaction of Ethyl propiolate(cas: 623-47-2COA of Formula: C5H6O2)
Ethyl propiolate(cas: 623-47-2) is a clear colorless to pale yellow liquid that is soluble in ethanol, ether and chloroform. It an important organic chemical raw material and pharmaceutical intermediate. Ethyl propargylate is obtained by oxidation of propargyl alcohol to propargylic acid followed by esterification.COA of Formula: C5H6O2
Referemce:
Ester – Wikipedia,
Ester – an overview | ScienceDirect Topics