Chemoinformatic design of amphiphilic molecules for methane hydrate inhibition

• Published in: Journal of Chemometrics
• Main Authors: Di Profio, Pietro, Canale, Valentino, Marvulli, Francesca, Zappacosta, Romina, Fontana, Antonella, Siani, Gabriella, Germani, Raimondo
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2018
• Subjects: Methane hydrate
• Online Access: http://dx.doi.org/10.1002/cem.3008; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fcem.3008; https://onlinelibrary.wiley.com/doi/full/10.1002/cem.3008

Abstract Cationic surfactants and other low molecular weight compounds are known to inhibit nucleation and agglomeration of methane hydrates. In particular, tetralkylammonium salts are kinetic hydrate inhibitors; ie, they reduce the rate of hydrate formation. This work relates to the in‐silico determination of structural features of molecules modulating methane hydrate formation, as found experimentally, and the prediction of novel structures to be tested as candidate inhibitors. Experimental data for each molecule are the amount of absorbed methane. By inserting these numerical values into a chemoinformatic model, it was possible to find a mutual correlation between structural features and inhibition properties. A maximum amount of information is extracted from the structural features and experimental variables, and a model is generated to explain the relationship therebetween. Chemometric analysis was performed by using the software package Volsurf+ with the aim of finding a primary correlation between surfactant structures and their properties. Experimental parameters (pressure, temperature, and concentration) were further processed through an optimization procedure. A careful study of the chemometric analysis responses and the numerical descriptors of tested surfactants allowed to define the features of a good inhibitor, as far as the amount of absorbed gas is concerned. An external prediction is finally made to project external compounds, whose structures and critical micellar concentration are known, in a statistical model, to predict the inhibition properties of a particular molecule in advance of synthesis and testing. This method allowed to find novel amphiphilic molecules for testing as candidate inhibitors in flow‐assurance.