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Cindy Trinh, Silvia Lasala, Olivier Herbinet and Dimitrios Meimaroglou
This article investigates the applicability domain (AD) of machine learning (ML) models trained on high-dimensional data, for the prediction of the ideal gas enthalpy of formation and entropy of molecules via descriptors. The AD is crucial as it describe...
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Jianshen Zhu, Chenxi Wang, Aleksandar Shurbevski, Hiroshi Nagamochi and Tatsuya Akutsu
Inference of chemical compounds with desired properties is important for drug design, chemo-informatics, and bioinformatics, to which various algorithmic and machine learning techniques have been applied. Recently, a novel method has been proposed for th...
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Robert J. Meier
Physicochemical properties of chemicals as referred to in this review include, for example, thermodynamic properties such as heat of formation, boiling point, toxicity of molecules and the fate of molecules whenever undergoing or accelerating (catalytic)...
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Supratik Kar, Juganta K. Roy, Danuta Leszczynska and Jerzy Leszczynski
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Chun Fei Chow
Pág. 27
Activity coefficient of benzene at infinite dilution, ?8, in ionic liquids is significant for the development of a process involving these two chemicals such as extraction of benzene from hydrocarbon using ionic liquids (ILs). Nevertheless, since ionic l...
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Neeraj Tomar, Geeta Rani, Vijaypal Singh Dhaka, Praveen K. Surolia, Kalpit Gupta, Eugenio Vocaturo and Ester Zumpano
The exponentially growing energy requirements and, in turn, extensive depletion of non-restorable sources of energy are a major cause of concern. Restorable energy sources such as solar cells can be used as an alternative. However, their low efficiency i...
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