Researchers from University of Edinburgh Describe Findings in Ma- chine Learning [Estimating Gas Sorption In Polymeric Membranes From the Molecular Structure: a Machine Learning Based Group Contribution Method for the Non-equilibrium Lattice Fluid ...]

Robotics & Machine Learning Daily News2024，Issue(Feb.2) ：64-65.DOI:10.1016/j.memsci.2023.122220

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Researchers from University of Edinburgh Describe Findings in Ma- chine Learning [Estimating Gas Sorption In Polymeric Membranes From the Molecular Structure: a Machine Learning Based Group Contribution Method for the Non-equilibrium Lattice Fluid ...]

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Abstract

2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learning have been published. According to news originating from Edinburgh, United Kingdom, by NewsRx correspondents, research stated, “Since its incep- tion, the non-equilibrium lattice fluid (NELF) model has become a vital tool in correlating and predicting the gas solubility behaviour in glassy polymeric membranes. But like its equilibrium variant, the NELF model is highly constrained by the availability of the pure polymer characteristic parameters, which are not always convenient to obtain as the need arises.” Financial support for this research came from Royal Society of Edinburgh (RSE).

Key words

Edinburgh/United Kingdom/Europe/Cyborgs/Emerging Tech- nologies/Machine Learning/University of Edinburgh

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2024

Robotics & Machine Learning Daily News

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