Robotics & Machine Learning Daily News2024,Issue(Feb.15) :13-13.DOI:10.1016/j.fuel.2023.130308

Research Data from Virginia Polytechnic Institute and State University (Virginia Tech) Update Understanding of Machine Learning (Transport Properties of Oil-co2 Mixtures In Calcite Nanopores: Physics and Machine Learning Models)

Robotics & Machine Learning Daily News2024,Issue(Feb.15) :13-13.DOI:10.1016/j.fuel.2023.130308

Research Data from Virginia Polytechnic Institute and State University (Virginia Tech) Update Understanding of Machine Learning (Transport Properties of Oil-co2 Mixtures In Calcite Nanopores: Physics and Machine Learning Models)

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Abstract

Investigators discuss new findings in Machine Learning. According to news reporting out of Blacksburg, Virginia, by NewsRx editors, research stated, “Fundamental understanding and quantitative models of the transport properties of oil-CO2 mixtures in nanopores are indispensable for physics-based models of CO2-enhanced oil recovery in unconventional oil reservoirs. This study determines the Maxwell- Stefan (M-S) diffusivities of CO2-decane (1: CO2; 2: decane /C10) mixtures in calcite nanopores with compositions relevant to CO2 Huff-n-Puff by molecular dynamics (MD) simulations.”

Key words

Blacksburg/Virginia/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning/Virginia Polytechnic Institute and State University (Virginia Tech)

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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被引量1
参考文献量55
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