Pil Rip Jeon

Assistant Professor

Kongju National University College of Engineering

South Korea

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About

Dr. Pil Rip Jeon is an Assistant Professor at Kongju National University College of Engineering in South Korea. His research focuses on the adsorption equilibria of gases such as CO2 and CH4, advanced modeling of nonlinear dynamical systems using neural networks, and the solubility of carbon dioxide in various aqueous solutions. Additionally, he explores the implications of CO2 interaction with geological formations for enhanced fossil fuel recovery and carbon sequestration.

Articles (6)

Year:

2023

Year:

2022

Year:

2021

Year:

2021

Year:

2020

Year:

2020

Collaborators (1)

Chang-Ha Lee

Professor

Yonsei University

SOUTH KOREA

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Pil Rip Jeon

Research Interests

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Articles (6)

Review of the adsorption equilibria of CO2, CH4, and their mixture on coals and shales at high pressures for enhanced CH4 recovery and CO2 sequestration

Compact neural network modeling of nonlinear dynamical systems via the standard nonlinear operator form

Artificial neural network modelling for solubility of carbon dioxide in various aqueous solutions from pure water to brine

Reaction of drilled-cores from the Janggi basin with CO2-saturated brine from subcritical to supercritical condition of CO2: Implications on sequestration of dissolved CO2

Effect of surfactants on CO<inf>2</inf> solubility and reaction in CO<inf>2</inf>-brine-clay mineral systems during CO<inf>2</inf>-enhanced fossil fuel recovery

Prediction of CO<inf>2</inf> solubility in multicomponent electrolyte solutions up to 709 bar: Analogical bridge between hydrophobic solvation and adsorption model

Collaborators (1)

Chang-Ha Lee

Make your next move.

Pil Rip Jeon

Research Interests

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Contact this professor

About

Articles (6)

Review of the adsorption equilibria of CO2, CH4, and their mixture on coals and shales at high pressures for enhanced CH4 recovery and CO2 sequestration

Compact neural network modeling of nonlinear dynamical systems via the standard nonlinear operator form

Artificial neural network modelling for solubility of carbon dioxide in various aqueous solutions from pure water to brine

Reaction of drilled-cores from the Janggi basin with CO2-saturated brine from subcritical to supercritical condition of CO2: Implications on sequestration of dissolved CO2

Effect of surfactants on CO<inf>2</inf> solubility and reaction in CO<inf>2</inf>-brine-clay mineral systems during CO<inf>2</inf>-enhanced fossil fuel recovery

Prediction of CO<inf>2</inf> solubility in multicomponent electrolyte solutions up to 709 bar: Analogical bridge between hydrophobic solvation and adsorption model

Collaborators (1)

Chang-Ha Lee

Make your next move.

Prediction of CO<inf>2</inf> solubility in multicomponent electrolyte solutions up to 709 bar: Analogical bridge between hydrophobic solvation and adsorption model