Machine learning-assisted prediction of water adsorption isotherms and cooling performance
Zhilu Liu, Dongchen Shen, Shanshan Cai, Zhengkai Tu, Song Li
Abstract
Efficient machine learning models were demonstrated to predict water adsorption isotherms of various adsorbents based on uptake pressures and structure properties, as well as predict adsorption cooling performance based on isotherm features.
Topics & Concepts
AdsorptionSorption isothermWater coolingMaterials scienceThermodynamicsChemistryPhysical chemistryPhysicsAdsorption and Cooling SystemsSolar-Powered Water Purification MethodsPhase Change Materials Research