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Surface thermodynamic properties by reverse phase chromatography and visual traits using computer vision techniques on Amberlite XAD-7 acrylic-ester-resin
- Source :
- Polymers for Advanced Technologies vol.33 (2022) nr.10 p.3572-3582 [ISSN 1042-7147]
- Publication Year :
- 2022
-
Abstract
- In the current work, the surface thermodynamic properties of Amberlite XAD-7 acrylic-ester-resin have been determined. The inverse gas chromatography (IGC) technique at infinite dilution was applied to estimate the London dispersive surface free energy.ds was estimated by using the well-known Fowkes equation, Dorris-Gray relation, Hamieh-Dorris-Gray model and six other molecular models based on the values of the surface areas of organic molecules and Hamieh model considering the thermal effect. The London dispersive surface free energy values are reduced by increasing temperature in all used methods and models. The Gibbs surface free energy of the adsorption values also decreased by increasing temperature in all 14 methods such as that of Swayer-Brookman, Saint-Flour Papirer, Donnet, Brendle and Papirer, Chehimi et al, Hamieh methods (thermal method) and the methods of the enthalpy of vaporization as a function of the temperature.H0 vapoTTHORN and the standard enthalpy of formation. Delta H-f(0) and the six molecular models. The Lewis acidity parameter K-A and Lewis basicity parameter, K-D was calculated by the above stated 14 methods. The surface character "S" value was estimated to be greater than one in all the 14 methods. This indicate that the Amberlite XAD-7 polymer material contains mostly basic sites than the acidic sites, and it can be strongly interactive with an acidic media. In addition, the visual traits such as pore size distribution, surface roughness and intricate surface morphology of the polymer resin in its original form have been explored using computer vision techniques.
Details
- Database :
- OAIster
- Journal :
- Polymers for Advanced Technologies vol.33 (2022) nr.10 p.3572-3582 [ISSN 1042-7147]
- Notes :
- DOI: 10.1002/pat.5810, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1363325430
- Document Type :
- Electronic Resource