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Adsorption Thermodynamics for Process Simulation

delete2024-10-28
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PRE
AI
U
Usman Hamid
C
Chau‐Chyun Chen *
DOI:10.1021/acs.langmuir.4c02579delete
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摘要

摘要

En 中文
Adsorption has rapidly evolved in recent decades and is an established separation technology extensively practiced in gas separation industries and others. However, rigorous thermodynamic modeling of multicomponent adsorption equilibrium remains elusive, and industrial practitioners rely heavily on expensive and time-consuming trial-and-error pilot studies to develop adsorption units. This article highlights the need for rigorous adsorption thermodynamic models and the limitations and deficiencies of existing models such as the extended Langmuir isotherm, dual-process Langmuir isotherm, and adsorbed solution theory. It further presents a series of recent advances in the generalization of the classical Langmuir isotherm of single-component adsorption by deriving an activity coefficient model to account for the adsorbed phase adsorbate-adsorbent interactions, substituting adsorbed phase adsorbate and vacant site concentrations with activities, and extending to multicomponent competitive adsorption equilibrium, both monolayer and multilayer. Requiring a minimum set of physically meaningful model parameters, the generalized Langmuir isotherm for monolayer adsorption and the generalized Brunauer-Emmett-Teller isotherm for multilayer adsorption address various thermodynamic modeling challenges including adsorbent surface heterogeneity, isosteric enthalpies of adsorption, BET surface areas, adsorbed phase nonideality, adsorption azeotrope formation, and multilayer adsorption. Also discussed is the importance of quality adsorption data that cover sufficient temperature, pressure, and composition ranges for reliable determination of the model parameters to support adsorption process simulation, design, and optimization.
Keyword:
METAL-ORGANIC FRAMEWORK
GAS-ADSORPTION
CARBON-DIOXIDE
ADSORBENT HETEROGENEITY
EQUILIBRIUM ADSORPTION
ACTIVITY-COEFFICIENTS
CALORIMETRIC HEATS
BINARY-MIXTURES
LANGMUIR MODEL
PSA PROCESS

期刊

Langmuir 封面图
Langmuir
IF:
3.9
论文数:
5.4W
被引数:
10.6W

机构

Texas Tech University System 封面图
Texas Tech University System
学者数:
1.5W
论文数: 1.3W
被引数: 15
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