Adsorbed-Phase Activity Coefficients for Non-Ideal Mixed-Gas Adsorption
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Solution Overview
Problem
Existing models for predicting gas adsorption equilibria, such as IAST and RAST, fail to accurately account for non-ideality and azeotropic behavior in mixed-gas adsorption systems, particularly for polar gas mixtures and heterogeneous adsorbents like molecular sieves or metal organic frameworks, necessitating improved activity coefficient models.
Innovation Solution
A novel activity coefficient model derived from the non-random two-liquid theory (aNRTL) that considers adsorbate-adsorbent interactions, requiring a single binary interaction parameter per adsorbate-adsorbate pair, accurately predicts negative deviations from ideality and azeotropic behavior in mixed-gas adsorption systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the Ideal Adsorbed Solution Theory (IAST) is used to model mixed-gas adsorption, then the model is simple and easy to use, but it fails to predict adsorption equilibria for polar gas mixtures and heterogeneous adsorbents
Solution Approach 1:
The patent introduces activity coefficients as a parameter modification to the ideal model. By multiplying the ideal adsorption equilibrium pressure by the activity coefficient (γi), the model transitions from ideal to non-ideal behavior, enabling accurate prediction of polar gas mixtures and heterogeneous adsorbents while maintaining the original model's structural simplicity
Solution Approach 2:
The activity coefficient serves as an intermediary parameter that bridges the gap between ideal and real adsorption behavior. This intermediary allows the model to account for molecular polarity and surface heterogeneity effects without requiring complete reformulation of the underlying theoretical framework
2Ease of manufacture
If bulk liquid activity coefficient models (Van Laar, Wilson, NRTL, UNIQUAC) are used for adsorbate phase, then the models are well-established and easy to implement, but they fail to properly account for adsorbate-adsorbent interactions
Solution Approach 1:
The patent adapts the NRTL model by modifying the interaction energy terms to specifically represent adsorbate-adsorbent interactions rather than bulk liquid interactions. The local composition concept is applied to the adsorbed phase, where the interaction parameters reflect the unique environment at the adsorbent surface rather than bulk liquid conditions
Solution Approach 2:
The interaction energy parameters in the NRTL model are reinterpreted and reparameterized to represent adsorbate-adsorbent interaction energies (g_i0, g_j0) rather than liquid-liquid interaction energies. This parameter transformation allows the use of established model structure while achieving accurate correlation of adsorption data
3Reliability
If activity coefficient models are introduced to account for non-ideality, then prediction accuracy for polar gas mixtures improves, but the model complexity increases
Solution Approach 1:
The patent segments the adsorption model into distinct components: the ideal adsorption framework (IAST) and the non-ideality correction (activity coefficients). This segmentation allows practitioners to understand and implement each component separately, reducing the perceived complexity while maintaining overall accuracy
Solution Approach 2:
The activity coefficient model serves multiple functions simultaneously: it corrects for polar interactions, accounts for surface heterogeneity, and maintains consistency with ideal adsorption theory. This multi-functionality reduces the need for separate correction models for different types of non-ideal behavior
Data Source
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AI summary
A method and system for adsorbed phase activity coefficients for mixed-gas adsorption includes: providing one or more processors, a memory communicably coupled to the one or more processors and an input/output device communicably coupled to the one or more processors; calculating a first gas activity coefficient γ1 for a first gas using the one or more processors and a first equation; calculating a second gas activity coefficient y2 for a second gas using the one or more processors and a second equation based on a bulk mole fraction of the first gas; providing the first gas activity coefficient y1 for the first gas and the second gas activity coefficient y2 for the second gas to the input/output device; and using the first gas activity coefficient y1 for the first gas and the second gas activity coefficient y2 for the second gas in the gas adsorption system.