From Crystal to Adsorption Column: Challenges in Multiscale Computational Screening of Materials for Adsorption Separation Processes

Abstract

Multiscale material screening strategies combine molecular simulations and process modeling to identify the best performing adsorbents for a particular application, such as carbon capture. The idea to go from the properties of a single crystal to the prediction of material performance in a real process is both powerful and appealing; however, it is yet to be established how to implement it consistently. In this article, we focus on the challenges associated with the interface between molecular and process levels of description. We explore how predictions of the material performance in the actual process depend on the accuracy of molecular simulations, on the procedures to feed the equilibrium adsorption data into the process simulator, and on the structural characteristics of the pellets, which are not available from molecular simulations and should be treated as optimization parameters. The presented analysis paves the way for more consistent and robust multiscale material screening strategies.

The Role of Molecular Modeling & Simulation in the Discovery and Deployment of Metal-Organic Frameworks for Gas Storage and Separation

“…Although these simple properties are important indicators of the performance of these materials for adsorptionbased engineering applications, these metrics do not completely determine process-level objectives. [376][377][378] For instance, the usable capacity and selectivity of CO 2 are commonly used performance metrics for CO 2 capture applications, while the overall process objectives are the cost of capturing and recovering the CO 2 ($/g CO 2 ) and the productivity of the material, 378 both under CO 2 purity and recovery constraints. Since the improvements in equilibrium adsorptive selectivity and usable capacity do not necessarily translate into better process performance, we envisage the integration of process-level simulations and molecular simulations, feeding innate material properties obtained from molecular simulations into processlevel (larger length scale) simulations to account for heat and mass transfer kinetics, pressure drops in columns, etc.…”

“…to properly rank materials. 378,379 However, (i) process-level modeling requires many physical properties of the material to be known, and (ii) often, processlevel detriments to material performance can be corrected via engineering, e.g., poor thermal conductivity can be addressed by incorporating heat exchangers into the process.…”

The Role of Molecular Modeling & Simulation in the Discovery and Deployment of Metal-Organic Frameworks for Gas Storage and Separation

“…Although these simple properties are important indicators of the performance of these materials for adsorptionbased engineering applications, these metrics do not completely determine process-level objectives. [285][286][287] For instance, the usable capacity and selectivity of CO 2 are commonly used performance metrics for CO 2 capture applications, while the overall process objectives are the cost of capturing and recovering the CO 2 ($/g CO 2 ) and the productivity of the material, 287 both under CO 2 purity and recovery constraints. Since the improvements in equilibrium adsorptive selectivity and usable capacity do not necessarily translate into better pro-cess performance, we envisage the integration of process-level simulations and molecular simulations, feeding innate material properties obtained from molecular simulations into processlevel (larger length scale) simulations to account for heat and mass transfer kinetics, pressure drops in columns, etc.…”

“…to properly rank materials. 287 For example, First et al 286 combined molecular simulations [to predict adsorption isotherms] and pressure swing adsorption process modeling and optimization of e.g., the column length and pressure of adsorption and desorption, under methane recovery and purity constraints, to rank zeolites for CO 2 capture from natural gas. Interestingly, the authors found "no clear correlation between the overall cost and materialcentric metrics, such as adsorption selectivity".…”

Exploring new sources of efficiency in process-driven materials screening for post-combustion carbon capture

“…17,21,22 In this approach, key characteristic properties of adsorbent materials, such as equilibrium adsorption isotherms and micropore diffusivity of gas components, are calculated from microscale molecular simulations, however the actual performance of materials (e.g. productivity, energy consumption, purity and recovery of the product) is evaluated at the process level 22,23 using optimization of PSA/VSA processes. The current research thrust is to extend these strategies to screen a large number of porous materials available within recently assembled databases of porous solids, such as CSD, 24 CoRE-MOFs 25 and DZS.…”