Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights. Issue 12 (8th October 2021)

• Record Type: Journal Article
• Authors: Datar, Archit; Witman, Matthew; Lin, Li‐Chiang
• Is Part Of: AIChE journal. Volume 67:Issue 12(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-08
• Subjects: flat histogram methods -- metal–organic frameworks (MOFs) -- Monte Carlo simulations -- water adsorption -- water harvesting; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.17447
• Languages: English
• ISSNs: 0001-1541

Abstract

Abstract: Technologies based on water adsorption such as water harvesting from air have tremendous potential in mitigating important global crises such as water scarcity. An important challenge to the deployment of such technologies is finding optimal adsorbent materials. Given the large materials space of available adsorbents, large‐scale computational screening can be extremely helpful for this task. This work explores the methods and details associated with such screening procedures and recommends best practices. We also shed light on the limitations of traditionally used and inexpensive to compute prescreening approaches involving geometric and energetic features to predict water adsorption behavior of porous materials. Such approaches can provide general trends to predict adsorption behavior but may lead to the overlook of potentially important structures due to the complex nature of water adsorption. This study offers insights for future water adsorption simulations to facilitate the development of optimal water adsorbents.