In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage Applications
By Rocío Mercado, Rueih-Sheng Fu, Aliaksandr V. Yakutovich, Leopold Talirz, Maciej Haranczyk, Berend Smit. Chemistry of Materials, 2018
137 citations recorded by the source corpus.
Here, we present a database of 69 840 largely novel covalent organic frameworks assembled in silico from 666 distinct organic linkers and four established synthetic routes. Due to their light weights and high internal surface areas, the frameworks are promising materials for methane storage applications. To assess their methane storage performance, we used grand-canonical Monte Carlo simulations to calculate their deliverable capacities. We demonstrate that the best structure, composed of carbon–carbon bonded triazine linkers in the tbd topology, has a predicted 65-bar deliverable capacity of 216 v STP/v, better than the best methane storage materials published to date. Using our approach, we also discovered other high-performing materials with 300 structures having calculated deliverable capacities greater than 190 v STP/v and 10% of these outperforming 200 v STP/v. To encourage screening studies of these materials for other applications, all structures and their properties were made available on the Mat...
Subfields: Inorganic Chemistry, Materials Chemistry, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/7fe6fc9809dc5570db7d6497b4c0fd33a224a06d
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In Inorganic Chemistry
In Materials Chemistry
In Mechanical Engineering
Citations in the corpus
- The Role of Machine Learning in the Understanding and Design of Materials (2020, background): “For instance, in the fi eld of nanoporous materials, this e ff ort has led to the development several hypothetical databases 22 of metal − organic frameworks (MOFs), 23 − 27 covalent organic frameworks (COFs), 28,29 and zeolites.”