Computational Design of Metal–Organic Frameworks with Unprecedented High Hydrogen Working Capacity and High Synthesizability

Abstract

Compared to conventional computational screening studies that are limited by the size of database, inverse design has a great potential to facilitate identifying new materials with optimal properties. In this work, we integrate machine learning with genetic algorithm to computationally design metal−organic frameworks (MOFs) for hydrogen storage applications at cryogenic conditions. As such, we identified 6277 MOFs that exceed the current record (37.2 g/L of NPF-200) at operating conditions between 5 and 100 bar at 77 K. MOFs, whose working capacities exceed 40.0 g/L (systembased 2025 DOE target) were also identified, where the highest working capacity obtained from this work was 41.6 g/L, which is higher than any other hypothetical MOFs reported thus far. Furthermore, synthesizability of the top performing structures was assessed by comparing relative stability with their polymorphic structures while taking into account the possibility of interpenetration. We demonstrate that our methodology can successfully design MOFs with both high hydrogen capacity and synthesizability and we anticipate our workflow can be widely applied to various other materials and applications.

Database Design for Double-Linker Metal–Organic Frameworks

“…Next, we analyzed the adsorption properties of the two groups, especially for hydrogen storage. There have been some computational works that have been conducted in this area. − Ahmed et al guided materials that optimize overall hydrogen storage performance using a combination of computational screening, synthesis, and characterization. Lu et al established classification models for hydrogen storage from the dataset obtained by GCMC computations.…”

In Silico Design of Metal–Organic Frameworks Using Cooperative Binding of Two Metal Catecholates

“…PORMAKE generates MOFs with the selected metal node, organic linker, and topology from the database. PORMAKE has been used for construction in other screening works as well. , Given that the stability of the framework is a key issue for these MOFs, we selected seven zirconium metal nodes for MOF generation since zirconium MOFs were known for having high stability and structural diversity. A combination of 93 organic building blocks containing benzene rings was employed as the organic linker.…”

Inverse design of metal-organic frameworks for direct air capture of CO2 via deep reinforcement learning

“…However, optimizing the materials with non-convex objective functions in such a high dimensional latent space can be challenging. [25] In addition, evolutionary algorithms have commonly been used to optimize the chemical design space to identify best-performing MOFs across various applications such as gas storage and separation applications [15,[26][27][28][29].…”