Isoreticular chemistry within metal–organic frameworks for gas storage and separation
W Fan, X Zhang, Z Kang, X Liu, D Sun - Coordination chemistry reviews, 2021 - Elsevier
Precise control of the pore size and environment of metal–organic framework (MOF) is a
necessary condition for achieving high performance of gas adsorption and separation. After …
necessary condition for achieving high performance of gas adsorption and separation. After …
[HTML][HTML] Recent advances in computational modeling of MOFs: From molecular simulations to machine learning
The reticular chemistry of metal–organic frameworks (MOFs) allows for the generation of an
almost boundless number of materials some of which can be a substitute for the traditionally …
almost boundless number of materials some of which can be a substitute for the traditionally …
Big-data science in porous materials: materials genomics and machine learning
By combining metal nodes with organic linkers we can potentially synthesize millions of
possible metal–organic frameworks (MOFs). The fact that we have so many materials opens …
possible metal–organic frameworks (MOFs). The fact that we have so many materials opens …
Machine learning meets with metal organic frameworks for gas storage and separation
The acceleration in design of new metal organic frameworks (MOFs) has led scientists to
focus on high-throughput computational screening (HTCS) methods to quickly assess the …
focus on high-throughput computational screening (HTCS) methods to quickly assess the …
[HTML][HTML] New frontiers for the materials genome initiative
Abstract The Materials Genome Initiative (MGI) advanced a new paradigm for materials
discovery and design, namely that the pace of new materials deployment could be …
discovery and design, namely that the pace of new materials deployment could be …
Machine learning: accelerating materials development for energy storage and conversion
With the development of modern society, the requirement for energy has become
increasingly important on a global scale. Therefore, the exploration of novel materials for …
increasingly important on a global scale. Therefore, the exploration of novel materials for …
Effect of metal–organic framework (MOF) database selection on the assessment of gas storage and separation potentials of MOFs
Abstract Development of computation‐ready metal–organic framework databases (MOF
DBs) has accelerated high‐throughput computational screening (HTCS) of materials to …
DBs) has accelerated high‐throughput computational screening (HTCS) of materials to …
Machine learning for renewable energy materials
Achieving the 2016 Paris agreement goal of limiting global warming below 2° C and
securing a sustainable energy future require materials innovations in renewable energy …
securing a sustainable energy future require materials innovations in renewable energy …
[HTML][HTML] Big data creates new opportunities for materials research: a review on methods and applications of machine learning for materials design
Materials development has historically been driven by human needs and desires, and this is
likely to continue in the foreseeable future. The global population is expected to reach ten …
likely to continue in the foreseeable future. The global population is expected to reach ten …
Metal–organic frameworks meet scalable and sustainable synthesis
Over the past decade, metal–organic frameworks (MOFs) have emerged as enabling
materials for a wide variety of sustainable technologies, leading to their recent …
materials for a wide variety of sustainable technologies, leading to their recent …