MOF‐based chemiresistive gas sensors: toward new functionalities
The sensing performances of gas sensors must be improved and diversified to enhance
quality of life by ensuring health, safety, and convenience. Metal–organic frameworks …
quality of life by ensuring health, safety, and convenience. Metal–organic frameworks …
FAIR data enabling new horizons for materials research
The prosperity and lifestyle of our society are very much governed by achievements in
condensed matter physics, chemistry and materials science, because new products for …
condensed matter physics, chemistry and materials science, because new products for …
Computational discovery of transition-metal complexes: from high-throughput screening to machine learning
Transition-metal complexes are attractive targets for the design of catalysts and functional
materials. The behavior of the metal–organic bond, while very tunable for achieving target …
materials. The behavior of the metal–organic bond, while very tunable for achieving target …
Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery
The modular nature of metal–organic frameworks (MOFs) enables synthetic control over
their physical and chemical properties, but it can be difficult to know which MOFs would be …
their physical and chemical properties, but it can be difficult to know which MOFs would be …
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 …
[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 …
Electronic structure modeling of metal–organic frameworks
Owing to their molecular building blocks, yet highly crystalline nature, metal–organic
frameworks (MOFs) sit at the interface between molecule and material. Their diverse …
frameworks (MOFs) sit at the interface between molecule and material. Their diverse …
Unravelling the origin of bifunctional OER/ORR activity for single-atom catalysts supported on C 2 N by DFT and machine learning
Designing high-performance bifunctional oxygen evolution/reduction reaction (OER/ORR)
catalysts is a newly emerging topic and these catalysts have wide applications in metal–air …
catalysts is a newly emerging topic and these catalysts have wide applications in metal–air …
Using machine learning and data mining to leverage community knowledge for the engineering of stable metal–organic frameworks
Although the tailored metal active sites and porous architectures of MOFs hold great promise
for engineering challenges ranging from gas separations to catalysis, a lack of …
for engineering challenges ranging from gas separations to catalysis, a lack of …
Exploring the Structural, Dynamic, and Functional Properties of Metal‐Organic Frameworks through Molecular Modeling
This review spotlights the role of atomic‐level modeling in research on metal‐organic
frameworks (MOFs), especially the key methodologies of density functional theory (DFT) …
frameworks (MOFs), especially the key methodologies of density functional theory (DFT) …