[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 …
Machine learning accelerates the investigation of targeted MOFs: performance prediction, rational design and intelligent synthesis
Metal-organic frameworks (MOFs) are a new class of nanoporous materials that are widely
used in various emerging fields due to their large specific surface area, high porosity and …
used in various emerging fields due to their large specific surface area, high porosity and …
ARC–MOF: a diverse database of metal-organic frameworks with DFT-derived partial atomic charges and descriptors for machine learning
Metal–organic frameworks (MOFs) are a class of crystalline materials composed of metal
nodes or clusters connected via semi-rigid organic linkers. Owing to their high-surface area …
nodes or clusters connected via semi-rigid organic linkers. Owing to their high-surface area …
Chemistry-informed machine learning enables discovery of DNA-stabilized silver nanoclusters with near-infrared fluorescence
DNA can stabilize silver nanoclusters (Ag N-DNAs) whose atomic sizes and diverse
fluorescence colors are selected by nucleobase sequence. These programmable …
fluorescence colors are selected by nucleobase sequence. These programmable …
Combined deep learning and classical potential approach for modeling diffusion in UiO-66
Modeling of diffusion of adsorbates through porous materials with atomistic molecular
dynamics (MD) can be a challenging task if the flexibility of the adsorbent needs to be …
dynamics (MD) can be a challenging task if the flexibility of the adsorbent needs to be …
Computational screening of MOFs and zeolites for direct air capture of carbon dioxide under humid conditions
JM Findley, DS Sholl - The Journal of Physical Chemistry C, 2021 - ACS Publications
With rising CO2 levels, it is important to develop new methods to capture CO2 directly from
air. Currently, most direct air capture (DAC) adsorbents, such as amines, rely on …
air. Currently, most direct air capture (DAC) adsorbents, such as amines, rely on …
Efficient generation of large collections of metal–organic framework structures containing well-defined point defects
High-throughput molecular simulations of metal–organic frameworks (MOFs) are a useful
complement to experiments to identify candidates for chemical separation and storage. All …
complement to experiments to identify candidates for chemical separation and storage. All …
The Open DAC 2023 dataset and challenges for sorbent discovery in direct air capture
Direct air capture (DAC) of CO2 with porous adsorbents such as metal− organic frameworks
(MOFs) has the potential to aid large-scale decarbonization. Previous screening of MOFs for …
(MOFs) has the potential to aid large-scale decarbonization. Previous screening of MOFs for …
Polymer informatics at scale with multitask graph neural networks
Artificial intelligence-based methods are becoming increasingly effective at screening
libraries of polymers down to a selection that is manageable for experimental inquiry. The …
libraries of polymers down to a selection that is manageable for experimental inquiry. The …
Phase classification of multi-principal element alloys via interpretable machine learning
There is intense interest in uncovering design rules that govern the formation of various
structural phases as a function of chemical composition in multi-principal element alloys …
structural phases as a function of chemical composition in multi-principal element alloys …