High-throughput computational screening of metal–organic frameworks
There is an almost unlimited number of metal–organic frameworks (MOFs). This creates
exciting opportunities but also poses a problem: how do we quickly find the best MOFs for a …
exciting opportunities but also poses a problem: how do we quickly find the best MOFs for a …
Materials informatics with PoreBlazer v4. 0 and the CSD MOF database
The development of computational methods to explore crystalline materials has received
significant attention in the last decades. Different codes have been reported to help …
significant attention in the last decades. Different codes have been reported to help …
Machine learning in the development of adsorbents for clean energy application and greenhouse gas capture
Addressing climate change challenges by reducing greenhouse gas levels requires
innovative adsorbent materials for clean energy applications. Recent progress in machine …
innovative adsorbent materials for clean energy applications. Recent progress in machine …
Polymer nanofilms with enhanced microporosity by interfacial polymerization
Highly permeable and selective membranes are desirable for energy-efficient gas and liquid
separations. Microporous organic polymers have attracted significant attention in this …
separations. Microporous organic polymers have attracted significant attention in this …
N-Aryl–linked spirocyclic polymers for membrane separations of complex hydrocarbon mixtures
The fractionation of crude-oil mixtures through distillation is a large-scale, energy-intensive
process. Membrane materials can avoid phase changes in such mixtures and thereby …
process. Membrane materials can avoid phase changes in such mixtures and thereby …
Computation-ready, experimental metal–organic frameworks: A tool to enable high-throughput screening of nanoporous crystals
Experimentally refined crystal structures for metal–organic frameworks (MOFs) often include
solvent molecules and partially occupied or disordered atoms. This creates a major …
solvent molecules and partially occupied or disordered atoms. This creates a major …
[HTML][HTML] Metal–organic framework with optimally selective xenon adsorption and separation
Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy
economy. The mass deployment of nuclear energy as a low-emissions source requires the …
economy. The mass deployment of nuclear energy as a low-emissions source requires the …
[HTML][HTML] Direct prediction of gas adsorption via spatial atom interaction learning
Physisorption relying on crystalline porous materials offers prospective avenues for
sustainable separation processes, greenhouse gas capture, and energy storage. However …
sustainable separation processes, greenhouse gas capture, and energy storage. However …
Predicting hydrogen storage in MOFs via machine learning
The H 2 capacities of a diverse set of 918,734 metal-organic frameworks (MOFs) sourced
from 19 databases is predicted via machine learning (ML). Using only 7 structural features …
from 19 databases is predicted via machine learning (ML). Using only 7 structural features …
Noble gas adsorption in metal–organic frameworks containing open metal sites
JJ Perry IV, SL Teich-McGoldrick, ST Meek… - The Journal of …, 2014 - ACS Publications
The adsorption of noble gases (Ar, Kr, Xe, and Rn) and N2 by a diverse range of Metal–
Organic Frameworks (MOFs) containing open metal sites (OMS) was systematically …
Organic Frameworks (MOFs) containing open metal sites (OMS) was systematically …