Machine learning in gas separation membrane developing: Ready for prime time
Membrane technology is a promising next-generation gas separation technology and has
drawn tremendous research interest during the past decades. Despite the advanced …
drawn tremendous research interest during the past decades. Despite the advanced …
Machine learning for membrane design in energy production, gas separation, and water treatment: a review
Membrane filtration is a major process used in the energy, gas separation, and water
treatment sectors, yet the efficiency of current membranes is limited. Here, we review the use …
treatment sectors, yet the efficiency of current membranes is limited. Here, we review the use …
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks
Metal–organic frameworks (MOFs) are a class of crystalline porous materials that exhibit a
vast chemical space owing to their tunable molecular building blocks with diverse …
vast chemical space owing to their tunable molecular building blocks with diverse …
[HTML][HTML] Assessing CH4/N2 separation potential of MOFs, COFs, IL/MOF, MOF/Polymer, and COF/Polymer composites
Separating CH 4/N 2 mixture is challenging, and performance of the existing materials is still
open to improvement. In this study, we examined both the adsorption-and membrane-based …
open to improvement. In this study, we examined both the adsorption-and membrane-based …
Combining machine learning and molecular simulations to unlock gas separation potentials of MOF membranes and MOF/polymer MMMs
Due to the enormous increase in the number of metal-organic frameworks (MOFs),
combining molecular simulations with machine learning (ML) would be a very useful …
combining molecular simulations with machine learning (ML) would be a very useful …
High-throughput screening of COF membranes and COF/polymer MMMs for helium separation and hydrogen purification
Hundreds of covalent organic frameworks (COFs) have been synthesized, and thousands of
them have been computationally designed. However, it is impractical to experimentally test …
them have been computationally designed. However, it is impractical to experimentally test …
Machine learning and in-silico screening of metal–organic frameworks for O2/N2 dynamic adsorption and separation
Y Yan, Z Shi, H Li, L Li, X Yang, S Li, H Liang… - Chemical Engineering …, 2022 - Elsevier
It remains a great challenge to separate O 2 from N 2 at room temperature. Pressure swing
adsorption (PSA) technology is a potential candidate, and the development of high …
adsorption (PSA) technology is a potential candidate, and the development of high …
Prediction of O2/N2 Selectivity in Metal–Organic Frameworks via High-Throughput Computational Screening and Machine Learning
Machine learning (ML), which is becoming an increasingly popular tool in various scientific
fields, also shows the potential to aid in the screening of materials for diverse applications. In …
fields, also shows the potential to aid in the screening of materials for diverse applications. In …
[HTML][HTML] Multi-scale design of MOF-based membrane separation for CO2/CH4 mixture via integration of molecular simulation, machine learning and process modeling …
Metal-organic framework (MOF) membranes have demonstrated high efficiency for CO 2
capture due to their wide range of pore sizes, high surface area, high porosity, and open …
capture due to their wide range of pore sizes, high surface area, high porosity, and open …
Eu-MOF and its mixed-matrix membranes as a fluorescent sensor for quantitative ratiometric pH and folic acid detection, and visible fingerprint identifying
Y Jiang, Y Huang, X Shi, Z Lu, J Ren, Z Wang… - Inorganic Chemistry …, 2021 - pubs.rsc.org
Here, we demonstrate the assembly of a new stable lanthanide-based metal–organic
framework (MOF), Eu (HDPB)(phen)(1)(HDPB=(1, 1′: 3′, 1′′-terphenyl)-3, 3′′, 5 …
framework (MOF), Eu (HDPB)(phen)(1)(HDPB=(1, 1′: 3′, 1′′-terphenyl)-3, 3′′, 5 …