Efficient removal of greenhouse gases: machine learning-assisted exploration of metal–organic framework space
R ** these materials for useful separation applications. The ideal adsorbed solution …
An XGBoost algorithm based on molecular structure and molecular specificity parameters for predicting gas adsorption
L Li, Y Zhao, H Yu, Z Wang, Y Zhao, M Jiang - Langmuir, 2023 - ACS Publications
In this paper, an improved Extreme Gradient Boosting (XGBoost) algorithm based on the
Graph Isomorphic Network (GIN) for predicting the adsorption performance of metal–organic …
Graph Isomorphic Network (GIN) for predicting the adsorption performance of metal–organic …
Multi-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations
Our objective is to search a large candidate set of covalent organic frameworks (COFs) for
the one with the largest equilibrium adsorptive selectivity for xenon (Xe) over krypton (Kr) at …
the one with the largest equilibrium adsorptive selectivity for xenon (Xe) over krypton (Kr) at …
Efficient Exploration of Adsorption Space for Separations in Metal–Organic Frameworks Combining the Use of Molecular Simulations, Machine Learning, and Ideal …
Adsorption-based separations using metal–organic frameworks (MOFs) are promising
candidates for replacing common energy-intensive separation processes. The so-called …
candidates for replacing common energy-intensive separation processes. The so-called …
[HTML][HTML] Hypothetical yet effective: computational identification of high-performing MOFs for CO2 capture
With the advances in computational resources and algorithms, computer simulations are
being increasingly used to tackle the most challenging problems of the world. Among them …
being increasingly used to tackle the most challenging problems of the world. Among them …