Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks

Adsorption-Based Separation of Near-Azeotropic Mixtures—A Challenging Example for High-Throughput Development of Adsorbents

(2021) Dai Tang et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Computational Screening of Trillions of Metal–Organic Frameworks for High-Performance Methane Storage

(2021) Sangwon Lee et al.   ACS Applied Materials & Interfaces

Adsorption space for microporous polymers with diverse adsorbate species

(2021) Dylan M. Anstine et al.   npj Computational Materials

Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures

(2021) Zhao Li et al.   JOURNAL OF CHEMICAL PHYSICS

Efficient Models for Predicting Temperature-Dependent Henry’s Constants and Adsorption Selectivities for Diverse Collections of Molecules in Metal–Organic Frameworks

(2021) Xiaohan Yu et al.   Journal of Physical Chemistry C

Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

(2020) Ryther Anderson et al.   Journal of Chemical Theory and Computation

Impact of Chemical Features on Methane Adsorption by Porous Materials at Varying Pressures

(2020) Maryam Pardakhti et al.   Journal of Physical Chemistry C

Selecting Adsorbents to Separate Diverse Near-Azeotropic Chemicals

(2020) Farhad Gharagheizi et al.   Journal of Physical Chemistry C

Topological Descriptors Help Predict Guest Adsorption in Nanoporous Materials

(2020) Aditi S. Krishnapriyan et al.   Journal of Physical Chemistry C

A Robust Machine Learning Algorithm for the Prediction of Methane Adsorption in Nanoporous Materials

(2019) George S. Fanourgakis et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Rapid Prediction of Adsorption Isotherms of a Diverse Range of Molecules in Hyper-Cross-Linked Polymers

(2019) Dai Tang et al.   Journal of Physical Chemistry C

Design and analysis of machine learning exchange-correlation functionals via rotationally invariant convolutional descriptors

(2019) Xiangyun Lei et al.   Physical Review Materials

Data-driven design of metal–organic frameworks for wet flue gas CO2 capture

(2019) Peter G. Boyd et al.   NATURE

Efficiently Exploring Adsorption Space to Identify Privileged Adsorbents for Chemical Separations of a Diverse Set of Molecules

(2018) Dai Tang et al.   ChemSusChem

Geometrical Properties Can Predict CO2 and N2 Adsorption Performance of Metal–Organic Frameworks (MOFs) at Low Pressure

(2016) Michael Fernandez et al.   ACS Combinatorial Science

In silico screening of 4764 computation-ready, experimental metal–organic frameworks for CO2 separation

(2016) Zhiwei Qiao et al.   Journal of Materials Chemistry A

In silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm

(2016) Y. G. Chung et al.   Science Advances

Predicting multicomponent adsorption: 50 years of the ideal adsorbed solution theory

(2015) Krista S. Walton et al.   AICHE JOURNAL

What Are the Best Materials To Separate a Xenon/Krypton Mixture?

(2015) Cory M. Simon et al.   CHEMISTRY OF MATERIALS

RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials

(2015) David Dubbeldam et al.   MOLECULAR SIMULATION

High-throughput computational screening of metal–organic frameworks

(2014) Yamil J. Colón et al.   CHEMICAL SOCIETY REVIEWS

Large-Scale Quantitative Structure–Property Relationship (QSPR) Analysis of Methane Storage in Metal–Organic Frameworks

(2013) Michael Fernandez et al.   Journal of Physical Chemistry C

Atomic Property Weighted Radial Distribution Functions Descriptors of Metal–Organic Frameworks for the Prediction of Gas Uptake Capacity

(2013) Michael Fernandez et al.   Journal of Physical Chemistry C

Toward Rational Design of Metal–Organic Frameworks for Sensing Applications: Efficient Calculation of Adsorption Characteristics in Zero Loading Regime

(2012) Lev Sarkisov   Journal of Physical Chemistry C