Computational characterization and prediction of metal-organic framework properties
arXiv:1506.08219 · doi:10.1016/j.ccr.2015.08.001
Abstract
In this introductory review, we give an overview of the computational chemistry methods commonly used in the field of metal-organic frameworks (MOFs), to describe or predict the structures themselves and characterize their various properties, either at the quantum chemical level or through classical molecular simulation. We discuss the methods for the prediction of crystal structures, geometrical properties and large-scale screening of hypothetical MOFs, as well as their thermal and mechanical properties. A separate section deals with the simulation of adsorption of fluids and fluid mixtures in MOFs.
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- Recent advances in the computational chemistry of soft porous crystals
- A Hessian-Based Assessment of Atomic Forces for Training Machine Learning Interatomic Potentials
- Elastic heterogeneity governs asymmetric adsorption-desorption in a soft porous crystal
- Adsorption superlattice stabilized by elastic interactions in a soft porous crystal